Do not Miss Out! Enroll in FREE Programs Earlier than 2023 Ends – KDnuggets #Imaginations Hub

Do not Miss Out! Enroll in FREE Programs Earlier than 2023 Ends – KDnuggets #Imaginations Hub
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The final quarter of the 12 months is when individuals come alive. You’ve gotten your ultimate push to attain your yearly targets with the intention to hit your 2024 targets. Whether or not it’s beginning a brand new profession within the tech trade or growing your present expertise, self-development is vital. 

The continual enchancment in expertise is inflicting there to be a rush to get into the trade. Folks from all walks of life need to become involved. The intention of the weblog is to offer you an inventory of fantastic FREE programs that you would be able to take that will help you get there. I’ll break it down into sections by matter to make it simpler so that you can navigate in the direction of your space of focus. 

These free programs are all obtainable on YouTube, making it really feel like you’re enrolled on an precise course. It’s troublesome to search out the appropriate 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 Studying, Dmitry Kobak, 2020/21

2. Stanford CS229: Machine Studying

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

3. Cornell Tech CS 5787: Utilized Machine Studying

Hyperlink: Utilized Machine Studying (Cornell Tech CS 5787, Fall 2020)

4. Making Buddies with Machine Studying

Hyperlink: Making Buddies with Machine Studying, Cassie Kozyrkov

5. Basis Fashions

Hyperlink: Basis Fashions

 

 

1. Statistical Machine Studying

Hyperlink: Statistical Machine Studying

 

 

Rookies:

 

1. MIT 6.S191: Introduction to Deep Studying

Hyperlink: Introduction to Deep Studying

2. CMU Introduction to Deep Studying

Hyperlink: Introduction to Deep Studying: 11785 Spring 2023 Lectures

3. MIT: Introduction to Deep Studying

Hyperlink: Introduction to Deep Studying

4. Neural Networks: Zero to Hero

Hyperlink: Neural Networks: Zero to Hero

5. Foundations of Deep RL

Hyperlink: Foundations of Deep RL

 

Intermediate:

 

1. Stanford CS230: Deep Studying

Hyperlink: Stanford CS230: Deep Studying, Autumn 2018

2. Stanford CS25 – Transformers United

Hyperlink: Transformers United

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

Hyperlink: Deep Studying for Artwork, Aesthetics, and Creativity

4. CS 285: Deep Reinforcement Studying

Hyperlink: Deep Reinforcement Studying

5. Stanford: Reinforcement Studying

Hyperlink: Reinforcement Studying

6. Berkeley: Deep Unsupervised Studying

Hyperlink: Deep Unsupervised Studying, Spring 2020

7. NYU Deep Studying

Hyperlink: Deep Studying SP21

8. Full Stack Deep Studying

Hyperlink: Full Stack Deep Studying 2021

9. Deep Studying for Pc Imaginative and prescient

Hyperlink: Deep Studying for Pc Imaginative and prescient

 

 

1. Hugging Face Course: NLP

Hyperlink: NLP: Hugging Face Course

2. Stanford CS224U: Pure Language Understanding

Hyperlink: Pure Language Understanding

3. CMU Superior NLP

Hyperlink: Superior NLP, 2022

4. CMU Multilingual NLP

Hyperlink: Multilingual NLP

5. UMass CS685: Superior Pure Language Processing

Hyperlink: Superior Pure Language Processing

 

 

1. Sensible Deep Studying for Coders

Hyperlink: Sensible Deep Studying for Coders

2. Machine Studying Engineering for Manufacturing (MLOps) 

Hyperlink: Machine Studying Engineering for Manufacturing

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 specific lecturer’s voice you like over one other or the best way a lecturer presents. There are such a lot of belongings you think about. 

I’ve supplied an in depth checklist in every part that will help you select which one you like and might proceed your studying with. 

Hope this checklist has helped you. And if you understand of any good assets, please drop them within the feedback to share with the educational group – thanks!

Joyful Studying!
 
 
Nisha Arya is a Knowledge Scientist, Freelance Technical Author and Group Supervisor at KDnuggets. She is especially all in favour of offering Knowledge Science profession recommendation or tutorials and principle primarily based data round Knowledge Science. She additionally needs to discover the other ways Synthetic Intelligence is/can profit the longevity of human life. A eager learner, in search of to broaden her tech data and writing expertise, while serving to information others.
 


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