
Learn the basics of Python with hands-on tutorials for data science and machine learning, building confidence to write your own code and explore the language's features.
Explore Python basics for data science, including numbers, strings, indexing, slicing, and common operators. Learn via Jupyter notebooks and Anaconda, using the interpreter, modules, and print formatting to code.
Learn Python list basics: create lists, index and slice, concatenate, and mutate lists; compare assignment vs copy and explore shallow vs deep copies for nested lists.
Explore python control flow with practical examples of for and while loops, and learn break, continue, and pass, indentation rules, and if/elif logic with lists.
Define and call Python functions using def, formal and actual parameters with defaults, and returns, then implement stack and queue with lists and collections.deque.
This course starts with the Introduction to Python language. Then, I discuss about the data types available. Control flow structure is discussed. Different data structures like list, array, tuple, dictionary are explained. Stack, Queue and matrix implementation are explained. Modules and packages are discussed. Object oriented programming concepts in Python are also discussed briefly. For all the features, detailed hands-on coding are shown.