🔥 MIT has updated its famous course 6.S191: Introduction to Deep Learning.

The program covers topics of #NLP, #CV, #LLM and the use of technology in medicine, offering a full cycle of training - from theory to practical classes using current versions of libraries.

The course is designed even for beginners: if you know how to take derivatives and multiply matrices, everything else will be explained in the process.

The lectures are released for free on YouTube and the #MIT platform on Mondays, with the first one already available

.

All slides, #code and additional materials can be found at the link provided.

📌 Fresh lecture : https://youtu.be/alfdI7S6wCY?si=6682DD2LlFwmghew

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🏳️‍🌈 "NumPy Library" Tutorial

👨🏻‍💻 For the past few days, I've been busy preparing this comprehensive tutorial on the NumPy library for data science, trying to cover all the tips and tricks of this library.

✅ Why is this booklet different? Because it is not written based on just theoretical concepts, but is the result of my own experiences and learning. It has real and practical examples that will help you better understand #NumPy concepts and use them in your projects.💯

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https://t.me/CodeProgrammer ✅

Python #Pandas Cheat Sheet 🐼

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🔖 The book that paved the way for me to "data science"!

👨🏻‍💻 "Where do I start now?" This was the first and biggest question I faced when I started my Data Science learning journey!

⏪ I was really overwhelmed by the large number of scattered sources, long courses, and specialized books full of heavy terminology. I didn't know how to start and move forward in this direction...

✔️ But the book Intro to Data Science with Python changed everything for me and gave me a new perspective!

✏️ This book is a complete guide to starting from scratch and is great for both beginners and professionals in this field!! From coding with Python to working with data, visualization, and even AI tools, it explains everything in the simplest and most practical way possible.

💸 A great start for anyone looking to learn data science with Python!👇

┌ 🏳️‍🌈 Intro to Data Science with Python
├ 📄 E-book
└ 🐱 GitHub-Repos

#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming  #Keras

https://t.me/CodeProgrammer ✅

"Introduction to Python Programming"

This 415-pages #FREE book is perfect if you are starting your #Python journey.

Download book: https://t.co/aMLeAQre6r

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🔍 Free Data Analytics Courses by Microsoft

1. Get started with microsoft data analytics
https://learn.microsoft.com/en-us/training/paths/data-analytics-microsoft/

2.  Introduction to version control with git
https://learn.microsoft.com/en-us/training/paths/intro-to-vc-git/

3. Microsoft azure ai fundamentals
https://learn.microsoft.com/en-us/training/paths/get-started-with-artificial-intelligence-on-azure/

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https://t.me/CodeProgrammer ✅

😍 New to AI agents?

This free 10-part course on #GitHub will guide you from concept to #code as you start building #AI #agents:

⚡ Link: msft.it/6013qZ7Zb

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https://t.me/CodeProgrammer ✅

👨🏻‍💻 One of the most popular GitHub repositories for "learning and using algorithms in Python" is The Algorithms - Python repo with 196K stars.

✏️ It has a lot of organized and categorized code that you can use to find, read, and run different algorithms. Everything you can think of is here; from simple algorithms like sorting to advanced algorithms for machine learning, artificial intelligence, neural networks, and more.

✅ Why should we use it?

🔢 For learning: If you're looking to learn algorithms in action, this is great.

🔢 For practice: You can take the codes, run them, and modify them to better understand.

🔢 For projects : You can even use the codes here in real-life or academic projects.

🔢 For interviews: If you're preparing for data science interviews, this is full of practical algorithms.


┌ 🏳️‍🌈 The Algorithms - Python
└ 🐱 GitHub-Repos

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https://t.me/CodeProgrammer ✅

📄 "Pandas Introduction to Advanced" booklet

👨🏻‍💻 You can't attend a #datascience interview and not be asked about Pandas! But you don't have to memorize all its methods and functions! With this booklet, you'll learn everything you need.

✔️ One of the most useful and interesting combinations is using #Pandas with #AWS Lambda, which can be very useful in real projects.

#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming  #Keras

https://t.me/CodeProgrammer ✅

Find these FREE AI Courses here 👇

https://www.mltut.com/best-resources-to-learn-artificial-intelligence/

#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming  #Keras

https://t.me/CodeProgrammer ✅