Don’t Miss Out! Enroll in FREE Programs Earlier than 2023 Ends

Don't Miss Out! Enroll in FREE Courses Before 2023 Ends
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The final quarter of the 12 months is when individuals come alive. You’ve gotten your remaining push to attain your yearly objectives with the intention to hit your 2024 objectives. Whether or not it’s beginning a brand new profession within the tech business or growing your present expertise, self-development is necessary. 

The continual enchancment in expertise is inflicting there to be a rush to get into the business. Individuals from all walks of life need to become involved. The intention of the weblog is to give you a listing of wonderful FREE programs you can take that can assist you get there. I’ll break it down into sections by subject to make it simpler so that you can navigate in the direction of your space of focus. 

These free programs are all out there on YouTube, making it really feel like you’re enrolled on an precise course. It’s troublesome to search out the best content material on YouTube as a result of there’s a lot of it! Hopefully, this text makes your search simpler, so let’s get into it.



1. Introduction to Machine Studying, 2020/21

Hyperlink: Introduction to Machine Learning, Dmitry Kobak, 2020/21

2. Stanford CS229: Machine Studying

Hyperlink: Stanford CS229: Machine Learning Full Course taught by Andrew Ng

3. Cornell Tech CS 5787: Utilized Machine Studying

Hyperlink: Applied Machine Learning (Cornell Tech CS 5787, Fall 2020)

4. Making Mates with Machine Studying

Hyperlink: Making Friends with Machine Learning, Cassie Kozyrkov

5. Basis Fashions

Hyperlink: Foundation Models



1. Statistical Machine Studying

Hyperlink: Statistical Machine Learning





1. MIT 6.S191: Introduction to Deep Studying

Hyperlink: Introduction to Deep Learning

2. CMU Introduction to Deep Studying

Hyperlink: Introduction to Deep Learning: 11785 Spring 2023 Lectures

3. MIT: Introduction to Deep Studying

Hyperlink: Introduction to Deep Learning

4. Neural Networks: Zero to Hero

Hyperlink: Neural Networks: Zero to Hero

5. Foundations of Deep RL

Hyperlink: Foundations of Deep RL




1. Stanford CS230: Deep Studying

Hyperlink: Stanford CS230: Deep Learning, Autumn 2018

2. Stanford CS25 – Transformers United

Hyperlink: Transformers United

3. MIT 6.S192: Deep Studying for Artwork, Aesthetics, and Creativity

Hyperlink: Deep Learning for Art, Aesthetics, and Creativity

4. CS 285: Deep Reinforcement Studying

Hyperlink: Deep Reinforcement Learning

5. Stanford: Reinforcement Studying

Hyperlink: Reinforcement Learning

6. Berkeley: Deep Unsupervised Studying

Hyperlink: Deep Unsupervised Learning, Spring 2020

7. NYU Deep Studying

Hyperlink: Deep Learning SP21

8. Full Stack Deep Studying

Hyperlink: Full Stack Deep Learning 2021

9. Deep Studying for Laptop Imaginative and prescient

Hyperlink: Deep Learning for Computer Vision



1. Hugging Face Course: NLP

Hyperlink: NLP: Hugging Face Course

2. Stanford CS224U: Pure Language Understanding

Hyperlink: Natural Language Understanding

3. CMU Superior NLP

Hyperlink: Advanced NLP, 2022

4. CMU Multilingual NLP

Hyperlink: Multilingual NLP

5. UMass CS685: Superior Pure Language Processing

Hyperlink: Advanced Natural Language Processing



1. Sensible Deep Studying for Coders

Hyperlink: Practical Deep Learning for Coders

2. Machine Studying Engineering for Manufacturing (MLOps) 

Hyperlink: Machine Learning Engineering for Production

And that’s it!



As I discussed earlier than, there are a variety of programs on the market and it may be troublesome to stay to 1. There could also be a selected lecturer’s voice you like over one other or the best way a lecturer presents. There are such a lot of stuff you think about. 

I’ve supplied an intensive record in every part that can assist you select which one you like and might proceed your studying with. 

Hope this record has helped you. And if you already know of any good sources, please drop them within the feedback to share with the training group – thanks!

Pleased Studying!
Nisha Arya is a Information Scientist, Freelance Technical Author and Group Supervisor at KDnuggets. She is especially excited by offering Information Science profession recommendation or tutorials and principle based mostly information round Information Science. She additionally needs to discover the other ways Synthetic Intelligence is/can profit the longevity of human life. A eager learner, searching for to broaden her tech information and writing expertise, while serving to information others.

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