This module focuses on decision-making in programming. Learners explore how programs can evaluate conditions and execute different instructions depending on the result. Through conditional statements and Boolean logic, learners learn how to control the flow of a program and design solutions that respond to different inputs or situations.

Learning Outcomes

• Use conditional statements to control program execution
• Write programs using if, elif, and else statements
• Construct logical expressions to evaluate conditions
• Trace and debug programs that include conditional logic

In this module, learners explore how functions allow programmers to break large problems into smaller, reusable components. They learn how to define functions, pass inputs as parameters, and return results. This module emphasizes writing modular, organized programs that are easier to maintain and reuse.

Learning Outcomes

1. Define and use functions in Python
2. Pass parameters to functions and return results
3. Organize programs into reusable components
4. Analyze and debug function-based programs

This module introduces loops, which allow programmers to automate repetitive tasks efficiently. Learners explore while loops and for loops, understand how iteration works, and practice writing programs that process repeated operations. The module also covers nested loops and debugging common looping errors.

Learning Outcomes

• Implement repetition using while and for loops
• Control loop execution using conditions and ranges
• Trace the execution of programs containing loops
• Use nested loops to solve more complex problems
• Identify and fix common loop-related errors

This module focuses on handling textual data and working with files in Python. Learners explore how to manipulate strings, process text data, and read from or write to files. These skills allow programs to store information, process real-world data, and interact with external resources.

Learning Outcomes

• Manipulate strings using built-in Python methods
• Extract and transform textual data
• Read from and write to text files
• Process file content using loops and string operations

In this module, learners begin working with collections of data using lists. They explore how lists store multiple values, how to modify them, and how to process list data using loops. The module also introduces important programming concepts such as mutable vs immutable data and basic searching and sorting techniques.

Learning Outcomes

• Create and manipulate lists in Python
• Iterate through lists using loops
• Understand mutable and immutable data types
• Implement simple searching and sorting operations

This module introduces two-dimensional data structures that represent tables or grids of information. Learners explore how nested lists can represent structured data and how nested loops can be used to process rows and columns of information.

Learning Outcomes

• Represent tabular data using two-dimensional lists
• Access and modify elements within grids
• Use nested loops to process structured data
• Extract insights from grid-based datasets

This module introduces recursion as a powerful programming concept where functions call themselves to solve problems. Learners explore how recursive solutions work, how to design recursive functions, and how to debug common recursion-related errors.

Learning Outcomes

• Understand the concept of recursion
• Identify base cases and recursive cases
• Implement recursive solutions to common problems
• Analyze and debug recursive programs

This module introduces dictionaries, a powerful data structure for storing and organizing information using key-value pairs. Learners explore how dictionaries differ from other data structures and how they can be used to solve real-world programming problems efficiently.

Learning Outcomes

• Create and use dictionaries in Python
• Retrieve and modify dictionary data using keys
• Compare dictionaries with lists and sets
• Build simple applications using dictionary-based data structures

In the final technical module, learners explore how Python can be used for basic data analysis and visualization. They learn how to manipulate numerical data using NumPy and create visualizations using matplotlib, allowing them to analyze and communicate insights from data.

Learning Outcomes

• Perform numerical computations using NumPy arrays
• Manipulate and transform datasets programmatically
• Create visualizations such as line charts, bar charts, and scatter plots
• Interpret visual outputs to understand data trends