#learn sql programming

[sectoralchromatics]

me because i'm unemployed and crazy: “here's a worksheet where you can see what the rally people do before they started their career fulltime !”

only get my hands on info of like 50 people and also the numbers are heavily skewed towards finns and frenchies. because .. duhh

charts breakdown part ! (this is just a part where i yap)

unsurprisingly many drivers had a career right in motorsports or some motorsports-related jobs like mechanics/engineers (started driving at a very young age, too). but also there's quite a portion of them studied law or practiced law previous to making a career out of racing. maybe driving 125km/h is the perfect way of destressing after memorising 300 lines of civil law 🙏

now about co-drivers. most of them studied engineering or even had really successful corporate jobs. like jonne halttunen is literally a ceo and he prolly has enough money to provide for kalle for the rest of his life lol. besides that we have the sportsplayers who switched over after some injury (enni included) or the military people - tina thörner was one of the first women to make it into the swedish air force and guy frequelin was a tank driving instructor ! so basically co-drivers be having the craziest sidejobs ever…

now since i have the most data for finland and france: voilà! comparison chart ! (co-drivers included)

apparently finns (and drivers in nordic countries) can have a professional rallying career at a very early age - usually they do this with external funding or working as a developer/driving instructor for car manufacturers. meanwhile most frenchies dabbled in a lot of jobs or struggled financially before they can have a full-time seat.

[crackaddict55]

🤩Are you a CS Student !?!???? 🥳🤩😎CHECK OUT THESE-

No. No I’m not. I study at home.

[codingquill]

SQL Fundamentals #1: SQL Data Definition

Last year in college , I had the opportunity to dive deep into SQL. The course was made even more exciting by an amazing instructor . Fast forward to today, and I regularly use SQL in my backend development work with PHP. Today, I felt the need to refresh my SQL knowledge a bit, and that's why I've put together three posts aimed at helping beginners grasp the fundamentals of SQL.

Understanding Relational Databases

Let's Begin with the Basics: What Is a Database?

Simply put, a database is like a digital warehouse where you store large amounts of data. When you work on projects that involve data, you need a place to keep that data organized and accessible, and that's where databases come into play.

Exploring Different Types of Databases

When it comes to databases, there are two primary types to consider: relational and non-relational.

Relational Databases: Structured Like Tables

Think of a relational database as a collection of neatly organized tables, somewhat like rows and columns in an Excel spreadsheet. Each table represents a specific type of information, and these tables are interconnected through shared attributes. It's similar to a well-organized library catalog where you can find books by author, title, or genre.

Key Points:

Tables with rows and columns.

Data is neatly structured, much like a library catalog.

You use a structured query language (SQL) to interact with it.

Ideal for handling structured data with complex relationships.

Non-Relational Databases: Flexibility in Containers

Now, imagine a non-relational database as a collection of flexible containers, more like bins or boxes. Each container holds data, but they don't have to adhere to a fixed format. It's like managing a diverse collection of items in various boxes without strict rules. This flexibility is incredibly useful when dealing with unstructured or rapidly changing data, like social media posts or sensor readings.

Key Points:

Data can be stored in diverse formats.

There's no rigid structure; adaptability is the name of the game.

Non-relational databases (often called NoSQL databases) are commonly used.

Ideal for handling unstructured or dynamic data.

Now, Let's Dive into SQL:

SQL is a :

Data Definition language ( what todays post is all about )

Data Manipulation language

Data Query language

Task: Building and Interacting with a Bookstore Database

Setting Up the Database

Our first step in creating a bookstore database is to establish it. You can achieve this with a straightforward SQL command:

CREATE DATABASE bookstoreDB;

SQL Data Definition

As the name suggests, this step is all about defining your tables. By the end of this phase, your database and the tables within it are created and ready for action.

1 - Introducing the 'Books' Table

A bookstore is all about its collection of books, so our 'bookstoreDB' needs a place to store them. We'll call this place the 'books' table. Here's how you create it:

CREATE TABLE books ( -- Don't worry, we'll fill this in soon! );

Now, each book has its own set of unique details, including titles, authors, genres, publication years, and prices. These details will become the columns in our 'books' table, ensuring that every book can be fully described.

Now that we have the plan, let's create our 'books' table with all these attributes:

CREATE TABLE books ( title VARCHAR(40), author VARCHAR(40), genre VARCHAR(40), publishedYear DATE, price INT(10) );

With this structure in place, our bookstore database is ready to house a world of books.

2 - Making Changes to the Table

Sometimes, you might need to modify a table you've created in your database. Whether it's correcting an error during table creation, renaming the table, or adding/removing columns, these changes are made using the 'ALTER TABLE' command.

For instance, if you want to rename your 'books' table:

ALTER TABLE books RENAME TO books_table;

If you want to add a new column:

ALTER TABLE books ADD COLUMN description VARCHAR(100);

Or, if you need to delete a column:

ALTER TABLE books DROP COLUMN title;

3 - Dropping the Table

Finally, if you ever want to remove a table you've created in your database, you can do so using the 'DROP TABLE' command:

DROP TABLE books;

To keep this post concise, our next post will delve into the second step, which involves data manipulation. Once our bookstore database is up and running with its tables, we'll explore how to modify and enrich it with new information and data. Stay tuned ...

Part2

[turtle-programming]

My certificate from SoloLearn ...

Topics: Data Programming with SQL & Python

Post #59: SoloLearn, Data Programming, SQL and Python Tutorial, 2025.

[education43]

What Are the Qualifications for a Data Scientist?

In today's data-driven world, the role of a data scientist has become one of the most coveted career paths. With businesses relying on data for decision-making, understanding customer behavior, and improving products, the demand for skilled professionals who can analyze, interpret, and extract value from data is at an all-time high. If you're wondering what qualifications are needed to become a successful data scientist, how DataCouncil can help you get there, and why a data science course in Pune is a great option, this blog has the answers.

The Key Qualifications for a Data Scientist

To succeed as a data scientist, a mix of technical skills, education, and hands-on experience is essential. Here are the core qualifications required:

1. Educational Background

A strong foundation in mathematics, statistics, or computer science is typically expected. Most data scientists hold at least a bachelor’s degree in one of these fields, with many pursuing higher education such as a master's or a Ph.D. A data science course in Pune with DataCouncil can bridge this gap, offering the academic and practical knowledge required for a strong start in the industry.

2. Proficiency in Programming Languages

Programming is at the heart of data science. You need to be comfortable with languages like Python, R, and SQL, which are widely used for data analysis, machine learning, and database management. A comprehensive data science course in Pune will teach these programming skills from scratch, ensuring you become proficient in coding for data science tasks.

3. Understanding of Machine Learning

Data scientists must have a solid grasp of machine learning techniques and algorithms such as regression, clustering, and decision trees. By enrolling in a DataCouncil course, you'll learn how to implement machine learning models to analyze data and make predictions, an essential qualification for landing a data science job.

4. Data Wrangling Skills

Raw data is often messy and unstructured, and a good data scientist needs to be adept at cleaning and processing data before it can be analyzed. DataCouncil's data science course in Pune includes practical training in tools like Pandas and Numpy for effective data wrangling, helping you develop a strong skill set in this critical area.

5. Statistical Knowledge

Statistical analysis forms the backbone of data science. Knowledge of probability, hypothesis testing, and statistical modeling allows data scientists to draw meaningful insights from data. A structured data science course in Pune offers the theoretical and practical aspects of statistics required to excel.

6. Communication and Data Visualization Skills

Being able to explain your findings in a clear and concise manner is crucial. Data scientists often need to communicate with non-technical stakeholders, making tools like Tableau, Power BI, and Matplotlib essential for creating insightful visualizations. DataCouncil’s data science course in Pune includes modules on data visualization, which can help you present data in a way that’s easy to understand.

7. Domain Knowledge

Apart from technical skills, understanding the industry you work in is a major asset. Whether it’s healthcare, finance, or e-commerce, knowing how data applies within your industry will set you apart from the competition. DataCouncil's data science course in Pune is designed to offer case studies from multiple industries, helping students gain domain-specific insights.

Why Choose DataCouncil for a Data Science Course in Pune?

If you're looking to build a successful career as a data scientist, enrolling in a data science course in Pune with DataCouncil can be your first step toward reaching your goals. Here’s why DataCouncil is the ideal choice:

Comprehensive Curriculum: The course covers everything from the basics of data science to advanced machine learning techniques.

Hands-On Projects: You'll work on real-world projects that mimic the challenges faced by data scientists in various industries.

Experienced Faculty: Learn from industry professionals who have years of experience in data science and analytics.

100% Placement Support: DataCouncil provides job assistance to help you land a data science job in Pune or anywhere else, making it a great investment in your future.

Flexible Learning Options: With both weekday and weekend batches, DataCouncil ensures that you can learn at your own pace without compromising your current commitments.

Conclusion

Becoming a data scientist requires a combination of technical expertise, analytical skills, and industry knowledge. By enrolling in a data science course in Pune with DataCouncil, you can gain all the qualifications you need to thrive in this exciting field. Whether you're a fresher looking to start your career or a professional wanting to upskill, this course will equip you with the knowledge, skills, and practical experience to succeed as a data scientist.

Explore DataCouncil’s offerings today and take the first step toward unlocking a rewarding career in data science! Looking for the best data science course in Pune? DataCouncil offers comprehensive data science classes in Pune, designed to equip you with the skills to excel in this booming field. Our data science course in Pune covers everything from data analysis to machine learning, with competitive data science course fees in Pune. We provide job-oriented programs, making us the best institute for data science in Pune with placement support. Explore online data science training in Pune and take your career to new heights!

[uthra-krish]

The Skills I Acquired on My Path to Becoming a Data Scientist

Data science has emerged as one of the most sought-after fields in recent years, and my journey into this exciting discipline has been nothing short of transformative. As someone with a deep curiosity for extracting insights from data, I was naturally drawn to the world of data science. In this blog post, I will share the skills I acquired on my path to becoming a data scientist, highlighting the importance of a diverse skill set in this field.

The Foundation — Mathematics and Statistics

At the core of data science lies a strong foundation in mathematics and statistics. Concepts such as probability, linear algebra, and statistical inference form the building blocks of data analysis and modeling. Understanding these principles is crucial for making informed decisions and drawing meaningful conclusions from data. Throughout my learning journey, I immersed myself in these mathematical concepts, applying them to real-world problems and honing my analytical skills.

Programming Proficiency

Proficiency in programming languages like Python or R is indispensable for a data scientist. These languages provide the tools and frameworks necessary for data manipulation, analysis, and modeling. I embarked on a journey to learn these languages, starting with the basics and gradually advancing to more complex concepts. Writing efficient and elegant code became second nature to me, enabling me to tackle large datasets and build sophisticated models.

Data Handling and Preprocessing

Working with real-world data is often messy and requires careful handling and preprocessing. This involves techniques such as data cleaning, transformation, and feature engineering. I gained valuable experience in navigating the intricacies of data preprocessing, learning how to deal with missing values, outliers, and inconsistent data formats. These skills allowed me to extract valuable insights from raw data and lay the groundwork for subsequent analysis.

Data Visualization and Communication

Data visualization plays a pivotal role in conveying insights to stakeholders and decision-makers. I realized the power of effective visualizations in telling compelling stories and making complex information accessible. I explored various tools and libraries, such as Matplotlib and Tableau, to create visually appealing and informative visualizations. Sharing these visualizations with others enhanced my ability to communicate data-driven insights effectively.

Machine Learning and Predictive Modeling

Machine learning is a cornerstone of data science, enabling us to build predictive models and make data-driven predictions. I delved into the realm of supervised and unsupervised learning, exploring algorithms such as linear regression, decision trees, and clustering techniques. Through hands-on projects, I gained practical experience in building models, fine-tuning their parameters, and evaluating their performance.

Database Management and SQL

Data science often involves working with large datasets stored in databases. Understanding database management and SQL (Structured Query Language) is essential for extracting valuable information from these repositories. I embarked on a journey to learn SQL, mastering the art of querying databases, joining tables, and aggregating data. These skills allowed me to harness the power of databases and efficiently retrieve the data required for analysis.

Domain Knowledge and Specialization

While technical skills are crucial, domain knowledge adds a unique dimension to data science projects. By specializing in specific industries or domains, data scientists can better understand the context and nuances of the problems they are solving. I explored various domains and acquired specialized knowledge, whether it be healthcare, finance, or marketing. This expertise complemented my technical skills, enabling me to provide insights that were not only data-driven but also tailored to the specific industry.

Soft Skills — Communication and Problem-Solving

In addition to technical skills, soft skills play a vital role in the success of a data scientist. Effective communication allows us to articulate complex ideas and findings to non-technical stakeholders, bridging the gap between data science and business. Problem-solving skills help us navigate challenges and find innovative solutions in a rapidly evolving field. Throughout my journey, I honed these skills, collaborating with teams, presenting findings, and adapting my approach to different audiences.

Continuous Learning and Adaptation

Data science is a field that is constantly evolving, with new tools, technologies, and trends emerging regularly. To stay at the forefront of this ever-changing landscape, continuous learning is essential. I dedicated myself to staying updated by following industry blogs, attending conferences, and participating in courses. This commitment to lifelong learning allowed me to adapt to new challenges, acquire new skills, and remain competitive in the field.

In conclusion, the journey to becoming a data scientist is an exciting and dynamic one, requiring a diverse set of skills. From mathematics and programming to data handling and communication, each skill plays a crucial role in unlocking the potential of data. Aspiring data scientists should embrace this multidimensional nature of the field and embark on their own learning journey. If you want to learn more about Data science, I highly recommend that you contact ACTE Technologies because they offer Data Science courses and job placement opportunities. Experienced teachers can help you learn better. You can find these services both online and offline. Take things step by step and consider enrolling in a course if you’re interested. By acquiring these skills and continuously adapting to new developments, they can make a meaningful impact in the world of data science.

[a-curious-studyblr]

11/7/24 - I've not got a computer sciences background (I'm a biologist!), but I've been learning the bare basics of SQL for a few days. I've applied to two data tech/analyst apprenticeships so I'm trying to get the basics and prep for interviews like this

[python-programming-language]

MIMO - My SQL Certificate ...

Post #94: MIMO, Learn To Code, My SQL Certificate, 2023.

[dcoder0604]

Day 0

Hello guys welcome to my blog. this blog is based on coding life

In this blog, I can share updates on daily codes and data-related work, What I do, and what I don't do on a daily basis

So it will be starting on the 1st of November because my exams are near

[small-basic-programming]

My 365 Days Streak at MIMO ...

"At Mimo, we believe that coding can open doors to opportunities like few other skills. That's why we've rallied around the purpose of making coding accessible to as many people as possible." MIMO

Today I completed my 365 day streak at Mimo. Phew, that was a long way through the programming and scripting languages “Python”, “SQL”, “HTML”, “CSS” and “JavaScript”.

Even though there were sometimes tough times and I often repeated certain course sections, e.g. with "JavaScript", and the progress wasn't immediately apparent, I still enjoyed learning with MIMO again and again.

The support is also good, if you have questions or just get stuck. I can recommend MIMO to anyone who wants to immerse themselves in the world of programming languages online or with the app.

Post #209: Whoopee! My 365 Day streak on Mimo happens today on March 3, 2024.

[onlineitsolutions01]

online certification programs Empower your journey with Online IT Solutions. Access top-notch, professional training courses online, and earn certifications for a brighter future. online professional courses ,online certification programs ,certification courses ,online training courses ,online learning platforms ,

[crackaddict55]

To do 9-24-23

I’ll study for 6 hours today 🧍

Mostly going to focus on interview practice and SQL.

[joneswebgoods]

Learn SQL Easy

If you're interested in learning SQL (Structured Query Language), the standard database access language, try learning from a place called SQL Easy. They provide a great self-learning environment where you can learn this language or troubleshoot how to code something.

I'm still learning SQL, even after using it for a few years. I came here looking for a code to pull records within a 7-day span and used this page here: https://www.sql-easy.com/learn/how-to-get-last-7-days-record-in-postgresql/

[turtle-programming]

My 1 Year Streak At MIMO ...

Seit einem Jahr lerne ich neben Small (Visual) Basic und Logo auch noch verschiedene andere Programmier- und Scriptsprachen mit MIMO.

In addition to Small (Visual) Basic and Logo, I have also been learning various other programming and scripting languages ​​with MIMO for a year.

Momentan befasse ich mich intensiv mit der Programmiersprache "JavaScript". Die fortgeschrittenen Programmiertechniken sind etwas anspruchsvoll wie z.B. die Array-Operationen.

At the moment I'm working intensively with the programming language "JavaScript". The advanced programming techniques are a bit demanding such as the array operations.

Post #22: Mimo, My 365 day streak at Mimo, 2024.