Hi smart people!
I have been reading a lot of AI information in the last 7 days. After meditating on it, I am now a bit confused which way to go. Being a professional with more than 10 years experience in the IT industry, AI field is new to me but I don’t know where to begin. My goal is switch to AI field ASAP! I have the following questions:
1.) Should I jump in right away to specializations? if yes, which one: ML, GenAI, LLMs?
2.) Should I start in beginners phase or intermediate?
3.) Given the limited time and energy (I have a full time job as Software Engineer), what should my pacing be?
4.) I love to code, should I jump in right away to practical applications with having just a bit of fundamental knowledge on AI concepts. I also have to learn the industry’s coding language which i have zero skills.
In your situation, I recommend you attend a Python intro course. You’ll pick it up quickly. Note: Python code blocks depend entirely on indentation.
The first course should be the Machine Learning Specialization (MLS). It covers the basics.
Then the Deep Learning Specialization (DLS). It tackles more advanced methods and uses more sophisticated tools, like TensorFLow.
After that, it depends on where your interests lie. There are lots of courses on generative technologies, like Large Language Models (all the rage at present).
If you want to learn about some of the leading edge tech in chat bots, you could take some of the free Short Courses. They’re mostly technology snapshots from people who are making those tools. But you won’t understand how they work until after you’ve completed DLS.
Which certification adds value to my credentials? and should i take free courses/tutorials in learning Python or getting a certificate makes a “huge” difference?
If your goal is to build a law startup, you may find that there’s quite a bit you can do with off-the-shelf LLMs, using prompt engineering, RAG and Agents. These courses are short and will give you a sense of what’s possible. Some sections the instructor will be coding in python, and there’s a notebook for you to follow along, but if you know Java you’ll likely get the gist of what’s going on.
This is awesome. However, they all look Chinese to me It’s overwhelming to know and realize the amount of time and work I need to put into this new learning. But because I’m committed to doing this career switch, I hope I can learn them fast. I need to put my social life on hold in the next 6 months.
I’m the same. It’s really overwhelming and it takes a lot of effort. We definitely need to sacrifice some aspects of our life because there is not much time and there are tons of things to learn. But we’ll make it! I’m currently taking the Deep Learning Specialization and some of the short courses offered here by deeplearning.ai, those are really good. Also need to build your portfolio.
I would recommend to start with ML Specialization and since you are a Software Engineer you will pick Python very quickly so this won’t be an issue. The ML Specialization is a truly good one to walk you through the foundations of how ML models are build, tested and optimized and the intuition behind the algorithms being used. You will have a much better idea about what to focus on next when you are done with it.
To me personally, there is no point in learning Python for the sake of learning Python. It would be much more rewarding after you have some idea what you want to do with it. The ML Specialization is also the better course to take prior any GenAI courses.
Good luck!
Thanks for the practical advice @Jenys! I actually started ML specialization and I’m in the multiple linear regression section now. I kinda have a feeling that learning Python is really needed, not per se how to code it but what the libraries actually do. I do feel like the import statements are becoming now a memorization game.
It’s overwhelming to know and realize the amount of time and work I need to put into this new learning. But because I’m committed to doing this career switch, I hope I can learn them fast. I need to put my social life on hold in the next 6 months. 
