How should I get started with DSA after learning Python?

I’d pick one beginner-friendly resource first rather than trying to follow two courses at once. Runestone’s Python data structures material is a reasonable place to build the basic ideas. Once those topics feel familiar, MIT 6.006 can add more depth, but it may feel like a lot if you’re new to algorithms.

For each topic, write a small implementation in Python, then try a couple of short problems that use it. A stack and a balanced-parentheses check is a good example.

Keep the learning loop small: read about one structure or algorithm, code it yourself, test it on a few inputs, and then solve a problem where it helps. Start with arrays and strings, then lists, stacks, queues, hash tables, recursion, trees, and graph traversal.

Also learn to estimate time and memory use as you go. You don’t need to memorize every detail up front, but being able to compare, say, a linear search with a binary search is part of understanding why an algorithm is useful.

Don’t let the course choice become the whole project. Pick a topic and spend more time coding than watching or reading. Try implementing a stack, queue, depth-first search, and breadth-first search in plain Python before leaning on packages. You’ll get a clearer feel for what the code is doing.

It’s fine to use Python’s built-in list and dictionary when solving problems. Implementing structures yourself is useful for learning, but you don’t have to rebuild everything every time. Once you understand the idea, practice choosing the right tool for a problem.

When a solution doesn’t click, trace it with a tiny example on paper. That often makes recursion or traversal much less mysterious.