What tools should I learn?

AI Discussions
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Hey! I am a high school student interested in the field of Artificial Intelligence. I’ve looked up many roadmap guides an becoming an AI engineer. And I took a few python courses and data science courses from coursera.

My current knowledge consists of:

  1. Intermediate python knowledge: Generators, Decorators, Exception Handling, etc.
  2. Data Structures and Algorithms: Searching, Sorting, Graphs, Trees, DP
  3. Very basic version control knowledge ( I mainly know how to click random buttons on Github )
  4. Basic knowledge on mySQL: Joining, ER Diagrams, etc.
  5. Basic ( And I mean really basic ) Knowledge on python libraries: numpy, pandas, matplotlib, seaborn

I feel like most of the roadmap videos give me a path to follow, but I’m unsure on how much to learn a single topic until I can move on to the next one. Sometimes I wonder how much pandas do I learn till I can move on, do I read the entire documentation?

Any guidance would be appreciated!

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@chitcid In so far as libraries go (and for the moment restricting one’s self to Python), I would say Scikit-Learn, Matplotlib and Numpy would be the big three-- plus either Tensorflow and/or Pytorch depending on one’s preferences.

Personally I’ve been reading Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 3rd Edition by Aurélien Géron and quite liking it-- Though perhaps it doesn’t cover the math topics with the needed rigor, and an understanding/proficiency with Python is presumed.

As to Pandas, well in a way I think this is where knowing Scikit-Learn would really help. Working through and solving some problems with various methods will show you how much (and in what ways) you have to manipulate your data to get results, and thus ‘how much’ Pandas you need to know.

If you want to be a Data Engineer, it might be a different story.

Finally, since you are still in high school you can just work it into your regular curriculum, but definitely pick up single/multivariate Calculus as well as Linear Algebra. You will thank yourself later.

Best of luck !

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What tools to learn depends on your goals.

If you want to be an expert at applying current Machine Learning methods, then you can attend courses that teach those tools.

Most of the DLAI offerings are exactly that.

If you want to create new types of Machine Learning tools (push the state of the art ahead in algorithms), then you’ll need a different curriculum and years of experience working with small teams of experts. Now is a great time to start that voyage.

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