My path for learnning AI
Motivation behind this blog
Being motivated by something in life is really important. Professionally speaking, I chose computer science because I was always fascinated to understand how computers work. How does this small cursor move inside a screen? I pursued this fascination and ended up graduating as a software engineer in 2014.
Even when I was studying computer science, I was always fascinated by artificially intelligent machines and their implementations. This fascination only skyrocketed when I interacted with OpenAI's LLM back in 2019. It was such a weird but nostalgic moment for me to relive the same feelings I did when I used to think about the cursor inside the computer.
This fueled my passion for pursuing AI/ML further. The only 2 issues I have are, I am a practical person (engineering does this to you). I can only learn and take interest in learning something if it involves lots of practical knowledge alongside real-world examples. The second issue is something I dealt with in university as well. We used to learn stuff without any reference to why it's important or why we are learning them. This usually lead to us learning stuff that we forgot right after passing our exams. Also, it's really important for me to make a connection between my existing knowledge and whatever new I am learning. Otherwise, I can never learn something that sticks with me.
Given the context above, I started my search for learning material that will satisfy my requirements. I figured I should share these resources with you so in case you are like me, You can benefit from them as well. Since I am really selective, I usually take my time in finding good quality courses. Therefore, I'll keep this blog upto date. Meanwhile, if you have any suggestions for me, feel free to reach out to me at [email protected].
Courses
Maths Refresher (PAID)
Before you can get into the cool part, you need to solidify your base. Regardless of whether your background is in Maths or not, maths for machine learning and data science will help you prepare for the challenges ahead.
Intro to machine learning using PyTorch (PAID)
This nanodegree not only exposes you to existing libraries to build neural networks, but also shows you a lot of data-science techniques.
Maven course for fine-tuning LLMs (PAID)
This is a very interesting and in-depth course on fine-tuning LLMs.
Youtube Channels
In my opinion, the following Youtube channels provide a lot of very useful information around AI and base concepts in general.
Upcoming courses
These are highly anticipated and upcoming courses. I will definitely be going through them once they are ready.