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bugfender2000 · 2 years ago

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Leveraging Kotlin Collections in Android Development

Kotlin has gradually replaced Java as the lingua franca of Android programming. It’s a more concise language than Java, meaning your code works harder and you can build leaner applications. And Kotlin Collections are fundamental.

These collections play a fundamental role in our work as programmers by simplifying the organization and management of data. Whether it’s a list, set, map or other data structure, they allow us to categorize and store data logically. So we can save, retrieve and manipulate information, and manage a range of tasks from simple data presentation to complex algorithm implementation.

Collections also facilitate code reusability, enabling us to utilize their existing functions and methods rather than developing individual data-handling mechanisms for every task This streamlines development, reduces errors and enhances code maintainability.

At a granular level, collections enable us to perform operations like sorting, filtering, and aggregation efficiently, improving the overall quality of our products.

Overview of Kotlin Collections

Kotlin Collections come in three primary forms: Lists, Maps, and Sets. Each is a distinct type, with its unique characteristics and use cases. Here they are:

Kotlin Lists

A Kotlin List is a sequential arrangement of elements that permit duplicate values, preserving the order in which they are added.

Elements in a list are accessed by their index, and you can have multiple elements with the same value.

Lists are a great help when storing a collection of items whose order needs to be maintained – for example, a to-do list – and storing duplicate values.

Kotlin Maps

Kotlin Maps are collections of key-value pairs. In lightweight markdown language, a method allows us to link values with distinct keys, facilitating effortless retrieval of values using their corresponding keys.

The keys are also ideal for efficient data retrieval and mapping relationships between entities.

Common use cases of Kotlin Maps include building dictionaries, storing settings, and representing relationships between objects.

Kotlin Set

A Kotlin Set is an unordered collection of distinct elements, meaning it does not allow duplicate values.

Sets are useful when you need to maintain a unique set of elements and do not require a specific order for those elements.

Common use cases of Kotlin Sets include tracking unique items, such as unique user IDs, or filtering out duplicates from a list.

The choice between lists, maps, and sets depends on your specific data requirements. Lists are suitable for ordered collections with potential duplicates, maps are ideal for key-value associations, and sets are perfect for maintaining unique, unordered elements.

Kotlin Immutable vs Mutable Collections

Kotlin provides support for both immutable and mutable collections, giving you flexibility when managing data.

Immutable Collections

Immutable collections cannot be modified once they are created. They provide both general safety and specific thread safety, making them ideal for scenarios where you want to keep the data constant. Immutable collections are created using functions like listOf() , mapOf() , and setOf() .

Mutable Collections

A mutable collection can be modified after creation. These collections are more flexible and versatile, allowing you to add, remove or modify individual elements. Mutable collections are created using functions like mutableListOf() , mutableMapOf(), and mutableSetOf().

Now that we have a foundational understanding of Kotlin collections, let’s dive deeper into each type.

Using Kotlin List

How to create a list in Kotlin

Creating a Kotlin list is straightforward. Here are two great ways to get started.

Create an immutable list

To create an immutable list we can use listOf(). Check out the following example:// Example Of listOf function fun main(args: Array<String>) { //initialize list var listA = listOf<String>("Anupam", "Singh", "Developer") //accessing elements using square brackets println(listA[0]) //accessing elements using get() println(listA.get(2)) }

In the Kotlin console, you will see the following output:[Anupam, native, android, developer]

Create a mutable list

If you want to create a mutable list, we should use the mutableListOf() method. Here is an example:// Example of mutableListOf function fun main(args: Array<String>) { //initialize a mutable list var listA = mutableListOf("Anupam", "Is", "Native") //add item to the list listA.add("Developer") //print the list println(listA) }

And this is the output :[Anupam, Is, Native, Developer]

Working with a Kotlin List

Now, we’ll look at working with list items.

Accessing elements from the List

We can reach a list item using its place or index. Here’s the first item from the cantChangeList.// get first item from list var cantChangeList = listOf<Int>(1, 2, 3) val firstItem = cantChangeList[0] println(firstItem) //Output: 1

Iterating over a list

There are multiple ways to traverse a list effectively, leveraging higher-order functions such as *forEach* or utilizing for loops. This enables you to handle the list’s elements one after the other, in sequence. For example:var MyList = listOf<Int>(1, 2, 3) // print each item from list using for loop for (element in myList) { println(element) } //output: //1 //2 //3 // print each item from list using forEach loop MyList.forEach { println(it) } // Output: // 1 // 2 // 3

Adding elements from a list

Modifying a Kotlin List is a great option for mutable lists that harness functions like *add()* , **remove()** , and set(). If we want to add an element to a list, we will simply use the add()method.// Example of add() function in list val numberAdd = mutableListOf(1, 2, 3, 4) numberAdd.add(5) println(numberAdd) //Output : [1, 2, 3, 4, 5]

Removing elements from a list

Removing elements is also a straightforward process. Here’s a coding example:// Example of remove() function in list val numberRemove = mutableListOf(1, 2, 3, 4) numberRemove.remove(3) println(numberRemove) //Output: [1, 2, 4]

Modifying List Items

Altering list items is simple. You can swap them directly with new data via their indices or by using the set commands. Here we have an example of changing an item value, either through its place marker or by using the setmethod:var myList = mutableListOf<String>("Anupam","five", "test", "change") // Changing value via index access myList[0] = "FreshValue" println(myList[0]) // Ouput: // FreshValue // Changing value using set method myList.set(0, "SetValue") println(myList[0]) // Ouput: // SetValue

Other list functions and operations

In Kotlin, list methods are essential tools when we work with collections. While there are numerous methods available, we’ll limit our focus to the most commonly used ones today.

Each of these methods brings its own unique power and utility to a Kotlin collection. Now let’s explore them in detail.

sorted() : Returns a new List with elements sorted in natural order.

sortedDescending() : Returns a new List with elements sorted in descending order.

filter() : Returns a new List containing elements that satisfy a given condition.

map() : Transforms each element of the List, based on a given predicate.

isEmpty() : Checks whether the List is empty.

Here are some key examples of these methods:

Sort a Kotlin list

This collection includes the following elements (3, 1, 7, 2, 8, 6).

Here they are in ascending order:// Ascending Sort val numbs = mutableListOf(3, 1, 7, 2, 8, 6) println(numbs) val sortedNumbs = numbs.sorted() println(sortedNumbs) //Output: // Before Sort : [3, 1, 7, 2, 8, 6] // After Sort : [1, 2, 3, 6, 7, 8]

Now, here’s an example of sorting in descending order:// Descending Sort val numbs = mutableListOf(3, 1, 7, 2, 8, 6) println(numbs) val sortedDesNumbs = numbs.sortedDescending() println(sortedDesNumbs) //Output: // Before Sort : [3, 1, 7, 2, 8, 6] // After Sort : [8, 7, 6, 3, 2, 1]

Filtering a Kotlin list

If you want to filter a Kotlin list, you can use the filter function. This allows you to specify a condition that each element of the list must satisfy in order to be included in the filtered list. Here’s an example:val listOfData = listOf("Anupam","is","native","android","developer") val longerThan5 = listOfData.filter { it.length > 5 } println(longerThan5)

In this example, we have a list of strings under the heading listOfData. We use the filter function to create a new list, longerThan5 , that contains only the strings from listOfData with a length greater than five characters.

Finally, we print the filtered list. The output will be:[Anupam, native, android, developer]

Check whether a Kotlin list is empty

Here you can use the isEmpty() function, as you can see in this example:val myList = listOf<Int>() if (myList.isEmpty()) { println("The list is empty.") } else { println("The list is not empty.") } // Output: // The list is empty.

In the following example we’ll create a list, myList , with values using the listOf() function, so the isEmpty will return false:// example of isEmpty() return false var list = listOf<String>("Anupam") if (list.isEmpty()) { println("Its empty.") } else { println("Its not empty.") } // Output: // Its not empty.

Transforming a list using map

As we mentioned earlier, the Kotlin map function is a powerful tool for transforming each element of a list into a new form. It applies a specified transformation function to each element and returns a new list with the results. This gives us a concise way to modify the elements in a list, without mutating the original collection.val numbers = listOf(1, 2, 3, 4, 5) val squaredNumbers = numbers.map { it * it } println(squaredNumbers) // Output: // [1, 4, 9, 16, 25]

In this example, we have a list called numbers, containing integers. We apply the map function to numbers and provide a lambda expression as the transformation function. The lambda expression takes each element in the numbers list and returns its square. The map function applies this transformation to each element of the list and creates a new list, squaredNumbers, with the squared values.

Searching elements in a List

Check whether element exists in the list

To search for an element in a Kotlin list, you can utilize the various methods available in the Kotlin standard library. One widely used method is the contains() function, which allows you to check whether a list contains a specific element.

Here’s an example of how you can use the contains() function in Kotlin:val myList = listOf("apple", "banana", "orange") val isElementFound = myList.contains("banana") if (isElementFound) { println("Element found!") } else { println("Element not found!") } // Output: // banana

You can also use the filter() method we mentioned earlier to filter all the elements that match a given criteria.

Search the element and get its index

Another option is to use the indexOf() method, which returns the specific position of an element in the list.val myList = listOf("apple", "banana", "orange") val index = myList.indexOf("banana") if (index != -1) { println("Element found at index $index") } else { println("Element not found in the list") } // Output: // Element found at index 1

Working with Kotlin Map

Accessing and modifying a Kotlin Map

Creating and initializing a map in Kotlin

In Kotlin, you can create and initialize a map by utilizing either the mapOf() function for immutable maps or the mutableMapOf() function for mutable maps. Here is an example of how you can create a map containing names and ages:// Immutable Map Example. Syntax is mapOf<key,value> val myImmuMap = mapOf<Int,String>(1 to "Anupam", 2 to "Singh", 3 to "Developer") for(key in myImmuMap.keys){ println(myImmuMap[key]) } // Output : // Anupam // Singh // Developer

The mapOf() function allows you to create an immutable map, ensuring that its content cannot be altered once initialized. Conversely, the **mutableMapOf()** function enables you to modify the map, transforming it into a mutable map.

In the example provided, the map contains pairs of names and ages. Each pair is created using the ‘to’ keyword, where the name is associated with its corresponding age. The map’s content is enclosed in curly brackets which look like {}.

By utilizing these functions, you can easily create and initialize maps in Kotlin according to your specific needs.

Retrieving map values

To access values in a Map, you use the associated key. For example, to get the value of “Anupam” in ‘immutable map’, you can do the:val myImmuMap = mapOf<Int,String>(1 to "Anupam", 2 to "Singh", 3 to "Developer") val valueOfAnupam = myImmuMap["Anupam"] // valueOfAnupam will be 1

Modify a map entry

You can also modify the values in a mutable Map, using keys:val myImmuMap = mapOf<Int,String>(1 to "Anupam", 2 to "Singh", 3 to "Developer") myImmuMap["Anupam"] = 5 // Update Anupam value from 1 to 5

Iterating over map entries via the map keys

You can use a for loop to iterate over a map. In this case we are iterating the map using the keys property, which contains all the keys present in the Map:val myImmuMap = mapOf<Int,String>(1 to "Anupam", 2 to "Singh", 3 to "Developer") for(key in myImmuMap.keys){ println(myImmuMap[key]) } // Output: // Anupam // Singh // Developer

Iterating over map values

We can also use a for loop to iterate over a map’s values, ignoring the map keys:val myImmuMap = mapOf<Int,String>(1 to "Anupam", 2 to "Singh", 3 to "Developer") for(value in myImmuMap.values){ println(value) } // Output: // Anupam // Singh // Developer

Other map functions and operations

Kotlin provides several useful functions and operations for working with maps. Some common ones include:

keys : This method retrieves a set, comprising all the keys present in the map.

values : The values function ensures retrieval of a collection, containing all the values stored in the map.

containsKey(key) : Determines whether a key exists in the map.

containsValue(value) : Checks whether a value exists in the map.

We have seen keys and values in the previous examples. Now let’s see the other methods in action.

Checking the existence of keys or values in the map

As we have mentioned, you can use the containsKey(key) function to check whether a specific key exists in the map, or the containsValue(value) function to determine whether a particular value is present in the map.val myImmuMap = mapOf<Int,String>(1 to "Anupam", 2 to "Singh", 3 to "Developer") // example of ***containsKey(key)*** println(myImmuMap.containsKey(2)) // exists so will print true println(myImmuMap.containsKey(4)) // not exists so will print false // Output: // true // false // example of ***containsValue(value)*** println(myImmuMap.***containsValue***("Ajay")) // not exists so print false println(myImmuMap.***containsValue***("Anupam")) // exists so print true // Output : // false // true

Working with Kotlin Set

Creating and manipulating sets in Kotlin

Creating a Kotlin Set is similar to other collections. You can use setOf() for an immutable set and mutableSetOf() for a mutable set. Here’s an example:// Immutable Set val intImmutableSet = setOf(1, 2, 3) for(element in intImmutableSet){ println(element) } // Output: // 1 // 2 // 3 // Mutable Set val intMutableSet = mutableSetOf(14, 24, 35) for(element in intMutableSet){ println(element) } // Output: // 14 // 24 // 35

Other useful Kotlin set operations and functions

Sets have unique characteristics that make them useful in certain scenarios. Common set operations include:

union() : Returns a new set that is the union of two sets.

intersect() : Returns a new set that is the intersection of two sets.

add(element) : A new element is added to enhance the set.

remove(element) : Removes an element from the set.

In the following example we show how to use the union() function:// Example of Union function val firstNum = setOf(1, 2, 3, 4,5) val secondNum = setOf(3, 4, 5,6,7,8,9) val finalUnionNums = firstNum.union(secondNum) println(finalUnionNums) // Output : // [1, 2, 3, 4, 5, 6, 7, 8, 9]

And here we have an example of intersect()// Example of Intersect function val fArray = arrayOf(1,2,3,4,5) val sArray = arrayOf(2,5,6,7) val iArray = fArray.intersect(sArray.toList()).toIntArray() println(Arrays.toString(iArray)) // Output: // [2, 5]

Iterating over Kotlin Set elements

Iterating through a set bears resemblance to iterating through a list. You can use a ‘for’ loop, or other iterable operations, to process each element.val intImmutableSet = setOf(1, 2, 3) for(element in intImmutableSet){ println(element) } // Output: // 1 // 2 // 3

Use cases and examples of sets in Kotlin

Sets are particularly useful when you need to maintain a collection of unique elements. For example:

Keep track of unique user IDs in a chat application.

Ensure that a shopping cart contains only distinct items.

Manage tags or categories without duplicates in a content management system.

Sets also simplify the process of checking for duplicates and ensuring data integrity.

FAQs

How do I filter strings from a Kotlin list?

To extract only strings, which can contain elements of any type, utilize the filterIsInstance() method. This method should be invoked on the kist, specifying the type T as String within the filterIsInstance() function.

The appropriate syntax for filtering only string elements within a list is:var myList: List<Any> = listOf(41, false, "Anupam", 0.4 ,"five", 8, 3) var filteredList = myList.filterIsInstance<String>() println("Original List : ${myList}") println("Filtered List : ${filteredList}") // Output : // Original List : [41, false, Anupam, 0.4, five, 8, 3] // Filtered List : [Anupam,five]

Executing filterIsInstance() will yield a list consisting solely of the String elements present within the original list, if any are found.

How do I define a list of lists in Kotlin?

The Kotlin list function listOf() is employed to generate an unchangeable list of elements. This function accepts multiple arguments and promptly furnishes a fresh list incorporating the provided arguments.val listOfLists = listOf( listOf(1, 2, 3), listOf("Anupam", "Singh", "Developer") ) print(listOfLists) Output: [[1, 2, 3], [Anupam, Singh, Developer]]

How do I filter only integers from a Kotlin list?

To extract only integers, which can contain elements of any type, you should utilize the filterIsInstance() method. This method should be invoked on the list, specifying the type T as Int within the filterIsInstance() function.

The appropriate syntax for filtering solely integer elements within a list is:var myList: List<Any> = listOf(5, false, "Anupam", 0.4 ,"five", 8, 3) var filteredList = myList.filterIsInstance<Int>() println("Original List : ${myList}") println("Filtered List : ${filteredList}") // Output : // Original List : [5, false, Anupam, 0.4, five, 8, 3] // Filtered List : [5, 8, 3]

Executing filterIsInstance() will yield a list consisting solely of the Int elements present within the original list, if any are found.

What are the different types of Kotlin Collections?

Kotlin’s official docs provide an overview of collection types in the Kotlin Standard Library, including sets, lists, and maps. For each collection type, there are two interfaces available: a read-only interface that allows accessing collection elements and provides some operations and then a mutable interface collections where you can modify the items. The most common collections are:

List

Set

Map (or dictionary)

How do I find out the length a Kotlin list?

To find out the length of a Kotlin list, you can use the size property. Here is an example:val myList = listOf(1, 2, 3, 4, 5) val length = myList.size println("The length of the list is $length")

Output:The length of the list is 5

What is List<*> in Kotlin?

In Kotlin, you can create a generic list with an unspecified type. When you use a generic list, you’re essentially saying, “I want a list of something, but I don’t care what type of things are in it”. This can be useful when you are writing generic code that can work with any type of list.fun printList(list: List<*>) { for (item in list) { println(item) } } val intList = listOf(1, 2, 3) val stringList = listOf("a", "b", "c") printList(intList) // This will print 1, 2, 3 printList(stringList) // This will print a, b, c

Can we use iterators to iterate a Koltin collection?

Yes, you can use iterators in Kotlin. In the previous examples we have seen how to iterate a Kotlin collection using for or forEach. In case you want to use iterators, here you can see an example of iterating a Kotlin list with an iterator.val myList = listOf("apple", "banana", "orange") val iterator = myList.iterator() while (iterator.hasNext()) { val value = iterator.next() println(value) }

In the example, we call iterator() on the list to get the iterator for the list. The while loop then uses hasNext() to check if there is another item in the list and next() to get the value of the current item.

#succession #full stack developer #full stack course

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computerguru-blogs · 2 years ago

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Array Vs Lists in Java (With Examples)

Define List In Java

In Java, A List is an ordered collection of an object in which values can be stored. It allows insertion, delete, update and positional access elements in list with index number. List created by the following classes(ArrayList, LinkedList , Stack, Vector).

The list method is found in java.util.List package. using this package we can iterate list in forward and backward directions. The implementation of classes of list are ArrayList, LinkedList, Stack, vector. The arrayList and linkedList are widly uesd in java. The vector class is deprecated scince java5

How to create a List in JAVA

Implementation of Array List:-

Syntax: List<String> lst1=New ArrayList<>();

Implementation of Linked List:-

Syntax: List<String> lst2=new LinkedList<>();

Different types of Methods of List in Java.

Some of List methods are commonly used in java are:

add() - It is used to add new Element in a list.

addAll()- It is used for add all elements of a list to a new list.

get() - It is used to access any element in a list.

set() - It is used for change element in a List. (More)

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courseforfree · 4 years ago

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Data Structures and Algorithms from Zero to Hero and Crack Top Companies 100+ Interview questions (Java Coding)

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Java Data Structures and Algorithms Masterclass

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Recursion

Big O

Dynamic Programming

Divide and Conquer Algorithms

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Section 1 – Introduction

What are Data Structures?

What is an algorithm?

Why are Data Structures And Algorithms important?

Types of Data Structures

Types of Algorithms

Section 2 – Recursion

What is Recursion?

Why do we need recursion?

How does Recursion work?

Recursive vs Iterative Solutions

When to use/avoid Recursion?

How to write Recursion in 3 steps?

How to find Fibonacci numbers using Recursion?

Section 3 – Cracking Recursion Interview Questions

Question 1 – Sum of Digits

Question 2 – Power

Question 3 – Greatest Common Divisor

Question 4 – Decimal To Binary

Section 4 – Bonus CHALLENGING Recursion Problems (Exercises)

power

factorial

products array

recursiveRange

fib

reverse

palindrome

some recursive

flatten

capitalize first

nestedEvenSum

capitalize words

stringifyNumbers

collects things

Section 5 – Big O Notation

Analogy and Time Complexity

Big O, Big Theta, and Big Omega

Time complexity examples

Space Complexity

Drop the Constants and the nondominant terms

Add vs Multiply

How to measure the codes using Big O?

How to find time complexity for Recursive calls?

How to measure Recursive Algorithms that make multiple calls?

Section 6 – Top 10 Big O Interview Questions (Amazon, Facebook, Apple, and Microsoft)

Product and Sum

Print Pairs

Print Unordered Pairs

Print Unordered Pairs 2 Arrays

Print Unordered Pairs 2 Arrays 100000 Units

Reverse

O(N) Equivalents

Factorial Complexity

Fibonacci Complexity

Powers of 2

Section 7 – Arrays

What is an Array?

Types of Array

Arrays in Memory

Create an Array

Insertion Operation

Traversal Operation

Accessing an element of Array

Searching for an element in Array

Deleting an element from Array

Time and Space complexity of One Dimensional Array

One Dimensional Array Practice

Create Two Dimensional Array

Insertion – Two Dimensional Array

Accessing an element of Two Dimensional Array

Traversal – Two Dimensional Array

Searching for an element in Two Dimensional Array

Deletion – Two Dimensional Array

Time and Space complexity of Two Dimensional Array

When to use/avoid array

Section 8 – Cracking Array Interview Questions (Amazon, Facebook, Apple, and Microsoft)

Question 1 – Missing Number

Question 2 – Pairs

Question 3 – Finding a number in an Array

Question 4 – Max product of two int

Question 5 – Is Unique

Question 6 – Permutation

Question 7 – Rotate Matrix

Section 9 – CHALLENGING Array Problems (Exercises)

Middle Function

2D Lists

Best Score

Missing Number

Duplicate Number

Pairs

Section 10 – Linked List

What is a Linked List?

Linked List vs Arrays

Types of Linked List

Linked List in the Memory

Creation of Singly Linked List

Insertion in Singly Linked List in Memory

Insertion in Singly Linked List Algorithm

Insertion Method in Singly Linked List

Traversal of Singly Linked List

Search for a value in Single Linked List

Deletion of a node from Singly Linked List

Deletion Method in Singly Linked List

Deletion of entire Singly Linked List

Time and Space Complexity of Singly Linked List

Section 11 – Circular Singly Linked List

Creation of Circular Singly Linked List

Insertion in Circular Singly Linked List

Insertion Algorithm in Circular Singly Linked List

Insertion method in Circular Singly Linked List

Traversal of Circular Singly Linked List

Searching a node in Circular Singly Linked List

Deletion of a node from Circular Singly Linked List

Deletion Algorithm in Circular Singly Linked List

A method in Circular Singly Linked List

Deletion of entire Circular Singly Linked List

Time and Space Complexity of Circular Singly Linked List

Section 12 – Doubly Linked List

Creation of Doubly Linked List

Insertion in Doubly Linked List

Insertion Algorithm in Doubly Linked List

Insertion Method in Doubly Linked List

Traversal of Doubly Linked List

Reverse Traversal of Doubly Linked List

Searching for a node in Doubly Linked List

Deletion of a node in Doubly Linked List

Deletion Algorithm in Doubly Linked List

Deletion Method in Doubly Linked List

Deletion of entire Doubly Linked List

Time and Space Complexity of Doubly Linked List

Section 13 – Circular Doubly Linked List

Creation of Circular Doubly Linked List

Insertion in Circular Doubly Linked List

Insertion Algorithm in Circular Doubly Linked List

Insertion Method in Circular Doubly Linked List

Traversal of Circular Doubly Linked List

Reverse Traversal of Circular Doubly Linked List

Search for a node in Circular Doubly Linked List

Delete a node from Circular Doubly Linked List

Deletion Algorithm in Circular Doubly Linked List

Deletion Method in Circular Doubly Linked List

Entire Circular Doubly Linked List

Time and Space Complexity of Circular Doubly Linked List

Time Complexity of Linked List vs Arrays

Section 14 – Cracking Linked List Interview Questions (Amazon, Facebook, Apple, and Microsoft)

Linked List Class

Question 1 – Remove Dups

Question 2 – Return Kth to Last

Question 3 – Partition

Question 4 – Sum Linked Lists

Question 5 – Intersection

Section 15 – Stack

What is a Stack?

What and Why of Stack?

Stack Operations

Stack using Array vs Linked List

Stack Operations using Array (Create, isEmpty, isFull)

Stack Operations using Array (Push, Pop, Peek, Delete)

Time and Space Complexity of Stack using Array

Stack Operations using Linked List

Stack methods – Push, Pop, Peek, Delete, and isEmpty using Linked List

Time and Space Complexity of Stack using Linked List

When to Use/Avoid Stack

Stack Quiz

Section 16 – Queue

What is a Queue?

Linear Queue Operations using Array

Create, isFull, isEmpty, and enQueue methods using Linear Queue Array

Dequeue, Peek and Delete Methods using Linear Queue Array

Time and Space Complexity of Linear Queue using Array

Why Circular Queue?

Circular Queue Operations using Array

Create, Enqueue, isFull and isEmpty Methods in Circular Queue using Array

Dequeue, Peek and Delete Methods in Circular Queue using Array

Time and Space Complexity of Circular Queue using Array

Queue Operations using Linked List

Create, Enqueue and isEmpty Methods in Queue using Linked List

Dequeue, Peek and Delete Methods in Queue using Linked List

Time and Space Complexity of Queue using Linked List

Array vs Linked List Implementation

When to Use/Avoid Queue?

Section 17 – Cracking Stack and Queue Interview Questions (Amazon, Facebook, Apple, Microsoft)

Question 1 – Three in One

Question 2 – Stack Minimum

Question 3 – Stack of Plates

Question 4 – Queue via Stacks

Question 5 – Animal Shelter

Section 18 – Tree / Binary Tree

What is a Tree?

Why Tree?

Tree Terminology

How to create a basic tree in Java?

Binary Tree

Types of Binary Tree

Binary Tree Representation

Create Binary Tree (Linked List)

PreOrder Traversal Binary Tree (Linked List)

InOrder Traversal Binary Tree (Linked List)

PostOrder Traversal Binary Tree (Linked List)

LevelOrder Traversal Binary Tree (Linked List)

Searching for a node in Binary Tree (Linked List)

Inserting a node in Binary Tree (Linked List)

Delete a node from Binary Tree (Linked List)

Delete entire Binary Tree (Linked List)

Create Binary Tree (Array)

Insert a value Binary Tree (Array)

Search for a node in Binary Tree (Array)

PreOrder Traversal Binary Tree (Array)

InOrder Traversal Binary Tree (Array)

PostOrder Traversal Binary Tree (Array)

Level Order Traversal Binary Tree (Array)

Delete a node from Binary Tree (Array)

Entire Binary Tree (Array)

Linked List vs Python List Binary Tree

Section 19 – Binary Search Tree

What is a Binary Search Tree? Why do we need it?

Create a Binary Search Tree

Insert a node to BST

Traverse BST

Search in BST

Delete a node from BST

Delete entire BST

Time and Space complexity of BST

Section 20 – AVL Tree

What is an AVL Tree?

Why AVL Tree?

Common Operations on AVL Trees

Insert a node in AVL (Left Left Condition)

Insert a node in AVL (Left-Right Condition)

Insert a node in AVL (Right Right Condition)

Insert a node in AVL (Right Left Condition)

Insert a node in AVL (all together)

Insert a node in AVL (method)

Delete a node from AVL (LL, LR, RR, RL)

Delete a node from AVL (all together)

Delete a node from AVL (method)

Delete entire AVL

Time and Space complexity of AVL Tree

Section 21 – Binary Heap

What is Binary Heap? Why do we need it?

Common operations (Creation, Peek, sizeofheap) on Binary Heap

Insert a node in Binary Heap

Extract a node from Binary Heap

Delete entire Binary Heap

Time and space complexity of Binary Heap

Section 22 – Trie

What is a Trie? Why do we need it?

Common Operations on Trie (Creation)

Insert a string in Trie

Search for a string in Trie

Delete a string from Trie

Practical use of Trie

Section 23 – Hashing

What is Hashing? Why do we need it?

Hashing Terminology

Hash Functions

Types of Collision Resolution Techniques

Hash Table is Full

Pros and Cons of Resolution Techniques

Practical Use of Hashing

Hashing vs Other Data structures

Section 24 – Sort Algorithms

What is Sorting?

Types of Sorting

Sorting Terminologies

Bubble Sort

Selection Sort

Insertion Sort

Bucket Sort

Merge Sort

Quick Sort

Heap Sort

Comparison of Sorting Algorithms

Section 25 – Searching Algorithms

Introduction to Searching Algorithms

Linear Search

Linear Search in Python

Binary Search

Binary Search in Python

Time Complexity of Binary Search

Section 26 – Graph Algorithms

What is a Graph? Why Graph?

Graph Terminology

Types of Graph

Graph Representation

The graph in Java using Adjacency Matrix

The graph in Java using Adjacency List

Section 27 – Graph Traversal

Breadth-First Search Algorithm (BFS)

Breadth-First Search Algorithm (BFS) in Java – Adjacency Matrix

Breadth-First Search Algorithm (BFS) in Java – Adjacency List

Time Complexity of Breadth-First Search (BFS) Algorithm

Depth First Search (DFS) Algorithm

Depth First Search (DFS) Algorithm in Java – Adjacency List

Depth First Search (DFS) Algorithm in Java – Adjacency Matrix

Time Complexity of Depth First Search (DFS) Algorithm

BFS Traversal vs DFS Traversal

Section 28 – Topological Sort

What is Topological Sort?

Topological Sort Algorithm

Topological Sort using Adjacency List

Topological Sort using Adjacency Matrix

Time and Space Complexity of Topological Sort

Section 29 – Single Source Shortest Path Problem

what is Single Source Shortest Path Problem?

Breadth-First Search (BFS) for Single Source Shortest Path Problem (SSSPP)

BFS for SSSPP in Java using Adjacency List

BFS for SSSPP in Java using Adjacency Matrix

Time and Space Complexity of BFS for SSSPP

Why does BFS not work with Weighted Graph?

Why does DFS not work for SSSP?

Section 30 – Dijkstra’s Algorithm

Dijkstra’s Algorithm for SSSPP

Dijkstra’s Algorithm in Java – 1

Dijkstra’s Algorithm in Java – 2

Dijkstra’s Algorithm with Negative Cycle

Section 31 – Bellman-Ford Algorithm

Bellman-Ford Algorithm

Bellman-Ford Algorithm with negative cycle

Why does Bellman-Ford run V-1 times?

Bellman-Ford in Python

BFS vs Dijkstra vs Bellman Ford

Section 32 – All Pairs Shortest Path Problem

All pairs shortest path problem

Dry run for All pair shortest path

Section 33 – Floyd Warshall

Floyd Warshall Algorithm

Why Floyd Warshall?

Floyd Warshall with negative cycle,

Floyd Warshall in Java,

BFS vs Dijkstra vs Bellman Ford vs Floyd Warshall,

Section 34 – Minimum Spanning Tree

Minimum Spanning Tree,

Disjoint Set,

Disjoint Set in Java,

Section 35 – Kruskal’s and Prim’s Algorithms

Kruskal Algorithm,

Kruskal Algorithm in Python,

Prim’s Algorithm,

Prim’s Algorithm in Python,

Prim’s vs Kruskal

Section 36 – Cracking Graph and Tree Interview Questions (Amazon, Facebook, Apple, Microsoft)

Section 37 – Greedy Algorithms

What is a Greedy Algorithm?

Well known Greedy Algorithms

Activity Selection Problem

Activity Selection Problem in Python

Coin Change Problem

Coin Change Problem in Python

Fractional Knapsack Problem

Fractional Knapsack Problem in Python

Section 38 – Divide and Conquer Algorithms

What is a Divide and Conquer Algorithm?

Common Divide and Conquer algorithms

How to solve the Fibonacci series using the Divide and Conquer approach?

Number Factor

Number Factor in Java

House Robber

House Robber Problem in Java

Convert one string to another

Convert One String to another in Java

Zero One Knapsack problem

Zero One Knapsack problem in Java

Longest Common Sequence Problem

Longest Common Subsequence in Java

Longest Palindromic Subsequence Problem

Longest Palindromic Subsequence in Java

Minimum cost to reach the Last cell problem

Minimum Cost to reach the Last Cell in 2D array using Java

Number of Ways to reach the Last Cell with given Cost

Number of Ways to reach the Last Cell with given Cost in Java

Section 39 – Dynamic Programming

What is Dynamic Programming? (Overlapping property)

Where does the name of DC come from?

Top-Down with Memoization

Bottom-Up with Tabulation

Top-Down vs Bottom Up

Is Merge Sort Dynamic Programming?

Number Factor Problem using Dynamic Programming

Number Factor: Top-Down and Bottom-Up

House Robber Problem using Dynamic Programming

House Robber: Top-Down and Bottom-Up

Convert one string to another using Dynamic Programming

Convert String using Bottom Up

Zero One Knapsack using Dynamic Programming

Zero One Knapsack – Top Down

Zero One Knapsack – Bottom Up

Section 40 – CHALLENGING Dynamic Programming Problems

Longest repeated Subsequence Length problem

Longest Common Subsequence Length problem

Longest Common Subsequence problem

Diff Utility

Shortest Common Subsequence problem

Length of Longest Palindromic Subsequence

Subset Sum Problem

Egg Dropping Puzzle

Maximum Length Chain of Pairs

Section 41 – A Recipe for Problem Solving

Introduction

Step 1 – Understand the problem

Step 2 – Examples

Step 3 – Break it Down

Step 4 – Solve or Simplify

Step 5 – Look Back and Refactor

Section 41 – Wild West

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generatour1 · 5 years ago

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annu29-blog1 · 6 years ago

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Basic Knowledge of websites

Introduction of Dynamic Website

Introduction to PHP

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XAMPP and WAMP Installation

Session 2:PHP programming Basi

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Embedding PHP in HTML

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Introduction to PHP variable

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Introduction to MySQL Database

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Adding Radio Buttons & List Menus

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Creating Unordered & Ordered and Definition Lists

Detailing Tags with Attributes

Using Heading Tags

Adding Bold & Italics

Understanding How a Browser Reads HTML

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Creating a link for Email Addresses

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Building & Applying Class Selectors

Creating Comments in Your Code

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Transparency and semi-transparency

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Creative typography

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Transparency and semi-transparency

CSS drop down navigation systems

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Divs and spans

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Arranging Layers Using the Z Index

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Floating elements

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Choosing Fonts and Font Size

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Applying Styles to Text

Setting Line Height

Letter Spacing (Kerning)

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Form based selectors

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Changing the appearance of buttons

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Adding Content to Posts & Pages

Using Categories

Using Tags

Managing User Comments

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Uploading Images

Basic and Advanced Image Formatting

Adding Video

Adding Audio

Managing the Media Library

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Project Discussion

Requirements analysis of Project

Project code Execution

Project Testing

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Cocoa and application architecture on Mac OS X

Session 4: Iphone development quick start

Overview of native application

Configuring application/running applications

Using iphone simulator/managing devices

Session 5: View and navigation controllers

Adding and implementing the view controller/Nib file

Configuring the view

Table views

Navigation and interface building

AlertViews

Session 6: Advanced Modules

SQLite

User input

Performance enhancement and debugging

Multi touch functions,touch events

Core Data

Map Integration

Social Network Integration (Facebook, Twitter , Mail)

Session 7: Submitting App to App Store

Creating and Downloading Certificates and Provisioning Profiles

Creating .ipa using certificates and provisioning profiles

Uploading App to AppStore

3>Android training:- The training programme and curriculum has designed in such a smart way that the student could familiar with industrial professionalism since the beginning of the training and till the completion of the curriculum.

Session 1: Android Smartphone Introduction

Session 2: ADLC(Android Development Lifecycle)

Session 3: Android Setup and Installation

Session 4: Basic Android Application

Session 5: Android Fundamentals

Android Definition

Android Architecture

Internal working of Android Applications on underlying OS

Session 6: Activity

Activity Lifecycle

Fragments

Loaders

Tasks and Back Stack

Session 7: Android Application Manifest File

Session 8: Intent Filters

Session 9: User Interface

View Hierarchy

Layout Managers

Buttons

Text Fields

Checkboxes

Radio Buttons

Toggle Buttons

Spinners

Pickers

Adapters

ListView

GridView

Gallery

Tabs

Dialogs

Notifications

WebView

Styles and Themes

Drag and Drop

Custom Components

Session 10: Android Design

Session 11: Handling Configuration

Session 12: Resource Types

Session 13: Android Animation

View Animation

Tween Animation

Frame animation

Property Animation

Session 14: Persistent data Storage

Shared Preference

Preference Screen

Sqlite Database

Session 15: Managing Long Running Processes

UI Thread

Handlers and Loopers

Causes of ANR issue and its solution

Session 16: Services

Service Lifecycle

Unbound Service

Bound Service

Session 17: Broadcast Receivers

Session 18: Content Providers

Session 19: Web Services

Http Networking

Json Parsing

Xml Parsing

Session 20: Google Maps

Session 21: Android Tools

Session 22: Publishing your App on Google market

4> java training:-We provide best java training in jodhpur, wscube tech one of the best result oriented java training company in jodhpur ,its offers best practically, experimental knowledge by 5+ year experience in real time project.we provide basic and advance level of java training with live project with 100%job placement assistance with top industries.

Session 1 : JAVA INTRODUCTION

WHAT IS JAVA

HISTORY OF JAVA

FEATURES OF JAVA

HELLO JAVA PROGRAM

PROGRAM INTERNAL

JDK

JRE AND JVM INTERNAL DETAILS OF JVM

VARIABLE AND DATA TYPE UNICODE SYSTEM

OPERATORS

JAVA PROGRAMS

Session 2 : JAVA OOPS CONCEPT

ADVANTAGE OF OOPS,OBJECT AND CLASS

METHOD OVERLOADING

CONSTRUCTOR

STATIC KEYWORD

THIS KEYWORD

INHERITANCE METHOD

OVERRIDING

COVARIANT RETURN TYPE

SUPER KEYWORD INSTANCE INITIALIZER BLOCK

FINAL KEYWORD

RUNTIME POLYMORPHISM

DYNAMIC BINDING

INSTANCE OF OPERATOR ABSTRACT CLASS

INTERFACE ABSTRACT VS INTERFACE PACKAGE ACCESS ODIFIERS

ENCAPSULATION

OBJECT CLASS

JAVA ARRAY

Session 3 : JAVA STRING

WHAT IS STRING

IMMUTABLE STRING

STRING COMPARISON

STRING CONCATENATION

SUBSTRING METHODS OF STRING CLASS

STRINGBUFFER CLASS

STRINGBUILDER CLASS

STRING VS STRINGBUFFER

STRINGBUFFER VS BUILDER

CREATING IMMUTABLE CLASS

TOSTRING METHOD STRINGTOKENIZER CLASS

Session 4 : EXCEPTION HANDLING

WHAT IS EXCEPTION

TRY AND CATCH BLOCK

MULTIPLE CATCH BLOCK

NESTED TRY

FINALLY BLOCK

THROW KEYWORD

EXCEPTION PROPAGATION

THROWS KEYWORD

THROW VS THROWS

FINAL VS FINALLY VS FINALIZE

EXCEPTION HANDLING WITH METHOD OVERRIDING

Session 5 : JAVA INNER CLASS

WHAT IS INNER CLASS

MEMBER INNER CLASS

ANONYMOUS INNER CLASS

LOCAL INNER CLASS

STATIC NESTED CLASS

NESTED INTERFACE

Session 6 : JAVA MULTITHREADING

WHAT IS MULTITHREADING

LIFE CYCLE OF A THREAD

CREATING THREAD

THREAD SCHEDULER

SLEEPING A THREAD

START A THREAD TWICE

CALLING RUN() METHOD JOINING A THREAD

NAMING A THREAD

THREAD PRIORITY

DAEMON THREAD

THREAD POOL

THREAD GROUP

SHUTDOWNHOOK PERFORMING MULTIPLE TASK

GARBAGE COLLECTION

RUNTIME CLASS

Session 7 : JAVA SYNCHRONIZATION

SYNCHRONIZATION IN JAVA

SYNCHRONIZED BLOCK

STATIC SYNCHRONIZATION

DEADLOCK IN JAVA

INTER-THREAD COMMUNICATION

INTERRUPTING THREAD

Session 8 : JAVA APPLET

APPLET BASICS

GRAPHICS IN APPLET

DISPLAYING IMAGE IN APPLET

ANIMATION IN APPLET

EVENT HANDLING IN APPLET

JAPPLET CLASS

PAINTING IN APPLET

DIGITAL CLOCK IN APPLET

ANALOG CLOCK IN APPLET

PARAMETER IN APPLET

APPLET COMMUNICATION

JAVA AWT BASICS

EVENT HANDLING

Session 9 : JAVA I/O

INPUT AND OUTPUT

FILE OUTPUT & INPUT

BYTEARRAYOUTPUTSTREAM

SEQUENCEINPUTSTREAM

BUFFERED OUTPUT & INPUT

FILEWRITER & FILEREADER

CHARARRAYWRITER

INPUT BY BUFFEREDREADER

INPUT BY CONSOLE

INPUT BY SCANNER

PRINTSTREAM CLASS

COMPRESS UNCOMPRESS FILE

PIPED INPUT & OUTPUT

Session 10 : JAVA SWING

BASICS OF SWING

JBUTTON CLASS

JRADIOBUTTON CLASS

JTEXTAREA CLASS

JCOMBOBOX CLASS

JTABLE CLASS

JCOLORCHOOSER CLASS

JPROGRESSBAR CLASS

JSLIDER CLASS

DIGITAL WATCH GRAPHICS IN SWING

DISPLAYING IMAGE

EDIT MENU FOR NOTEPAD

OPEN DIALOG BOX

JAVA LAYOUTMANAGER

Session 11 : JAVA JDBC and Online XML Data Parsing

Database Management System

Database Manipulations

Sqlite Database integration in Java Project

XML Parsing Online

Session 12 : Java Projects

NOTEPAD

PUZZLE GAME

PIC PUZZLE GAME

TIC TAC TOE GAME

Crystal App

Age Puzzle

BMI Calculator

KBC Game Tourist App

Meditation App

Contact App

Weather App

POI App

Currency Convertor

5>Python training:Wscube tech provides python training in jodhpur .we train the students from basic level to advanced concepts with a real-time environment.we are the best python training company in jodhpur.

Session 1 : Introduction

About Python

Installation Process

Python 2 vs Python 3

Basic program run

Compiler

IDLE User Interface

Other IDLE for Python

Session 2: Types and Operations

Python Object Types

Session 3 : Numeric Type

Numeric Basic Type

Numbers in action

Other Numeric Types

Session 4 : String Fundamentals

Unicode

String in Action

String Basic

String Methods

String Formatting Expressions

String Formatting Methods Calls

Session 5 : List and Dictionaries

List

Dictionaries

Session 6 : Tuples, Files, and Everything Else

Tuples

Files

Session 7 : Introduction Python Statements

Python’s Statements

Session 8 : Assignments, Expression, and Prints

Assignments Statements

Expression Statements

Print Operation

Session 9 : If Tests and Syntax Rules

If-statements

Python Syntax Revisited

Truth Values and Boolean Tests

The If/else ternary Expression

The if/else Ternary Expression

Session 10 : while and for loops

while Loops

break, continue, pass , and the Loop else

for Loops

Loop Coding Techniques

Session 11 : Function and Generators

Function Basic

Scopes

Arguments

Modules

Package

Session 12 : Classes and OOP

OOP: The Big Picture

Class Coding Basics

Session 13 : File Handling

Open file in python

Close file in python

Write file in python

Renaming and deleting file in python

Python file object method

Package

Session 14 : Function Basic

Why use Function?

Coding function

A First Example: Definitions and Calls

A Second Example : Intersecting Sequences

Session 15 :Linear List Manipulation

Understand data structures

Learn Searching Techniques in a list

Learn Sorting a list

Understand a stack and a queue

Perform Insertion and Deletion operations on stacks and queues

6>wordpress training:We will start with wordpress building blocks and installation and follow it with the theory of content management.we will then learn the major building blocks of the wordpress admin panel.the next unit will teach you about posts,pages and forums.and in last we done about themes which makes your site looks professional and give it the design you like.

Session 1: WordPress Hosting and installation options

CMS Introduction

Setting up Web Hosting

Introduction to PHP

Registering a Domain Name

Downloading and Installing WordPress on your Web Space

Session 2: WordPress Templates

Adding a pre-existing site template to WordPress

Creating and adding your own site template to WordPress

Note - this is an overview of templates - for in-depth coverage we offer an Advanced WordPress Course

Session 3: Configuring WordPress Setup Opt

When and How to Upgrade Wordpress

Managing User Roles and Permissions

Managing Spam with Akismet

Session 4: Adding WordPress Plugins

Downloading and Installing plugins

Activating Plugins

Guide to the most useful WordPress plugins

Session 5: Adding Content

Posts vs Pages

Adding Content to Posts & Pages

Using Categories

Using Tags

Managing User Comments

Session 6: Managing Media in WordPress

Uploading Images

Basic and Advanced Image Formatting

Adding Video

Adding Audio

Managing the Media Library

Session 7: Live Wordpress Project

Project Discussion

Requirements analysis of Project

Project code Execution

Project Testing

7>laravel training:Wscube tech jodhpur provide popular and most important MVC frameworks ,laravel using laravel training you can create web application with speed and easily.and before start training we done the basic introduction on framework.

Session 1 : Introduction

Overview of laravel

Download and Install laravel

Application Structure of laravel

Session 2 : Laravel Basics

Basic Routing in laravel

Basic Response in laravel

Understanding Views in laravel

Static Website in laravel

Session 3 : Laravel Functions

Defining A Layout

Extending A Layout

Components & Slots

Displaying Data

Session 4: Control Structures

If Statements

Loops

The Loop Variable

Comments

Session 5: Laravel Advanced Concepts

Intallation Packages

Routing

Middelware

Controllers

Forms Creating by laravel

Managing Sessions And Using Session Variables

Creating A Session And Registering Session Variables

Destroying A Session

Laravel - Working With Database

Session 6: SQL And Performing Queries

Inserting Records

Editing And Deleting Records

Retrieving Specific Columns

Filtering Records With A WHERE Clause

Sorting Records And Eliminating Duplicates

Limiting Results

Ajax

Sending Emails

Social Media Login

Session 7: Live Project

8>industrial automation engineer training :Automation is all about reducing human intervention .sometime it is employed to reduce human drudgery (e.g. crane,domestic,washing machine),sometime for better quality & production (e.g. CNC machine).some products can not be manufactured without automated machine (e.g. toothbrush,plastic,bucket,plastic pipe etc).

To replace a human being ,an automation system also needs to have a brain,hands,legs,muscles,eyes,nose.

Session 1:Introduction to Automaton

What is Automation

Components of Automation

Typical Structure of Automation

History & Need of Industrial Automation

Hardware & Software of Automation

Leading Manufacturers

Areas of Application

Role of Automation Engineer

Career & Scope in Industrial Automation

Session 2: PLC (Programmable Logic Controller)

Digital Electronics Basics

What is Control?

How does Information Flow

What is Logic?

Which Logic Control System and Why?

What is PLC (Programmable Logic Controller)

History of PLC

Types of PLC

Basic PLC Parts

Optional Interfaces

Architecture of PLC

Application and Advantage of PLCs

Introduction of PLC Networking (RS-232,485,422 & DH 485, Ethernet etc)

Sourcing and Sinking concept

Introduction of Various Field Devices

Wiring Different Field Devices to PLC

Programming Language of a PLC

PLC memory Organization

Data, Memory & Addressing

Data files in PLC Programming

PLC Scan Cycle

Description of a Logic Gates

Communication between PLC & PC

Monitoring Programs & Uploading, Downloading

Introduction of Instructions

Introduction to Ladder Programming

Session 3: Programming Of PLC (Ladder Logics)

How to use Gates, Relay Logic in ladder logic

Addressing of Inputs/Outputs & Memory bit

Math’s Instruction ADD, SUB, MUL, DIV etc.

Logical Gates AND, ANI, OR, ORI, EXOR, NOT etc.

MOV, SET, RST, CMP, INC, DEC, MVM, BSR, BSL etc.

How to Programming using Timer & Counter

SQC, SQO, SQL, etc.

Session 4:Advance Instruction in PLC

Jump and label instruction.

SBR and JSR instruction.

What is Forcing of I/O

Monitoring & Modifying Data table values

Programming on real time applications

How to troubleshoot & Fault detection in PLC

Interfacing many type sensors with PLC

Interfacing with RLC for switching

PLC & Excel communication

Session 5: SCADA

Introduction to SCADA Software

How to Create new SCADA Project

Industrial SCADA Designing

What is Tag & how to use

Dynamic Process Mimic

Real Time & Historical Trend

Various type of related properties

Summary & Historical Alarms

How to create Alarms & Event

Security and Recipe Management

How to use properties like Sizing, Blinking, Filling, Analog Entry, Movement of Objects, Visibility etc.

What is DDE Communication

Scripts like Window, Key, Condition & Application

Developing Various SCADA Applications

SCADA – Excel Communication

PLC – SCADA Communication

Session 6:Electrical and Panel Design

Concept of earthling, grounding & neutral

Study and use of Digital Multimeter

Concept of voltmeter & Ammeter connection

Definition of panel

Different Types of panel

Relay & contactor wiring

SMPS(Switch mode power supply)

Different type protection for panel

Application MCB/MCCB

Different Instruments used in panel (Pushbuttons, indicators, hooters etc)

Different type of symbols using in panel

Maintains & Troubleshooting of panel

Study of live distribution panel

Session 7: Industrial Instrumentation

Definition of Instrumentation.

Different Types of instruments

What is Sensors & Types

What is Transducers & Types

Transmitter & Receivers circuits

Analog I/O & Digital I/O

Different type sensors wiring with PLC

Industrial Application of Instrumentation

Flow Sensors & meters

Different type of Valves wiring

Proximate / IR Sensors

Inductive /Metal detector

Session 8: Study of Project Documentation

Review of Piping & Instrumentation Diagram (P&ID)

Preparation of I/O list

Preparation of Bill Of Material (BOM)

Design the Functional Design Specification (FDS)

Preparing Operational Manuals (O & M)

Preparing SAT form

Preparing Panel Layout, Panel wiring and Module wiring in AutoCAD.

9> digital marketing training: The digital marketing training course designed to help you master the essential disciplines in digital marketing ,including search engine optimization,social media,pay-per-click,conversion optimization,web analytics,content marketing,email and mobile marketing.

Session 1: Introduction To Digital Marketing

What Is Marketing?

How We Do Marketing?

What Is Digital Marketing?

Benefits Of Digital Marketing

Comparing Digital And Traditional Marketing

Defining Marketing Goals

Session 2: Search Engine Optimization (SEO)

Introduction To Search Engine

What Is SEO?

Keyword Analysis

On-Page Optimization

Off-Page Optimization

Search Engine Algorithms

SEO Reporting

Session 3: Search Engine Marketing (SEM

Introduction To Paid Ad

Display Advertising

Google Shopping Ads

Remarketing In AdWords

Session 4: Social Media Optimization (SMO)

Role Of Social Media In Digital Marketing

Which Social Media Platform To Use?

Social Media Platforms – Facebook, Twitter, LinkedIn, Instagram, YouTube And Google+

Audit Tools Of Social Media

Use Of Social Media Management Tools

Session 5: Social Media Marketing (SMM)

What Are Social Media Ads?

Difference Between Social Media And Search Engine Ads.

Displaying Ads- Facebook, Twitter, LinkedIn, Instagram & YouTube

Effective Ads To Lead Generation

Session 6: Web Analytics

What Is Analysis?

Pre-Analysis Report

Content Analysis

Site Audit Tools

Site Analysis Tools

Social Media Analysis Tool

Session 7: Email Marketing

What Is Email Marketing

Why EMail Marketing Is Necessary?G

How Email Works?

Popular Email Marketing Software

Email Marketing Goals

Best Ways To Target Audience And Generate Leads

Introduction To Mail Chimp

Email Marketing Strategy

Improving ROI With A/B Testing

Session 8: Online Reputation Management (ORM)

What Is ORM?

Why ORM Is Important?

Understanding ORM Scenario

Different Ways To Create Positive Brand Image Online

Understanding Tools For Monitoring Online Reputation

Step By Step Guide To Overcome Negative Online Reputation

Session 9: Lead Generation

What Is Lead Generation

Lead Generations Steps

Best Way To Generate Lead

How To Generate Leads From – LinkedIn, Facebook, Twitter, Direct Mail, Blogs, Videos, Infographics, Webinar, Strong Branding, Media

Tips To Convert Leads To Business

Measure And Optimize

Session 10: Lead Generation

What Is Affiliate Marketing

How Affiliate Marketing Works

How To Find Affiliate Niche

Different Ways To Do Affiliate Marketing

Top Affiliate Marketing Networks

Methods To Generate And Convert Leads

Session 11: Content Marketing

What Is Content Marketing?

Introduction To Content Marketing

Objective Of Content Marketing

Content Marketing Strategy

How To Write Great Compelling Content

Keyword Research For Content Ideas

Unique Ways To Write Magnetic Headlines

Tools To Help Content Creation

How To Market The Same Content On Different Platforms

Session 12: Mobile App Optimization

App store optimization (App name, App description, logo, screenshots)

Searched position of app

Reviews and downloads

Organic promotions of app

Paid Promotion

Session 13: Google AdSense

What is Google AdSense

How it Work?

AdSense Guidelines

AdSense setup

AdSense insights

Website ideas for online earning

10> robotics training:The lectures will guide you to write your very own software for robotics and test it on a free state of the art cross-platform robot simulator.the first few course cover the very core topics that will be beneficial for building your foundational skills before moving onto more advanced topics.End the journey on a high note with the final project and loss of confidence in skills you earned throughout the journey.

Session 1: Robotics Introduction

Introduction

Definition

History

Robotics Terminology

Laws of Robotics

Why is Robotics needed

Robot control loop

Robotics Technology

Types of Robots

Advantage & Disadvantage

ples of Robot

Session 2: Basic Electronics for Robotics

LED

Resistor

Ohm’s Law

Capacitor

Transistor

Bread board

DC Motor

DPDT switch

Rainbow Wire & Power Switch

Integrated Circuit

IC holder & Static Precaution

555 Timer & LM 385

L293D

LM 7805 & Soldering kit

Soldering kit Description

Soldering Tips

Soldering Steps

Projects

Session 3: Electronic Projects

a. Manual Robotic Car

Basic LED glow Circuit

LED glow using push button

Fading an LED using potentiometer

Darkness activation system using LDR

Light Activation system using LDR

Transistor as a NOT gate

Transistor as a touch switch

LED blinking using 555 timer

Designing IR sensor on Breadboard

Designing Motor Driver on Breadboard

Designing IR sensor on Zero PCB

Designing Motor Driver on Zero PCB

Line Follower Robot

Session 4: Sensors

Introduction to sensors

Infrared & PIR Senso

TSOP & LDR

Ultrasonic & Motion Sensors

Session 5: Arduino

a. What is Arduino

Different Arduino Boards

Arduino Shield

Introduction to Roboduino

Giving Power to your board

Arduino Software

Installing FTDI Drivers

Board & Port Selection

Port Identification – Windows

Your First Program

Steps to Remember

Session 6: Getting Practical

Robot Assembly

Connecting Wires & Motor cable

Battery Jack & USB cable

DC motor & Battery arrangement

Session 7: Programming

Basic Structure of program

Syntax for programming

Declaring Input & Output

Digital Read & Write

Sending High & Low Signals

Introducing Time Delay

Session 8: Arduino Projects

Introduction to basic shield

Multiple LED blinking

LED blinking using push button

Motor Control Using Push Button

Motor Control Using IR Sensor

Line Follower Robot

LED control using cell phone

Cell Phone Controlled Robot

Display text on LCD Display

Seven Segment Display

Session 8: Arduino Projects

Introduction to basic shield

Multiple LED blinking

LED blinking using push button

Motor Control Using Push Button

Motor Control Using IR Sensor

Line Follower Robot

LED control using cell phone

Cell Phone Controlled Robot

Display text on LCD Display

Seven Segment Display

11>SEO Training:SEO Search Engine Optimization helps search engines like google to find your site rank it better that million other sites uploaded on the web in answer to a query.with several permutation and combination related to the crawlers analyzing your site and ever changing terms and conditions of search engine in ranking a site,this program teaches you the tool and techniques to direct & increase the traffic of your website from search engines.

Session 1: Search engine Basics

Search Engines

Search Engines V/s Directories

Major Search Engines and Directories

How Search Engine Works

What is Search Engine Optimization

Page rank

Website Architecture

Website Designing Basics

Domain

Hosting

Session 2: Keyword Research and Analysis

Keyword Research

Competitor analysis

Finding appropriate Keywords

Target Segmentation

Session 3: On Page Optimization

Title

Description

Keywords

Anchor Texts

Header / Footer

Headings

Creating Robots File

Creating Sitemaps

Content Optimization

URL Renaming

HTML and CSS Validation

Canonical error Implementation

Keyword Density

Google Webmaster Tools

Google analytics and Tracking

Search Engine Submission

White Hat SEO

Black Hat SEO

Grey Hat SEO

Session 4: Off Page Optimization

Directory

Blogs

Bookmarking

Articles

Video Submissions

Press Releases

Classifieds

Forums

Link Building

DMOZ Listing

Google Maps

Favicons

QnA

Guest Postings

Session 5: Latest Seo Techniques & Tools

Uploading and website management

Seo Tools

Social media and Link Building

Panda Update

Penguin Update

EMD Update

Seo after panda , Penguin and EMD Update

Contact detail :-

a> WsCube Tech

First Floor, Laxmi Tower, Bhaskar Circle, Ratanada

Jodhpur - Rajasthan - India (342001)

b>Branch Office

303, WZ-10, Bal Udhyan Road,

Uttam Nagar, New-Delhi-59

c>Contact Details

Mobile : +91-92696-98122 , 85610-89567

E-mail : [email protected]

1 note · View note

huydx · 5 years ago

Text

Understand about how to implement (fast) queue (#1)

Background

(I tried to write this blog post in Vietnamese, but after write half of the blog, I realized that half of written text is in english (ﾉﾟ0ﾟ)ﾉ~ ..)

Recently I wanted to understand better about queue, and how to make a better "unbounded, thread safe queue". If you don't know about queue, you could understand queue as a main data structure to share "work load" or "task" (in another word, producer consumer problem).

My system is written mostly in go. As a go user, the very obvious way to implement unbounded, thread safe is to use go channel

Go channel will serve us very well in most cases and workload, it's not very fast. The problem of slow throughput is pretty obvious since go channel using many centralize lock object, which cause much contention to happen. There is one way to resolve the problem (we're using this method), is to batch the workload into bigger one, to reduce queue contention.

However, since we're still happy with batched workload and go channel, the problem here is very interesting, so I'm realize that thread safe, bounded queue implementation is indeed very interesting topic because it touches many interesting fields in computer science. So that is, that's why I tried to write this blog series.

Implement a queue, why it's hard?

Some simple googling how to implement high performance queue bring me to go github discussion of whether to add decent implementation of unbounded queue to std (container/queue) or not.

The discussion could be summarized into few ideas of why making a queue is hard?:

Variation of situation we would want to use the queue (MPMC, SPMC, MPSC, SPSC)

Variation of features we would the queue to support (push-front or not (dequeue vs queue)? lock-free or not? performance requirement?)

Since we don't want a slow queue, let's presume we want to make it as fast as possible. There are multiple ways to implement a queue:

Linked list

Flat slice or Ring buffer (both could be implemented using array)

Linked-list implementation bring some advantages:

Better lock contention (since the lock contention is only high on tail or head (not both)

Dynamic resizing (since add / remove node require alloc/dealloc a single node only)

However it come in disadvantages:

Memory usage (need 64 bit pointer memory for singly linked-list and 128 bit pointer for doubly linked list per node)

Memory fragment (since alloc happen in realtime, the memory of nodes will not be continuous obviously)

GC pressure (since we will have a lot of pointers to manage, more pointers, more pressure for GC language (java/go))

In opposite, array-backed implementation has totally opposite advantage / disadvantage

Bad: Harder lock method (since we may need to lock the whole array for each enqueue / dequeue ))

Bad: Resizing cost. Most decent resizing method is to double array every time we short of memory, but that will cause high memcopy cost (which is linear to element count).

Good: Contiguous array make a very well performance tradeoff utilizing CPU cache line characteristic. And using array reduce GC pressure a lot, since we only have to manage single pointer of array head.

Grasp some ideas from the giants

Find the optimized implementation that could minimize above disadvantages is hard. Let's see how de-facto implementations of few major languages are doing it. TL;DR most of standard libs don't fancy trick, they just try to do very decent implementation that is bug free and fast enough for most of the cases.

Java's LinkedBlockingQueue

In my daily job, the most queue implementation i've been using is java std LinkedBlockingQueue.

As explained in source code, the queue implementation based on a technique called "two lock queue" with LinkedList backed queue.

https://github.com/openjdk-mirror/jdk7u-jdk/blob/master/src/share/classes/java/util/concurrent/LinkedBlockingQueue.java#L83-L93

A variant of the "two lock queue" algorithm. The putLock gates entry to put (and offer), and has an associated condition for waiting puts. Similarly for the takeLock.

The comment explain it all, we use 2 lock to control the the queue. putlock used to control write (enqueue) path, and takeLock used to control read (dequeue) path. The origin paper is here: Simple, Fast, and Practical Non-Blocking and Blocking Concurrent Queue Algorithms .

public boolean offer(E e) { ..... putLock.lock(); try { if (count.get() < capacity) { enqueue(node); .... } } finally { putLock.unlock(); } } public E take() throws InterruptedException { takeLock.lockInterruptibly(); try { x = dequeue(); ... } finally { takeLock.unlock(); } return x; }

The good thing of queue (compare to stack) is that the concern for read and write is separated, we have 2 different object head and last to control read and write path, we could just easily separate lock for those.

Beside the two-lock technique, the implementation also has some fine-grain control method to reduce lock time. One of the method is to control number of remain items so when producer side call offer (or put), it could signal on-waiting take (or poll) right away. The idea is written in source code as below:

to minimize need for puts to get takeLock and vice-versa, cascading notifies are used. When a put notices that it has enabled at least one take, it signals taker. That taker in turn signals others if more items have been entered since the signal. And symmetrically for takes signalling puts.

private final Condition notEmpty = takeLock.newCondition(); public boolean offer(E e) { ..... if (c == 0) notEmpty.signal(); ..... } public E take() throws InterruptedException { ..... try { while (count.get() == 0) { notEmpty.await(); } x = dequeue(); .... } .... }

So that is, LinkedBlockingQueue idea is so simple. To use the queue as MPMC task queue, LinkedBlockingQueue is definitely better than other implementation like ArrayBlockingQueue, since ArrayBlockingQueue try to lock the whole queue for every single put or take.

LinkedBlockingQueue serves us very well for years, even for now. LinkedBlockingQueue is also very convenient in term of specification, since it block consumer or producer when the queue is empty or full, which reduce cost for us to implement to spin wait ourself. However the question still remain, do we have better idea or implementation, which will be talked at next part of this serie, so stay tune :).

1 note · View note

danielkvasnicka · 5 years ago

Text

Using Advent of Code 2019 to rediscover Common Lisp

UPDATE: Added generic-cl as suggested on Reddit.

Before last year’s Advent of Code started I declared on Twitter that I was going to do it in Common Lisp. And so I "did" (with a couple of 2016 challenges in CL as well). Yes, quite a bit of the challenges are missing. I hope to get back to them some time 😇

This writeup will be a summary of what I liked, what I did not like and finally a set of libraries for various purposes I used and found interesting. There are a couple of lists like that on the net (especially https://awesome-cl.com/, which I have actually submitted PRs to during my work on this article) but I wanted one that would include a couple of comments based on my personal experiences -- basically I’ll be making a purely subjective list of things I don’t want to forget about and it so happens that it will be publicly available on my blog 🤓

Just so you know, the views here will be expressed from the PoV of a long time Clojure and Racket fan.

Pros & Cons

Let’s start with what I liked:

Speed -- the best CL implementations are fast, while still allowing you to maintain a very readable, high level idiomatic code. With SBCL, the most popular implementation, you are basically getting one of the fastest lispy experiences possible. We obviously need to address the elephant in the room here and that’s Cloure. Clojure, thanks to JVM, can be faster than Common Lisp. However the speed often times comes at the cost of writing a relatively ugly “C wrapped in parens” style of code and/or you need enough data to get good amortization while JITting.

Debugging and optimization -- this one kind of relates to the first point as well. Common Lisp contains very powerful debugging, introspection and optimization tools that are part of the base lang spec. It does not matter what kind of implementation you use or whether you are using the IDE everyone thinks is the coolest right now... Hell, you can even disassmble your program to see the actual ASM code that your CPU will juggle.

Stability of the language -- there are people who can express this better so I’ll just link to the appropriate section of the magnificent article Steve Losh wrote in 2018:

My advice is this: as you learn Common Lisp and look for libraries, try to suppress the voice in the back of your head that says "This project was last updated six years ago? That's probably abandoned and broken." The stability of Common Lisp means that sometimes libraries can just be done, not abandoned, so don't dismiss them out of hand.

Specification & standard (kinda applies to Scheme as well) -- This is a tricky issue that has started many flamewars in the past, not just in the Lisp world (see the Spring vs Java EE battle). Having to adhere to a spec brings limitations but there are 2 counterarguments I can think of in the case of CL:

The power of macros means you can overcome almost all cases of stalled innovation without performance penalty. Look at the loop macro and how it was essentially completely covered with zero-cost abstractions.

The myriads of Clojure-like languages all suffer from the same problem: You cannot use libraries or any of the cool tools in the ecosystem. Yet, they themselves do not have anywhere near the traction necessary to be widely used production languages. CL shows that you can have a standard and still have enough room for differentiation and innovation.

Lisp-2 -- yep, you read that right. I would have never expected to say this (and I believe I’ve actually shunned Lisp-2 on this very blog some time ago?) but I actually like that functions in Common Lisp live in a separate namespace, for a very simple reason: code is read way more ofthen than it is written. When I look at code and see that seemingly annoying funcall I know it’s not just a top level defunned function and that I need to trace its origins somewhere else. Similar principle applies for the #' prefix (also makes life easier for syntax highlighters).

Next, the annoyances:

Widespread mutability and imperativeness -- Mutability is good if used in specific cases where it makes sense and if quarantined properly. However in CL mutability is king. It's not as much a problem of the language or implementations (you don't have to write mutable code) as it is a problem of the historical baggage -- it was never customary in the CL land to look bad at code that creates a mutable collection, then puts stuff in it in an imperative cycle and returns it from a function out to the dark and cold world... Purely functional collections exist but CL is not built around them. This is where Clojure shines.

CL Sequences apparatus not being user-extensible -- Common Lisp has a concept of sequences which puts a roof over lists and vectors and allows the user to use one function for both. However this facility, for some reason, is not easily extensible. This leads to many libraries implementing various new data structures and using completely custom API to do simple things like getting the size of a collection because (defmethod length ((seq my-epic-data-structure)) ...) signals COMMON-LISP:LENGTH already names an ordinary function or a macro. Fortunately there are libraries that are trying to solve this and to be honest it is not that much of a PITA anyway, because using a different function name for a special data structure has positive readability and performance implications. This applies to Racket too, to some degree. This lack of extensibility might have technical reasons I don't know of and if that is the case I'd be curious to learn and understand them.

LOOP -- I hate loop. Fortunately, this is an issue only if you have to deal with legacy code. The iteration story in CL is so good that you'll basically never have to write a single line of loop if you don't want to. My favourite comment on the topic is this one.

Destructuring not being 1st class citizen (enough) -- CL has macros with annoyingly long names to do destructuring and does not have the concept built-in deep enough for it to be ubiquitous in e.g. function definitions like you can see in JS or Clojure. Fortunately -- you guessed it -- libraries solve this issue satisfactorilly.

Interesting tools and libraries

What follows is a set of libraries that I tried and found useful -- libraries that helped me make a lot of annoyances (almost) irrelevant. I'll include one or two libraries that I have not used yet but would like to as they seem cool to me:

Platform tools

Quicklisp -- primary source of packages for CL. There is also Ultralisp, which is a faster-moving package distro.

Roswell -- this became my go-to tool for managing implementations and also packages. It can install packages from Quicklisp as well as GitHub repos in a manner similar to how go get works for example.

Qlot -- project-local dependencies manager that works well with Roswell. Think npm for Common Lisp. Can get dependencies from other Git repos, not just GitHub.

General purpose

Alexandria -- this is the utilities library in the CL world. It's so widespread that it's almost a standard thing.

Serapeum -- the Serapeum of Alexandria was an ancient Greek temple; referred to as the daughter of the Library of Alexandria. You get the idea ;) As you can see, the library is massive and I include it in most programs I write.

rutils (API) -- another impressive assortment of functions and macros. I would especially like to point out the with macro in the rutils.bind package, which is a kind of an extensible über-let.

metabang-bind -- another let on steroids. Unlike with it can bind arrays/vectors out of the box but is a little bit more chatty (and probably not as actively maintained).

cl-losh -- this is a library that its author explicitly does not want you to use. Sorry, Steve :) Your library is way too good for me to abide by your orders. What I found especially useful is the library of extensions for iterate, the de-facto replacement for LOOP we'll discuss later.

CL21 (and its very recent revival named 20XX) -- very interesting attempt at refreshing some of the more antiquated aspects of CL. It can be used as a library only to cherry-pick good stuff but it's probably less painfull to go all in and write programs "in" CL21 if it makes sense for a particular package.

cl-str -- Modern, simple and consistent Common Lisp string manipulation library.

Iteration & sequence procesing

iterate -- IMHO overall the best of iteration libraries for Common Lisp. A significantly lispier alternative to LOOP. Allows for very idiomatic, concise and understandable iteration code, is extensible and widely accepted and extended.

series -- the original transducers library (yes, those transducers). When used in tandem with taps (see my fork with a bugfix as well) it allows the programmer to write very succinct "top level" code (e.g. the main driver of a program that reads from a stream and delegates work to other parts of the code), or complex pipelines in general.

for -- another extensible LOOP replacement, this time a bit closer to Racket's ecosystem of for comprehensions.

gmap -- this is probably one of the most underrated/under-popularized pieces of gear I've come across in the Common Lisp land (tracing its origins back to 1980!). Combines mapping, filtering and reducing into a neat transducer-ish extensible construct and has a built-in support for FSet, a functional collections library we'll talk about later. The same Lisp project also contains new-let ...guess what is it supposed to be 😉 Yeah, let is the new loop.

generic-cl -- provides a generic function wrapper over various functions in the Common Lisp standard, such as equality predicates and sequence operations. An answer to on of my critical points above (defines generics that overlay CL builtins).

You can also find many small iteration helper tools scattered across the general purpose libraries we discussed in the previous section. Mapping from X to Y, reducing all kinds of things etc...

Math

cl-geometry -- 2D computational geometry library, which made work on Day 3 of AoC 2019 very enjoyable for me.

Data structures

FSet -- functional library of sets, maps and bags that has a natural and clean API and as we already mentioned, it comes with the added bonus of being written by the same guy who wrote gmap.

cl-containers -- a massive collection of (mostly tree-based) data structures and algorithms, useful when you need stuff like sorted map etc.

graph-utils -- graph data structure and algorithms

sycamore -- fast purely functional data structures

random-access-lists -- useful library for when you need a listy data structure and you don't want to pay O(n) when accessing elements in it.

array-operations -- library for concisely expressing operations on (multidimensional) arrays. Being used to the Racket array library it took me a while to get used to some of the specifics but it indeed is very powerful and fast.

Static typing & contracts

Apart from the built in tools for specifying types statically you can also use these to strenghten your safety net:

defstar -- Macros for easy inclusion of type declarations for arguments in lambda lists. Can replace defun, defmethod, defgeneric and others.

cl-algebraic-data-type -- a library for defining algebraic data types in a similar spirit to Haskell or Standard ML, as well as for operating on them

quid-pro-quo -- A contract programming library for Common Lisp in the style of Eiffel’s Design by Contract

Testing

These are the two testing libraries I tried out. I prefer parachute, the API feels more natural to me. There are others and it's getting worse 😉

rove

parachute

OOP

In addition to the following libraries you should check CLOS-related sections of almost all of the general purpose util libraries we discussed above. They contain stuff to help make CLOS a bit less verbose.

defclass-std -- a macro that atempts to give a very DRY and succint interface to the common DEFCLASS form. The goal is to offer most of the capabilities of a normal DEFCLASS, only in a more compact way.

sheeple -- prototype-based OOP in Common Lisp? 😱 Because we can!

Verdict

So is CL my new favorite language that I'll be using for everything from now on? No, not really. But in my book it's moving from a language that I wasn't really taking very seriously to a language that has a fixed place on my toolbelt. One scenario where I can see it shine is situations where I don't want (need?) to use Clojure but Racket / Scheme does not have the right libraries.

#commonlisp #lisp #adventofcode #programming #clojure #functional programming #adventofcode2019

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spideynow-blog · 6 years ago

Text

A Detailed Funnel Boss Review

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from Internet Marketing Aficionado https://internetmarketingaficionado.com/funnel-boss-review/

#Internet Marketing Aficionado

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vagueadulting-blog · 6 years ago

Text

A Detailed Funnel Boss Review

Every online marketer looks for the best strategies for generating traffic and boosting the sales of their business. However,

What is Funnel Boss?

Creator of Funnel Boss

What the core product is

Why Funnel Boss is a good product

Is The Funnel Boss Good?

As the product is divided into a series of segments, it becomes really easy to understand different aspects of the sales funnel.

The below-mentioned steps consist of a detailed summary of the Funnel Boss videos which will help you in understanding how the product is and how it will help you in making money faster online:

Video 1

The first video describes what a sales funnel is. This six minutes long video introduces to the specific concepts of Sales funnel, the working of customer flow and the ultimate goal of the funnel.

Video 2

Video 3

Video 4

Video 5

Video 6

Video 7

Video 8

My Bonuses For Buying The Product

from Internet Marketing Aficionado https://internetmarketingaficionado.com/funnel-boss-review/

#Internet Marketing Aficionado

0 notes

littlebeansplayhouse-blog · 6 years ago

Text

A Detailed Funnel Boss Review

Every online marketer looks for the best strategies for generating traffic and boosting the sales of their business. However,

What is Funnel Boss?

Creator of Funnel Boss

What the core product is

Why Funnel Boss is a good product

Is The Funnel Boss Good?

As the product is divided into a series of segments, it becomes really easy to understand different aspects of the sales funnel.

The below-mentioned steps consist of a detailed summary of the Funnel Boss videos which will help you in understanding how the product is and how it will help you in making money faster online:

Video 1

The first video describes what a sales funnel is. This six minutes long video introduces to the specific concepts of Sales funnel, the working of customer flow and the ultimate goal of the funnel.

Video 2

Video 3

Video 4

Video 5

Video 6

Video 7

Video 8

My Bonuses For Buying The Product

from Internet Marketing Aficionado https://internetmarketingaficionado.com/funnel-boss-review/

#Internet Marketing Aficionado

0 notes

lanisews-blog · 6 years ago

Text

A Detailed Funnel Boss Review

Every online marketer looks for the best strategies for generating traffic and boosting the sales of their business. However,

What is Funnel Boss?

Creator of Funnel Boss

What the core product is

Why Funnel Boss is a good product

Is The Funnel Boss Good?

As the product is divided into a series of segments, it becomes really easy to understand different aspects of the sales funnel.

The below-mentioned steps consist of a detailed summary of the Funnel Boss videos which will help you in understanding how the product is and how it will help you in making money faster online:

Video 1

The first video describes what a sales funnel is. This six minutes long video introduces to the specific concepts of Sales funnel, the working of customer flow and the ultimate goal of the funnel.

Video 2

Video 3

Video 4

Video 5

Video 6

Video 7

Video 8

My Bonuses For Buying The Product

from Internet Marketing Aficionado https://internetmarketingaficionado.com/funnel-boss-review/

#Internet Marketing Aficionado

0 notes

codebred · 6 years ago

Link

Many years ago, when programs were written mostly in C and C++, a programmer had to know quite a bit about how his code was affecting operations inside the machine. He had to know how much memory would be required to store a data structure, and then he’d have to request that memory from the operating system, and then free the memory later when he was done with it.

The programmer had to understand fundamental data structures and how the machine stored and accessed data in an array vs. a linked list vs. a hash table. He could only choose the right structure if he knew what kind of data the program would store and how and when the program would need to access it.

For a long time, there were no standard libraries for implementing and manipulating basic data structures, so programmers had to write them themselves. That, in turn, required programmers to understand and be able to implement basic algorithms for sorting, searching, etc.

The systems that developers had to work with decades ago had very little CPU and memory. You had to make the most of every resource, and if there was inefficiency anywhere, it showed up quickly. So you had to write code that was lean and efficient.

You may learn a programming language (or think that you have) but if you lack the ability to think logically, you won’t make it as a programmer.

By “programmer” I am covering all the various titles being tossed around.

If you write programs, you are a programmer. If you analyze systems and automate them, you are a programmer, etc.

A “software developer” is a programmer and there is no such thing as a “Software Engineer.”

Any title other than programmer is merely a name someone gives themselves to make them APPEAR to be better than they are and more important.

I disagree that there has been a decline in the quality of software developers. For that to be true, there would have to have been a time when the majority of software developers were highly skilled. My observation is that it has always been the case that a small percentage were of relatively higher skill than the norm. We see more people running around today than in years past; that’s all.

“In the early days, the only people who would be able to successfully program were those who were the very top of the scale in terms of innate ability.”

I don’t think that’s true. For one thing, the machines only supported a handful of operations, and they were just load/store, basic arithmetic, and shifts. The “programmers” were mathematicians and engineers. So the task of writing the “orders” (they didn’t have the word “software” then) wouldn’t have seemed very hard to them. Based on interviews and their memoirs, it seems they didn’t even regard it as a distinct type of work; it was just one of the things you did to build a device.

For another, the quality of “application” code was no better than today, on the whole. If you look at one of the major early projects, the Apollo Guidance Computer, the code was pretty hacked up at first. There was lots of duplication and tight coupling, and the system was plagued with integration errors. It was only after a NASA engineer (whose name escapes me at the moment) visited the team while they were still at MIT and introduced some engineering principles to them, and later when the work was at NASA and Margaret Hamilton joined the team., that the code was straightened out enough to work well. Even then, the code (that code in particular, and the concept of “software” generally, as well) had gained a reputation for unreliability, such that the inertial guidance system was used as the backup navigation system rather than the primary, as had been the original plan.

And the context of most programming in that era was different than today, too. Most of the few people involved with it were computer scientists, and they were engaged in developing operating systems, device drivers, compilers, and fundamental algorithms. Today, most software work is at the application level. It’s true that the high-end software engineers tend to produce cleaner and simpler designs than the average coder, but business applications come and go and they don’t actually have to be written to a high engineering standard in order to provide business value. The whole history of business applications proves that point. As long as we use programming languages that isolate the average coder from memory management (the most common stumbling block for average coders, and the reason COBOL, Java, and .NET in turn captured so much market share for business applications), the solutions they write will probably run more-or-less okay most of the time.

So, with all due respect, I think this is a non-issue. Grist for an article, maybe, but not a real problem.

The first computer I was able to put my hands on was a Tandy 1000 with 256KB RAM, a 5.25 inch floppy disk and DOS 2.51 (If I remember well).

To put a mouse in that machine was necessary to add a serial card. In that machine I was able to print complex things controlling the individual pins in an Epson matrix printer. My first achievement was to create my own music paper, and for that I made many attempts to have the right distance between the individual lines.

Later, I acquired, for my University studies, a wonderful Clone, with 512KB RAM, a Green monitor and a 3.5 inch floppy disk … oh, that was marvelous. Then I added to it a Genius mouse. To clarify, the mouse came in a nice box with a programming manual inside … in those days, that was “normal”, and the mouse was an investment because it was really expensive.

Then, I created my own text based user interface that, later, I improved to a graphical one … where the Borland Pascal 5.5 and Turbo C++ days.

You really needed to understand your machine to make it to sing because these machines were not really powerful. My Clone had a 8MHz TURBO mode that I improved replacing the Intel by a NEC V20 chip.

—

Let’s jump to today.

You just make software. You don’t worry about resources and, even with current monsters, you lack of memory and disk. And your user interface it is how you use what others designed for you, so you really don’t need to worry about.

How to deal with this?

I have been working with Raspberry and Arduino machines recently. My SBC machines are doing complex things, because they are extremely powerful, and with the Arduino I remembered my early days… if you are not careful enough your program will use so many resources that your Arduino will freeze.

For me, the answer is, to prepare the new bread of programmers.

Instead of providing more and more, and to facilitate things every day, the best solution is to put the programmers on a diet. Give them LESS and LESS and LESS, but ask them to do MORE and MORE … you will see how they improve their skills.

And, please, forget the easy food. Go to school, STUDY, try hard to understand complex math and physics and other basic sciences. The computer it is only a tool after all, you need to understand how to resolve real life problems.

Then, when the new programmers arrive to their new jobs, they will be flying on the all almighty machines they will receive to work with instead of painfully try to do whatever because they don’t know how to manage their resources.

#programming #work

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aksharasoftwares-blog · 7 years ago

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hoursofreading · 8 years ago

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Distributed Systems: CAP, P2P, Distributed Databases, Byzantine Generals, Consistent Hashing, Epidemic Algos, Paxos, Raft, Lamport Clocks

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Probabilistic Data Structures: Skip-List, HyperLogLog, Bloom Filter, Count-Min Sketch (These are useful for streaming data problems)

Languages: Python, R, SQL, Java, Scala

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isearchgoood · 5 years ago

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Create singly & doubly linked lists, stacks, & queues

Avoid memory leaks & other common problems

C is a general-purpose, imperative computer programming language that is ideal for developing firmware or portable applications. It is highly portable, making it a common choice for operating systems and microprocessors in hardware such as fridges and alarm clocks. C is a solid first language to learn since most programming languages are themselves today implemented in C. All of this is to say, this course is an excellent jumping off point for your programming odyssey.

Access 73 lectures & 8 hours of content 24/7

Master C programming concepts from the ground up

Use the source examples to learn step-by-step

Understand that special features of C: pointers, header files, null-terminated strings, buffers, IO

Read the supplied eBook, The Little Book of C, to explore the topics in even more depth

This video course is adapted from the instructor’s 15 years of teaching undergraduate engineering students in the classroom. Designed to cover an entire introduction to the C language, this course will help you build a sold foundation in C and boost your confidence to face technical interviews.

Access 124 lectures & 13.5 hours of content 24/7

Write C programs independently

Face technical interviews w/ confidence

Learn how to do assignments in C programs

Programming isn’t just about learning a language and starting to write programs like stories. One has to learn certain concepts that are fundamental to computer science in general. This course teaches fundamentals of data structures in a step-by-step manner. You’ll cover topics such as arrays, stacks and queues, linked lists, trees, and graphs in detail, alongside a variety of do-it-yourself coding exercises, building up your coding repertoire.

Access 66 lectures & 6 hours of content 24/7

Cover internal sorting, external sorting, symbol tables, & files

Complete meticulously planned coding exercises to strengthen your skills

This course will help you strengthen your fundamental understanding of C language. Using a real-world approach, it introduces several components of C programming that you may encounter in everyday programming challenges. This is the course to solidify your understanding of C, and give you that extra push you need to ace any important interview or test.

Access 47 lectures & 5 hours of content 24/7

Understand using C in real-world terms

Start developing a full-fledged C program

Cover many C programming concepts in a rigorous, but simple program

Reinforce concepts w/ included content questions

Consider C the programming equivalent of a French mother sauce. Just as chefs can create countless derivatives from a humble Bechamel, so too can developers easily master scores of languages upon learning C. This course will walk you through technical concepts such as loops, strings, and more, allowing you to conquer C and build a wide variety of apps and programs in no time at all.

Master C programming w/ 12 hours of content

Master language constructs: if/else & case statements, while & for loops, etc.

Familiarize yourself w/ functions, arrays & strings

Understand basic principles important to general programming

Craft a strong foundation for other languages: Objective-C, PHP & more

The C programming language is one of the earlier programming languages, and many other languages have their syntax based on C. Therefore, learning C can be an excellent introduction to programming as it makes learning many subsequent languages, like Java, PHP, or Swift, much easier. This introductory course will get you up to speed on C and enable you to dive into other languages more easily.

Access 13 lectures & 3 hours of content 24/7

Learn the foundations of C, from data types & operators to command line arguments & more

Understand functions & structures in C

Discover the stack vs. the heap & dynamic allocation

Write a program using C

Algorithms are a central tenet to programming, and are essential to ensure that software and programs perform the right operations under the right conditions. Companies depend on their systems algorithms to function correctly, which means they’ll pay top dollar for people who understand how to work with them. This course will help you to understand how to implement logic in code form to enable you to write algorithms efficiently in C.

Access 32 lectures & 3 hours of content 24/7

Learn the concepts behind the most popular algorithms used in computer science

Understand how algorithms work w/ the help of diagrams, examples & pseudocode

Practice algorithm implementation w/ the help of included programs in C language

Understand how to use algorithms to implement logic in any programming

Knowing the fundamentals of C programming is the first step to getting any C-heavy job. You may feel like you’ve got the language down, but it’s the most basic things that are the easiest to slip your mind when you sit down for an interview. This course irons out and tests your knowledge of all the core C programming fundamentals that you’ll need to know in order to ace an interview, so you don’t have to worry!

Access 22 lectures & 4 hours of content 24/7

Test & improve your knowledge on the intricacies of the C programming language

Reinforce your knowledge of variables & variable types & expressions

Build a better foundation w/ arrays, functions, pointers, structures & more

Iron out if conditions, switch statements, for loops, preprocessor directives & more

C, C++, Ruby, and Python are four of the most popular and powerful programming languages used today. You can find them in everything from web and mobile apps, games, operating systems, all of your favorite websites, and many hardware devices. This comprehensive course teaches you fundamentals in all 4, giving you a valuable programming background that you can confidently boast on your resume.

Access 307 lectures & 26 hours of content 24/7

Understand standard programs in C, C++, Python & Ruby programming

Explore the world of software languages

Write your own programs in C, C++, Python & Ruby

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