This module focuses on essential data manipulation techniques using Python’s core data structures. Learners will explore how to define and access data using lists, apply indexing for precise element referencing, and leverage slicing techniques for flexible data extraction. The module also covers combining sequences and manipulating structured data efficiently. Through practical examples and guided walkthroughs, students build foundational skills necessary for working with collections in real-world Python applications.

This module introduces learners to Python’s membership operators and collection-related functions. Learners will examine how to test for values in sequences using in and not in, apply list functions and methods for common operations like adding, removing, and searching elements, and understand the structure and use of tuples. The module also revisits and expands upon essential string operations for character testing, transformation, and searching. By the end of this module, learners will be well-equipped to manipulate lists, tuples, and strings with precision and fluency.

This module builds on foundational string concepts by introducing advanced formatting and string processing methods in Python. Learners will explore formatting numbers and text using width, precision, and alignment features, and apply practical techniques such as using find, join, translate, and case transformation methods. The module also includes in-depth string cleaning and replacement operations using strip, split, and translation tables. By mastering these utilities, learners gain the ability to write more precise, readable, and flexible string manipulation code.