After Python for Beginners, AI advises the below COURSES, but to first become familiar with NumPy and Scikit-Learn LIBRARIES. My goal is creating production level AI Agents. (There are more courses after).
-Mathematics for Machine Learning and Data Science Specialization
-Machine Learning Specialization
-Deep Learning Specialization
MLS and DLS will cover that you need to know about Numpy, Scikit, and TensorFlow.
The MLS and DLS courses do not expect you to have studied any of those tools in detail before you enroll.
Math for Machine Learning doesn’t teach much that you will need in either MLS or DLS. It’s more math than machine learning. Since MLS is a beginner level course, it covers all the basics you will need.
Thanks for replying. I lack Linear Algebra, Calculus, Probability knowledge- AI told me the these are needed for MLS, DLS. Not the case, or ???
Also, even if MLS, DLS don’t need the “Math for ML, Data Science” prior- what math knowledge do the MLS, DLS give me? Enough to create quality production level agents?
Thanks!
Math skills that MLS expects:
MLS sets you up for attending the Deep Learning Specialization.
DLS is where you’ll be introduced to the tech that is used for creating language models - and a whole lot more, including generative methods.
If you just want to use existing agentic workflows, that’s a totally different topic.
What courses to attend depends on your goals.
Hey, that’s great. You have already taken the step for your goal, and your end goal is building production-level AI agents. Here are some steps you should follow that will be efficient for you.
Step 1. Python for Beginners (you have already covered the basics).
Step 2. Learn Core Libraries (NumPy, Pandas, Matplotlib, Scikit-Learn).
Step 3. Mathematics for Machine Learning and Data Science (linear algebra, calculus, probability and statistics, and Optimization basics).
Step 4. Machine Learning Specialization.
Step 5. Deep Learning Specialization.
Step 6. Build Production-Level AI Agents.
Hope this will help you.