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This module introduces the fundamentals of Python, including its history, features, applications, installation, and environment setup. Students will learn Python syntax, variables, data types, operators, input/output operations, comments, and formatted output, building a strong foundation for programming and problem-solving.
This module introduces Python control structures, including indentation, conditional statements, loops, and loop control statements. Students will learn to use iterators, generators, assertions, and single-line statements to develop logical thinking and solve programming problems efficiently.
This module introduces Python's built-in data structures, including lists, tuples, sets, and dictionaries. Students will learn their operations, methods, indexing, slicing, updating techniques, and nested structures through practical examples for efficient data organization and manipulation.
This module introduces Python functions, including their definition, calling, arguments, and return values. It covers default and keyword arguments, recursion, lambda functions, and variable scope. Students learn to use built-in functions, work with modules, import libraries, and create user-defined modules for developing modular, reusable, and efficient Python programs and applications.
This module introduces Object-Oriented Programming (OOP) concepts in Python, including classes, objects, constructors, variables, and methods. It covers inheritance, polymorphism, encapsulation, and data hiding to promote code reusability and security. Students learn to design real-world applications using object-oriented principles through practical examples and problem-solving exercises.
This module introduces file handling in Python, including file operations, file modes, and reading and writing text and CSV files. It covers exception handling using `try-except` and `finally` blocks, handling multiple exceptions, and creating user-defined exceptions to build robust, reliable, and error-resistant Python applications.
This module introduces the fundamentals of NumPy and Pandas for data handling and analysis. Students learn array creation and operations, Series and DataFrames, data manipulation and cleaning techniques, and basic data analysis methods to efficiently process, organize, and interpret data for real-world applications and data-driven decision-making.
This module introduces Python applications in automation, including automation scripts, file and task automation, data processing, and command-line interface (CLI) applications. Students learn to develop practical solutions for automating repetitive tasks and solving real-world problems, enhancing productivity, efficiency, and problem-solving skills using Python programming.
This module introduces Python-based application development, focusing on designing and building practical applications using modular programming principles. It covers code optimization techniques, documentation practices, and project presentation skills, enabling students to develop efficient, maintainable, and professional software solutions while effectively communicating project outcomes and implementation strategies.
This course introduces the fundamentals of Python programming, covering core concepts such as variables, control structures, functions, data structures, modules, and object-oriented programming. Students will learn file handling, exception handling, and the use of Python libraries while developing problem-solving and coding skills. Through practical exercises and real-world projects, the course prepares learners to build Python applications and apply programming concepts in diverse domains.
Learning Objectives:
By the end of the course, students will be able to:
I. Explain Python syntax, variables, data types, and basic programming concepts.
II. Apply control structures and data structures to solve problems.
III. Develop modular programs using functions and object-oriented programming.
IV. Implement file handling, exception handling, and use Python libraries.
V. Design and develop Python-based applications for real-world problems.
Why This Course Matters for University Students
Develops logical thinking and problem-solving abilities.
Builds essential programming and computational skills.
Provides a foundation for AI, Data Science, Machine Learning, and Automation.
Enhances coding, analytical, and software development skills through practical applications.
Improves employability and career opportunities across multiple disciplines.
Encourages innovation, research, and interdisciplinary learning.
Equips students with future-ready digital skills required in academia and industry.
