This module introduces the list as a built-in data structure in Python. It covers the basics of what a list is, how to create lists, including heterogeneous lists (lists containing different data types), and how to access, slice, and manipulate them. Additionally, learners will explore list comprehension, a powerful Pythonic way to work efficiently with lists.

This module explores the tuple, a built-in data structure in Python. It covers what a tuple is, how to create one, and how to work with heterogeneous tuples (containing elements of different types). Learners will learn how to access elements by index and through iteration, slice tuples, and understand the concept of tuple comprehension for efficient data handling.

This module introduces the set, a built-in data structure in Python that stores unique, unordered elements. It covers what a set is, how to create one, and how to manage elements within a set. The module also explores set operations (such as union, intersection, and difference), common set methods, and set comprehension for efficient data manipulation.

This module focuses on the dictionary (dict), a built-in Python data structure that stores key-value pairs. It covers what a dictionary is, how to create one, and how to access its elements using keys. Learners will explore common dictionary methods to manipulate data, and the module concludes with an introduction to dictionary comprehension for efficient data creation and processing.

In this module, students will apply their knowledge of Python’s built-in data structures—list, tuple, set, and dictionary—by working on a real-life case study involving a grade book for students. They will use each of the data structures to store and manipulate the grade data, allowing them to practice and improve their understanding while comparing the advantages and limitations of each structure.