If you're aspiring to become a Machine Learning (ML) engineer OR if you just wanna learn AI to integrate some feature in your app, it's crucial to build a strong foundation and engage with hands-on resources. Here, I've compiled a selection of courses and platforms that will guide you on your learning journey.
There is a fast way and there is a slow way. Lets discuss both one by one.
Fast way: This is for those who are already in the industry and want to use AI in their projects without diving deeper into it. They are not interested in switching careers to AI.
Slow way: This is for those who want to switch their careers to AI or start from the basics. I have divided this extensive slow way into two parts:
Focuses majorly on theory with less practical stuff.
Focuses majorly on hands-on stuff with brief theoretical information.
If you think you can learn the practical aspects and don't need the theory, believing you can learn it all by yourself later and that what's happening under the hood is not your concern, I think you're wrong. I made the same mistake while learning, so don't do that.
Roadmap for both
Core Learning Resources
Theory focused resources
DON'T WORRY ABOUT IT IF YOU DON'T UNDERSTAND - Andrew Ng
I said this because a lot of maths will not going to make sense to you sometimes when you start learning so don't worry just keep learning with a good pace and everything will make sense eventually.
Now, here's a brief overview about different resources:
This course here will clear a lot of confusions of yours about AI. Questions like what's possible with AI and what's not become easy for you and you'll also understand the business perspective of AI.
[Optipnal] If you're good at Linear Algebra, Calculus and Probability & Stats you can skip this one but even if you are you'll learn a lot from this that how AI is leveraging all these concepts. Still I recommend the Luis Serrano who is THE BEST teacher I've found for learning maths from AI perspective.
This one's most important. It contains 3 different courses all taught by Prof. Andrew himself. I highly recommend this as this specialization will set the best possible base for you journey to become ML engineer.
Note: Do checkout other courses byDeepLearning.AIwhich are from intermediate to advance level.
Hands-on development focused resources
Zero to mastery academy provides one of the most extensive possible content on any topic. You can either purchase it from udemy or their own website.
Here is the sequence in which you have to follow their courses:
If you are interested you can go for pytorch one as well. Just search the above titles on the websites I mentioned, download the courses and start learning.
Note: After grabbing some basic knowledge make sure you do short courses from DeepLearning.Ai which are totally 100% free.
By following this structured approach, you'll gain a solid grounding in AI and ML, coupled with practical skills that are crucial for a successful career in this field.
BEST OF LUCK FOR YOUR AI JOURNEY🤞