Debugging Python Code: From Traceback to Root Cause
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About this course
Debugging Python Code: From Traceback to Root Cause teaches a reliable way to find out why Python code fails and to fix the real cause rather than the symptom. The first lesson reads a three-frame traceback that ends in a ValueError, bottom to top, and follows it back to the call that passed the bad value. From there the course covers chained exceptions, the built-in exceptions and what usually causes each, classic Python gotchas such as mutable default arguments and late-binding closures, a systematic method of reproducing, minimising and bisecting, print and logging debugging, pdb and breakpoint(), debugging with pytest, import and virtual environment problems, pandas and encoding bugs, async and concurrency bugs, profiling with cProfile and tracemalloc, git bisect, and checking AI-generated code. The course has 173 lessons and about 1153 minutes of content. Each lesson is a short narrated reading card followed by MCQ practice with an explanation for every answer.
How the lessons work
Each lesson starts from a short piece of broken Python and what it prints: a traceback, a wrong result or a hang. The cause is explained against that code, then MCQ practice shows similar code and asks which line fails, what the output is, or which change fixes it, with an explanation for every answer. Tracebacks and outputs are shown as CPython 3.12 prints them, so what you practise matches what you see in your own terminal.
Who this course is for
Students, freshers and junior developers who can write Python but lose time when it breaks, and anyone preparing for coding rounds where reading an error quickly matters. It also suits data analysts whose notebooks fail on messy data and developers who inherit code they did not write. If you are still learning the language itself, start with Python; this course assumes you know the basics and focuses on what to do when the code does not behave.
MCQ practice vs video courses
Debugging videos usually show an expert fixing a bug they already understand, which makes it look easy. The skill you need is deciding where to look next: which frame matters, whether the bug is in the data or the code, whether to add a print or a breakpoint. This course gives you the broken code and the evidence and asks you to choose, then explains why. That builds a method you can use on bugs no video has covered.
Best way to learn debugging
Keep a Python 3.12 environment open and run the broken examples yourself before reading the fix. Try breakpoint() on the first bug you meet rather than adding prints. Answer each MCQ before reading its explanation, and note the gotchas that caught you out, since those are the ones that will appear in your own code. When you next hit a real bug, use the reproduce, minimise and bisect steps from the Systematic Method topic.