#beginner project in python

[craftingtableus]

Home Automation Electronics Kit

Discover the fascinating world of smart home technology with this interactive learning kit, designed to spark curiosity in young minds. Combining the versatile ESP32 board with engaging story-based activities, this kit immerses children in the exciting world of home automation. Packed with a variety of sensor modules and programming tools, it allows young learners to build, experiment, and protect a smart home while honing essential STEM skills. Perfect for nurturing creativity and problem-solving abilities, this hands-on kit offers a fun and accessible introduction to the future of technology. Ready to dive in? Click the link to learn more and make your purchase!

[technology-123s-blog]

Start Your Machine Learning Projects Journey with Takeoff Projects

Machine learning is a growing field that has changed how businesses work and make decisions. At Takeoff Projects, we provide students and professionals with exciting opportunities to explore Machine Learning Projects that solve real-world problems. These projects are designed to help you learn by doing, making complex concepts easy to understand. Whether you are a beginner or an experienced coder, our projects are tailored to match your skill level.

One popular project involves building a spam email detector. This project teaches you how to use algorithms to classify emails as spam or not based on their content. You’ll work with datasets, clean the data, and train a machine learning model to improve its accuracy. Another favorite project is creating a movie recommendation system, like the ones used by streaming platforms. This project introduces collaborative filtering and how to personalize user experiences by predicting what they’ll like.

For students interested in finance, we offer projects like stock price prediction, which involves analysing historical data to forecast market trends. You’ll learn how to use Python libraries like Pandas and Scikit-learn to process data and build predictive models. Another exciting project is image recognition, where you train a model to identify objects or faces in pictures. This project gives you hands-on experience with neural networks and deep learning techniques.

At Takeoff Projects, we also focus on healthcare solutions, such as predicting diseases based on patient data or developing systems to monitor a patient’s health. These projects help you understand how machine learning can save lives and improve medical services.

[adityadigi]

Python Programming in Pitampura: Beginner to Advanced Training at DICS

[spreadsheetautomation]

How is Python Beneficial to The Pharmaceutical Industry?

Streamlining Research and Development

Python's role in the pharmaceutical industry is increasingly significant, especially in research and development (R&D) sectors. The language's simplicity and flexibility enable researchers to streamline complex biological data analysis, enhancing the efficiency of drug discovery processes. Python’s extensive libraries, such as Biopython, provide tools that are crucial for bioinformatics, allowing scientists to process genetic data, simulate biological processes and predict molecular behavior. These capabilities make Python an indispensable tool in the fast-paced environment of pharmaceutical R&D.

Enhancing Data Analysis and Machine Learning

Advanced-Data Handling

In the pharmaceutical industry, managing vast amounts of data efficiently is crucial. Python facilitates this through its powerful data-handling capabilities. Pharmaceuticals Python tools like Pandas and NumPy help manage and analyze large datasets, which are common in clinical trials and drug testing phases. These tools enable researchers to perform complex statistical analyses and data visualization, crucial for interpreting clinical data results and making data-driven decisions.

Leveraging Machine Learning

Machine learning is transforming how pharmaceutical companies approach drug design and patient treatment strategies. Python stands out with its rich ecosystem of machine learning libraries, such as TensorFlow and Scikit-learn. These pharmaceuticals Python tools allow companies to develop predictive models that can forecast drug interactions, treatment outcomes and patient responses. By incorporating machine learning techniques, pharmaceutical companies can significantly reduce the time and cost associated with bringing a new drug to market.

In conclusion, Python's versatility and its array of specialized libraries support critical operations across various phases of the pharmaceutical industry. From enhancing drug discovery and development to improving the accuracy of clinical trials and patient care strategies, Python's role as a powerful tool in this sector continues to grow, marking it as a cornerstone in the technological advancement of pharmaceuticals.

Read a similar article about Google spreadsheet automation here at this page.

[rupasriymts]

Unique Python Projects for engineering students

Welcome to the world of Python projects with Takeoff Edu Group! Here, we use Python, which is a popular language for making all kinds of cool stuff. Whether you're just starting to learn to code or you've been doing it for a while, Python is a great choice. You can use it to create websites, smart programs, and much more. In our collection of projects, you'll find lots of different ways to use Python to solve real problems. There are tons of tools and tricks in Python that you can explore to make your projects awesome. So, let's dive in together with Takeoff Edu Group and see all the amazing things we can do with Python!

Takeoff edu Group Titles of Python Projects

Latest:

Discovering Knee Osteoarthritis using CNN enhanced With Alex Net

Machine Learning Model For Prediction of Smartphone Addiction

Medical Insurance Premium Prediction with Machine Learning

Web Based Book Recommendation System using Collaborative Filtering

Trendy:

Glaucoma Detection Using Fundus Images Of The Eye

Detection of Phishing Attacks - A Machine Learning Approach

Classification of Google-Play-Store Apps using SVM and KNN Classifiers

Hand Written Digit Recognition using Machine Learning

Standard:

Image DC: Image Data Cleaning Framework Based on Deep Learning

Design And Implementation Of Brain Tumor Detection

Designing Disease Prediction Model Using ML Approach

Identity-Based Data Outsourcing Using Proxy Auditing In Clouds

End-to-End Speech Emotion Recognition with Gender Information.

Python projects can be broadly categorized under a wide range of uses that mirror the applicability and popularity of the language in various fields. From web development to data analysis and machine learning, automation, among other things, the Python ecosystem is a versatile platform for innovative problem-solving. Many web development projects currently make use of frameworks such as Django or Flask so that one can overcome scalability and security issues with ease. On the data science and analytics front, Python's vast ecosystem of libraries like NumPy, pandas and Matplotlib play quite a helpful role as they help in efficient data manipulation, exploration, and visualization Moreover, Python forms an essential component of automation projects as its ability to generate scripts and tools for automation of repetitive jobs and boosting efficiency stands out. Whatever is creating a dynamic website, using a big data set, building smart programs, or automating tasks, developers from all over the world prefer to use Python as a programming language for the reason that it offers unimaginable possibilities of innovation and impact.

The above Python Projects Titles are the example of Takeoff edu Group. Here Takeoff edu Group not only provide Python projects but also furnishes all kind of projects with proper guidance and support.

[machinelearningsite]

Python for Beginners: Organizing Virtual Space using Python

Picture this: a cluttered virtual space with random files scattered all over your PC. Now you can manually sort them out but programmers always want to get creative for doing simple stuff, don’t we? In today’s blog post, we’ll dive into a hands-on exercise that not only instills a sense of accomplishment but also enhances your confidence in Python. And the best part? This mini-project is lies…

[crescentmp3]

unrelatedly i need to become a computer scientist immediately i have to know everything

[izicodes]

hi!! do you have any free resources or textbooks for learning python? i’m doing my dissertation and i need a refresher before i start doing it properly. thanks!!

Hiya! 💗

Here you go:

Book

Python Objects and Classes

Roadmap.sh

Random Python Resources

Top 20 Python Projects for Beginners to Master the Language

Free Programming Books

Python Notes and Resources by @trialn1error

Python Official Roadmap

Python Project List

Python 3 Cheat Sheet

Python Cheatsheet for Beginners

These are the ones' I've shared on my blog over the years! Hope their helpful! 🥰👍🏾💗

[a-fox-studies]

hi! i'm shy as hell usually but trying to branch out cuz i saw u reblog that post abt asks. do u have any recs on where to start for a beginner coder (who has virtually no free time)? i feel like the landscape is so vast and overwhelming.

Hiii!! Thanks for the ask!

I think the best thing I've learned throughout my coding journey is that you must first pick a field that interests you. Computer Science is a VAST world, once you pick a field, you must really commit to it. For example, maybe data science interests you. You look up the requirements to be a date scientist. I don't have in-depth knowledge on it, but I do know that you need good knowledge about python and some of its modules like numpy, matplotlib etc. So you start learning the basics, and then move on to the modules. The key is to find what you love, then find what you need in order to pursue it.

For a kickstart I'd recommend w3schools — it's a really good site that has so many tutorials on various languages.

I was also a person that had no free time at all to focus on my learning. But then I realised that you must make time if you want to work on something with dedication. So now I devote Sunday afternoons to learning and working on my projects, and I try to stick to it as much as possible, except for when I have uni exams or any submissions lol

Hope this helped!!

[evelegy]

[Super Dwarf] Reticulated Pythons are NOT 'Beginner Reptiles'

I have had it with this stupid, reckless man. He is either proof that a phd doesn't make you intelligent, or he is willingly shilling for Reach Out Reptiles for lucrative gain and is morally bankrupt.

Let's establish some things upfront; the Reticulated Python is a species of snake native to a broad swathe of Southeast Asia, spanning from India to the Phillipines. They grow to be the longest snake in the world. Medusa, a snake owned by a Haunted House attraction LLC in Kansas City, was 25 feet long and weighed 350 pounds. This is a large and powerful animal capable of killing and even eating a person.

Now, reptile people often have pathologies that overlap with gun people, in that large or venomous animals under their control get them off. Any trip to a reptile show will confirm this (They even have their own NRA in the form of USARK). The impressive size of Reticulated Pythons, plus the wide variety of rare (thus high dollar value) color morphs, made them very popular in the pet trade in North America for a period of time.

How does one care for such a large animal? Well, if you look at known animal abuser, Jay Brewer's retic breeding facility, Prehistoric Pets, the answer is to keep them in small boxes. Hundreds of these snakes are bred each season so potentially one will come out with a ten thousand dollar or more color combo. What happens to the surplus animals? Where are they going? Well they either become food for cobra breeding projects, put in the freezer to die cold and dark, or are sold to the general public. These sales can occur with absolutely no oversight or background checks and are not self regulated by the reptile community and can occur at shockingly low prices. A child can walk into an Indiana reptile show and walk out with a baby specimen of the second largest snake in the world for less than sixty bucks. If this sounds horrifying, you'd be right!!!

When these animals don't die from improper care/neglect, or aren't just destroyed, they are released into the wild when they get too big and subsequently wreak havoc on the ecosystem. They can even injure or kill their owners in rare circumstances. For decades, an entire industry operated like this until two major factors would threaten the status quo.

The first is an ammendment to the Lacey Act, a piece of legislation that controls the importation of 'injurious' species to the US. This ammendment specificied that large constrictors, such as Reticulated Pythons or Anacondas, were barred from being transported across state lines. This virtually crippled a retic breeder's ability to make in person sales. In effect, the retic community created the circumstances for this law to exist by failing to properly hold people in their community accountable for their reckless and dangerous behavior. A retic breeder is not going to call foul on another retic breeder's behavior when they want to keep a business relationship with that individual. This is why inhuman monsters like Samson Pruitt (who deserves to be beaten to death in the streets) can operate in the space for so long with nary a peep from USARK. When Pruitt was exposed, so where all the people he did business with, including some of the big names in the reptile industry, like Reach Out Reptiles (who will become important later).

A second big impact on the Reticulated Python racket is millennials with social media accounts and disposable income; youtubers. The information age means that it is extremely easy to discover just how big the animal you want to get will be. There are dozens of blog posts, videos, and Instagram reels about just such a thing. A lot of this content flexes on how nice and elaborate the setups for their pet animals are, leading to viewers wanting to emulate that. The standards for reptile care are organically increasing because no one wants to get roasted on TikTok by having a substandard setup. How effectively can you privide a killer setup for a Reticulated Python? Not easily. Many millennials do not own houses or spaces large enough to accommodate a giant snake, and the cost of feeding and heating an animal like that is prohibitive in a way that wouldn't just be shameful. The emphasis now is trends towards smaller species of reptiles that are easier to max out the care for; wow people with the enclosure/setup rather than wow them with a large animal that is poorly taken care of.

So how does the industry react? Enter the [Super Dwarf Reticulated Python]. Garret Hartle, owner of the Reticulated Python breeding facility Reach Out Reptiles popularized the term in the past few years. These [conveniently perfect] snakes hail from island populations of Reticulated Pythons that don't grow as large because of the limited food in a smaller environment. A vendor trying to sell you a Super Dwarf Retic at a show might say they'll grow to 8 feet long, as opposed to 25 feet. That is definitely more manageable, but an eight foot snake is by no means a small animal. Their higher than normal intelligence makes them competent escape artists, and a strike from an eight foot snake *will* need stitches. A prospective owner might be prepared for that and do their research accordingly. For my first snake I chose a species that can theoretically get to six feet, and some people would consider that large. The key word there for our lesson today is 'theoretical'. Six feet is the extreme end of size for the animal I own, verifiable evidence shows that snakes of this species do not exceed six feet, and rarely even hit six feet.

The issue here is that the only information that seems to be available on these [Super Dwarf] Retics is information from the people *selling them*. They invented the terminology. What you won't find is a verifiable scientific study or dataset to suggest that a Super Dwarf Reticulated Python is substantially different from a Mainland Reticulated Python. Yes, predator populations on islands do trend smaller than their mainland counterparts because of lack of prey availability. Snakes reach breeding age at smaller sizes. Theoretically, spawn of those lines would stay smaller. *Theoretically*.

These snakes grow smaller because they have limited availability to food. In a captive environment the keeper *removes that limitation*. There is nothing on a genetic level preventing a Super Dwarf from growing to the same size as it's mainland counterpart if fed consistently... this means to maintain a small size you have to carefully curate a diet, which is not something a beginner keeper is likely to be proficient at. All that supports a Super Dwarf Retic staying small is just *a best guess*.

Reticulated Pythons can live for over thirty years. During that time they *never stop growing*. Some growing slowly, some fast, but regardless they never stop. Super Dwarf nomenclature has only been a thing gaining momentum in the past few years, despite Retics being a part of the hobby for decades and decades. All of this is spear-headed by Garret Hartle and his sales operation. If this sounds like a scam, *that's because it is*. Of course all of these snakes bred and sold within the last few years look small. His language always carefully hedges that the snakes are 'likely' to get to seven feet, or it's a 'reliable estimate', but he never gives a guarantee because he knows in 10 years all these buyers are going to be screwed. It's the same nonsense lies and obfuscation that you see surrounding teacup pigs.

Hartle is generally correct though, a Super Dwarf Retic that's only been bred to other Retics of the same two islands is likely to stay smaller. Uh-oh, here comes the Lacey Act with their importation laws!!! Now the only [Super Dwarf] Retics that breeders will ever have to work with are now all that's currently here in the US. How is this sustainable? You risk overly inbreeding the population and the viable offspring become way too cost prohibitive to gain a portion of the marketplace.

Enter crossbreeding. You take the Super Dwarf and breed it to a Mainland for a snake that technically has Super Dwarf genetics and so it's more likely to grow small, but less of a guarantee. They will sell these at lower prices, with whacky percentages listed like "37.5% SD". These confuse the medium information consumer to the point where they have to rely on the seller of the animal to be honest with them. Which they are not because they want that sale more than anything else.

Super Dwarf Reticulated Pythons became a hot topic because Hartle would send every YouTuber in the space one of his snakes for their collection and then have them specifically talk about on their programming about how Reach Out Reptiles is the only reliable source for 'true' Super Dwarf Retics that he sells at crazy prices. His business is advertised for in the above video from Clint. No other reptile breeder gets that same treatment across so many different channels. It's also probably no coincidence that both Clint and Hartle are weird religious nuts.

The point here is that a Super Dwarf Reticulated Python is a TERRIBLE suggestion for someone beginning to keep reptiles and Clint is being very disingenuous for recommending them to an impressionable audience.

The promises on max size are just wishful thinking.

Finding a 'true' island locality Reticulated Python is prohibitively expensive.

Vendors will lie and obfuscate the genetics and sources of their animals to make a sale, and not only to low information buyers.

There are much better and tamer snakes you can buy as a pet for the 6ft-8ft range that will not exceed those sizes and are easier to acquire. Go get a boa constrictor at your local animal shelter PLEASE FOR THE LOVE OF GOD.

[blubberquark]

Why Not Write Cryptography

I learned Python in high school in 2003. This was unusual at the time. We were part of a pilot project, testing new teaching materials. The official syllabus still expected us to use PASCAL. In order to satisfy the requirements, we had to learn PASCAL too, after Python. I don't know if PASCAL is still standard.

Some of the early Python programming lessons focused on cryptography. We didn't really learn anything about cryptography itself then, it was all just toy problems to demonstrate basic programming concepts like loops and recursion. Beginners can easily implement some old, outdated ciphers like Caesar, Vigenère, arbitrary 26-letter substitutions, transpositions, and so on.

The Vigenère cipher will be important. It goes like this: First, in order to work with letters, we assign numbers from 0 to 25 to the 26 letters of the alphabet, so A is 0, B is 1, C is 2 and so on. In the programs we wrote, we had to strip out all punctuation and spaces, write everything in uppercase and use the standard transliteration rules for Ä, Ö, Ü, and ß. That's just the encoding part. Now comes the encryption part. For every letter in the plain text, we add the next letter from the key, modulo 26, round robin style. The key is repeated after we get tot he end. Encrypting "HELLOWORLD" with the key "ABC" yields ["H"+"A", "E"+"B", "L"+"C", "L"+"A", "O"+"B", "W"+"C", "O"+"A", "R"+"B", "L"+"C", "D"+"A"], or "HFNLPYOLND". If this short example didn't click for you, you can look it up on Wikipedia and blame me for explaining it badly.

Then our teacher left in the middle of the school year, and a different one took over. He was unfamiliar with encryption algorithms. He took us through some of the exercises about breaking the Caesar cipher with statistics. Then he proclaimed, based on some back-of-the-envelope calculations, that a Vigenère cipher with a long enough key, with the length unknown to the attacker, is "basically uncrackable". You can't brute-force a 20-letter key, and there are no significant statistical patterns.

I told him this wasn't true. If you re-use a Vigenère key, it's like re-using a one time pad key. At the time I just had read the first chapters of Bruce Schneier's "Applied Cryptography", and some pop history books about cold war spy stuff. I knew about the problem with re-using a one-time pad. A one time pad is the same as if your Vigenère key is as long as the message, so there is no way to make any inferences from one letter of the encrypted message to another letter of the plain text. This is mathematically proven to be completely uncrackable, as long as you use the key only one time, hence the name. Re-use of one-time pads actually happened during the cold war. Spy agencies communicated through number stations and one-time pads, but at some point, the Soviets either killed some of their cryptographers in a purge, or they messed up their book-keeping, and they re-used some of their keys. The Americans could decrypt the messages.

Here is how: If you have message $A$ and message $B$, and you re-use the key $K$, then an attacker can take the encrypted messages $A+K$ and $B+K$, and subtract them. That creates $(A+K) - (B+K) = A - B + K - K = A - B$. If you re-use a one-time pad, the attacker can just filter the key out and calculate the difference between two plaintexts.

My teacher didn't know that. He had done a quick back-of-the-envelope calculation about the time it would take to brute-force a 20 letter key, and the likelihood of accidentally arriving at something that would resemble the distribution of letters in the German language. In his mind, a 20 letter key or longer was impossible to crack. At the time, I wouldn't have known how to calculate that probability.

When I challenged his assertion that it would be "uncrackable", he created two messages that were written in German, and pasted them into the program we had been using in class, with a randomly generated key of undisclosed length. He gave me the encrypted output.

Instead of brute-forcing keys, I decided to apply what I knew about re-using one time pads. I wrote a program that takes some of the most common German words, and added them to sections of $(A-B)$. If a word was equal to a section of $B$, then this would generate a section of $A$. Then I used a large spellchecking dictionary to see if the section of $A$ generated by guessing a section of $B$ contained any valid German words. If yes, it would print the guessed word in $B$, the section of $A$, and the corresponding section of the key. There was only a little bit of key material that was common to multiple results, but that was enough to establish how long they key was. From there, I modified my program so that I could interactively try to guess words and it would decrypt the rest of the text based on my guess. The messages were two articles from the local newspaper.

When I showed the decrypted messages to my teacher the next week, got annoyed, and accused me of cheating. Had I installed a keylogger on his machine? Had I rigged his encryption program to leak key material? Had I exploited the old Python random number generator that isn't really random enough for cryptography (but good enough for games and simulations)?

Then I explained my approach. My teacher insisted that this solution didn't count, because it relied on guessing words. It would never have worked on random numeric data. I was just lucky that the messages were written in a language I speak. I could have cheated by using a search engine to find the newspaper articles on the web.

Now the lesson you should take away from this is not that I am smart and teachers are sore losers.

Lesson one: Everybody can build an encryption scheme or security system that he himself can't defeat. That doesn't mean others can't defeat it. You can also create an secret alphabet to protect your teenage diary from your kid sister. It's not practical to use that as an encryption scheme for banking. Something that works for your diary will in all likelihood be inappropriate for online banking, never mind state secrets. You never know if a teenage diary won't be stolen by a determined thief who thinks it holds the secret to a Bitcoin wallet passphrase, or if someone is re-using his banking password in your online game.

Lesson two: When you build a security system, you often accidentally design around an "intended attack". If you build a lock to be especially pick-proof, a burglar can still kick in the door, or break a window. Or maybe a new variation of the old "slide a piece of paper under the door and push the key through" trick works. Non-security experts are especially susceptible to this. Experts in one domain are often blind to attacks/exploits that make use of a different domain. It's like the physicist who saw a magic show and thought it must be powerful magnets at work, when it was actually invisible ropes.

Lesson three: Sometimes a real world problem is a great toy problem, but the easy and didactic toy solution is a really bad real world solution. Encryption was a fun way to teach programming, not a good way to teach encryption. There are many problems like that, like 3D rendering, Chess AI, and neural networks, where the real-world solution is not just more sophisticated than the toy solution, but a completely different architecture with completely different data structures. My own interactive codebreaking program did not work like modern approaches works either.

Lesson four: Don't roll your own cryptography. Don't even implement a known encryption algorithm. Use a cryptography library. Chances are you are not Bruce Schneier or Dan J Bernstein. It's harder than you thought. Unless you are doing a toy programming project to teach programming, it's not a good idea. If you don't take this advice to heart, a teenager with something to prove, somebody much less knowledgeable but with more time on his hands, might cause you trouble.

[shivadmads]

Online Python Certification Training Course in India | NareshIT

Online Python Certification Training Course in India | NareshIT

In today’s tech-driven world, Python has emerged as one of the most popular and versatile programming languages. Its simplicity, robust libraries, and wide range of applications make it the first choice for both beginners and experienced developers. Whether you are an aspiring data scientist, a budding web developer, or a software engineer, learning Python can significantly boost your career prospects. For those looking to gain expertise in Python, NareshIT's Online Python Certification Training Course in India is the ideal platform.

Why Choose Python?

Python’s versatility lies in its applications across various domains. Some of the reasons Python has gained immense popularity are:

Ease of Learning: Python’s simple syntax makes it an excellent choice for beginners.

Wide Applications: From web development and data analysis to AI and machine learning, Python has diverse uses.

Community Support: A large and active community ensures plenty of resources and support for learners.

Demand in Job Market: Python is one of the most sought-after skills in the IT industry today.

About NareshIT’s Online Python Training

NareshIT is a renowned name in the field of software training. With years of experience and thousands of successful learners, it is the go-to institute for Python training in India. Here’s what makes NareshIT’s Python course stand out:

1. Comprehensive Curriculum

NareshIT’s Python Certification Training Course covers everything from basics to advanced concepts. The course includes:

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Object-oriented programming (OOP).

Advanced topics: Libraries like NumPy, Pandas, and Matplotlib.

Frameworks: Django and Flask for web development.

Data Science and Machine Learning basics.

2. Live Online Classes

NareshIT provides live, interactive online sessions conducted by experienced trainers. These sessions ensure personalized attention, allowing students to clear their doubts in real-time.

3. Hands-on Projects

The course emphasizes practical learning through hands-on projects. Students work on real-world scenarios, helping them understand the practical applications of Python.

4. Flexible Schedules

NareshIT understands the needs of working professionals and students. The flexible batch timings ensure that learners can pursue the course without disturbing their regular schedule.

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NareshIT’s Python Certification Training Course is designed for a wide audience:

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Why Opt for Online Training?

In the post-pandemic world, online learning has become the norm. NareshIT’s online training ensures that learners get the same quality education as in traditional classroom settings, with added benefits:

Learn from the comfort of your home.

Save time and money on travel.

Access recorded sessions for revision.

Interact with trainers and peers through virtual platforms.

Career Opportunities After Python Certification

Python opens doors to a plethora of career opportunities. After completing NareshIT’s Python Certification Training Course, learners can explore roles such as:

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Why NareshIT is the Best Choice?

NareshIT has established itself as a trusted name in software training. Some reasons why it is the best choice for learning Python are:

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Enroll Now and Start Your Python Journey

Python is the language of the future, and learning it from the right place can make all the difference. NareshIT’s Online Python Certification Training Course in India offers a perfect blend of theoretical knowledge and practical skills, ensuring that learners are job-ready upon completion.

Don’t wait! Enroll today and take the first step toward a successful career in Python programming.

Contact Us: For more details about the course, visit our website or contact NareshIT’s support team.

[frank-olivier]

The story of BASIC’s development began in 1963, when Kemeny and Kurtz, both mathematics professors at Dartmouth, recognized the need for a programming language that could be used by non-technical students. At the time, most programming languages were complex and required a strong background in mathematics and computer science. Kemeny and Kurtz wanted to create a language that would allow students from all disciplines to use computers, regardless of their technical expertise.

The development of BASIC was a collaborative effort between Kemeny, Kurtz, and a team of students, including Mary Kenneth Keller, John McGeachie, and others. The team worked tirelessly to design a language that was easy to learn and use, with a syntax that was simple and intuitive. They drew inspiration from existing programming languages, such as ALGOL and FORTRAN, but also introduced many innovative features that would become hallmarks of the BASIC language.

One of the key innovations of BASIC was its use of simple, English-like commands. Unlike other programming languages, which required users to learn complex syntax and notation, BASIC used commands such as “PRINT” and “INPUT” that were easy to understand and remember. This made it possible for non-technical users to write programs and interact with the computer, without needing to have a deep understanding of computer science.

BASIC was first implemented on the Dartmouth Time-Sharing System, a pioneering computer system that allowed multiple users to interact with the computer simultaneously. The Time-Sharing System was a major innovation in itself, as it allowed users to share the computer’s resources and work on their own projects independently. With BASIC, users could write programs, run simulations, and analyze data, all from the comfort of their own terminals.

The impact of BASIC was immediate and profound. The language quickly gained popularity, not just at Dartmouth, but also at other universities and institutions around the world. It became the language of choice for many introductory programming courses, and its simplicity and ease of use made it an ideal language for beginners. As the personal computer revolution took hold in the 1970s and 1980s, BASIC became the language of choice for many hobbyists and enthusiasts, who used it to write games, utilities, and other applications.

Today, BASIC remains a popular language, with many variants and implementations available. While it may not be as widely used as it once was, its influence can still be seen in many modern programming languages, including Visual Basic, Python, and JavaScript. The development of BASIC was a major milestone in the history of computer science, as it democratized computing and made it accessible to a wider range of people.

The Birth of BASIC (Dartmouth College, August 2014)

Friday, April 25, 2025

[angstics]

What's the difference to you between AI art being lacking because it's not from humans and AI code being okay? Very curious and confused by your posting last night/this morning.

I am so confused and annoyed by this. How is using ai to write code to highlight words in documents because i dont have the time to write code (my project isnt related to code at all!) in any way related to people’s disturbing misunderstanding of humanity’s role in art bc of genai? What, am i disregarding the human expression of beginner python coders????

The reason i talked about using it in the first place when i didnt need to is because i see people arent using their own discretion to make use of useful technology & i want to map out my values of what i think is right and wrong re ai. It isnt black and white.