Overview

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Description: This course lays the groundwork for your Python programming journey. You'll learn essential Python syntax, data structures, and control flow, while practicing debugging and basic code optimization techniques. Benefits: Gain a solid foundation in Python programming, enabling you to write clean, functional scripts and tackle common programming challenges. By the end of this course, you'll be able to: • Write basic Python programs using variables, data types, and operators. • Implement conditional statements and loops to control program flow. • Utilize functions and modules to write reusable and organized code. • Manipulate data using lists, dictionaries, and other data structures. • Debug code and handle errors effectively. • Employ Git for version control and create a professional GitHub portfolio. Tools/Software: Python, Jupyter Notebook, Git, GitHub This course is for entry-Level professionals looking to build a foundational understanding and experience with Python, while seeking employment as a Python developer. No prior work experience or degree is required.

Syllabus

Introduction to Python

This module establishes a foundation in Python programming. Learners examine Python’s key characteristics and common applications before setting up Python and Jupyter Notebook. They explore basic program structure, including indentation, statements, comments, variables, data types, operators, and expressions. Through introductory coding activities, learners write, execute, and troubleshoot simple Python programs.

Python basics

This module introduces the programming constructs used to control program flow and organize ordered data. Learners use conditional statements to support decision-making and loops to repeat actions and process data. They also trace code execution and identify common control-flow errors. The module then introduces Python lists, including their creation, modification, indexing, and slicing, enabling learners to store and process related values in simple programs.

Functions and modules

This module develops learners’ ability to organize Python code into reusable components. Learners create and call functions, work with parameters and return values, manage variable scope, and apply function-writing best practices. They also decompose programming problems into smaller tasks and create simple classes with attributes and methods. The module concludes with built-in modules, custom modules, external libraries, and the use of the pip package manager to extend Python’s functionality.

Data structures in Python

This module examines Python data structures used to organize, access, and manipulate information. Learners compare lists, tuples, dictionaries, and sets according to characteristics such as ordering, mutability, uniqueness, and access patterns. They apply these structures to practical data-management tasks and select suitable structures for different programming requirements. The module also introduces list sorting and linear and binary searching techniques for organizing and locating data.

Error handling and debugging

This module develops the skills required to identify and resolve errors in Python programs. Learners examine common exceptions, interpret error messages, and use print statements and interactive debugging tools to trace program execution. They also use try-except blocks to manage anticipated exceptions and prevent unexpected program termination. A systematic debugging process is applied to locate causes, test corrections, and improve program reliability.

Testing basics & version control

This module introduces practices used to test, manage, and present Python projects. Learners examine the purpose of unit testing and use pytest to create, organize, and execute tests. They then use Git to track changes and manage branches and distinguish Git-based version control from GitHub-based project hosting. The module concludes with the development of a professional GitHub portfolio that presents Python projects and technical skills.