Python Short Course
Learn Python from the ground up and start writing real, working programmes quickly. This course covers everything from syntax basics and data structures to object-oriented programming (OOP) and file handling. You will also explore practical tools like pandas, web scraping, and data visualisation. By the end, you will have the skills to automate tasks, process data, and build command-line tools confidently.
What you will learn:
This course takes you from installing Python to building complete, practical programmes using professional techniques. You will learn core syntax, control flow, functions, and Python's essential data structures. You will handle files, manage exceptions, and apply object-oriented programming (OOP) to real design problems. The curriculum also covers the standard library, third-party packages, Git version control, and data analysis with pandas. You will write unit tests, debug code effectively, and automate repetitive tasks. Every topic builds directly on the last, giving you a solid, connected foundation in Python development.
How you study in practice Python Short Course
How you practise Python Short Course
For companies looking to train their teams
With Dedika for Businesses, the course includes exercises and examples tailored to your own business and the specific needs of your company.
Course content
8 Chapters • 33 LessonsDuration between 4 and 360 hours (you decide)
Chapter 1HideHide detailsSee detailsPython Environment and Syntax Basics
Python Environment and Syntax Basics
Lesson 1 • Variables and Basic Data Types
Introduces variable assignment and Python's built-in primitive types. Students gain the ability to store and label data in programs.
Lesson 2 • Core Syntax Rules and Structure
Teaches indentation, comments, and statement structure. Correct syntax habits prevent errors throughout the entire course.
Lesson 3 • Input, Output, and Simple Expressions
Covers print(), input(), and arithmetic expressions. Students can write interactive scripts that accept and display data.
Lesson 4 • Installing Python and Setting Up Tools
Covers Python installation, virtual environments, and editor setup. Establishes the technical foundation every subsequent chapter depends on.
Chapter 2HideHide detailsSee detailsControl Flow and Decision Making
Control Flow and Decision Making
Lesson 1 • While Loops and Loop Control
Covers while loops and the break, continue, and pass statements. Students control loop termination precisely based on runtime conditions.
Lesson 2 • Conditional Statements
Covers if, elif, and else blocks for branching logic. Students write programs that respond differently to varying inputs.
Lesson 3 • For Loops and Iteration
Introduces for loops over sequences and ranges. Students automate repetitive tasks by iterating over data collections.
Lesson 4 • Boolean Logic and Comparisons
Teaches comparison operators and logical connectors. These are the building blocks of every conditional statement in the chapter.
Chapter 3HideHide detailsSee detailsFunctions and Code Reusability
Functions and Code Reusability
Lesson 1 • Parameters, Arguments, and Defaults
Covers positional, keyword, and default parameters. Students write flexible functions that handle varied calling patterns.
Lesson 2 • Scope and Variable Lifetime
Explains local, enclosing, global, and built-in scopes. Understanding scope prevents subtle bugs in multi-function programs.
Lesson 3 • Defining and Calling Functions
Teaches the def keyword, function calls, and return values. Functions are the primary tool for structuring all programs going forward.
Lesson 4 • Lambda Functions and Higher-Order Functions
Introduces anonymous functions and functions that accept or return functions. Students write concise, expressive code using functional patterns.
Chapter 4HideHide detailsSee detailsData Structures: Lists, Tuples, and Dicts
Data Structures: Lists, Tuples, and Dicts
Lesson 1 • Dictionaries and Sets
Covers key-value storage with dicts and unique-value storage with sets. Students model real-world relationships and perform fast lookups.
Lesson 2 • Tuples and Immutability
Introduces tuples as fixed-length, immutable sequences. Students use tuples to protect data integrity and enable dictionary keys.
Lesson 3 • List Comprehensions
Teaches compact list-building syntax with optional filtering. Students replace verbose loops with readable one-line expressions.
Lesson 4 • Lists: Creation and Manipulation
Covers list creation, indexing, slicing, and mutation methods. Lists are the most frequently used collection in Python programs.
Chapter 5HideHide detailsSee detailsFile Handling and Exception Management
File Handling and Exception Management
Lesson 1 • Reading and Writing Text Files
Teaches open(), read modes, and the with statement for safe file access. File I/O connects programs to persistent external data.
Lesson 2 • Raising and Creating Custom Exceptions
Covers the raise statement and defining custom exception classes. Students enforce business rules and communicate errors clearly.
Lesson 3 • Working with CSV and JSON Files
Covers the csv and json standard-library modules for structured data. Students exchange data with external systems and tools.
Lesson 4 • Exception Handling with Try and Except
Introduces try, except, else, and finally blocks. Students prevent crashes and provide meaningful feedback when errors occur.
Chapter 6HideHide detailsSee detailsObject-Oriented Programming in Python
Object-Oriented Programming in Python
Lesson 1 • Inheritance and Method Overriding
Introduces single and multiple inheritance and the super() function. Students extend existing classes without duplicating code.
Lesson 2 • Special Methods and Operator Overloading
Covers dunder methods like __str__, __repr__, and __eq__. Students make custom objects behave like built-in Python types.
Lesson 3 • Methods and Encapsulation
Covers instance methods, static methods, and name mangling for privacy. Students control access to object internals effectively.
Lesson 4 • Classes, Objects, and Attributes
Teaches class definition, instantiation, and instance attributes. Classes are the foundation of all object-oriented design patterns.
Chapter 7HideHide detailsSee detailsModules, Packages, and the Standard Library
Modules, Packages, and the Standard Library
Lesson 1 • Key Standard Library Modules
Surveys os, sys, math, datetime, and collections modules. Students solve common tasks without third-party dependencies.
Lesson 2 • Creating and Importing Modules
Teaches module creation, import syntax, and the module search path. Modular code is easier to test, maintain, and share.
Lesson 3 • Managing Third-Party Packages with pip
Covers pip install, requirements.txt, and virtual environment best practices. Students integrate the broader Python ecosystem into projects.
Lesson 4 • Organising Code into Packages
Covers package directories, __init__.py, and relative imports. Students structure multi-file projects cleanly and professionally.
Chapter 8HideHide detailsSee detailsApplied Python: Real-World Problem Solving
Applied Python: Real-World Problem Solving
Lesson 1 • Automating Repetitive Tasks
Covers file batch processing, renaming, and scheduled script execution. Students save hours of manual work through automation.
Lesson 2 • Data Processing and Transformation
Covers reading, cleaning, and transforming datasets using core Python. Students automate repetitive data-wrangling tasks end to end.
Lesson 3 • Introduction to Testing with unittest
Covers writing and running unit tests using the unittest module. Students verify program correctness and prevent regressions.
Lesson 4 • Building Command-Line Tools
Teaches argparse for CLI argument parsing and script packaging. Students deliver usable tools that non-programmers can run.
Lesson 5 • Debugging and Code Quality
Introduces pdb, print-based debugging, and linting tools. Students find and fix bugs faster and write cleaner, consistent code.
Your valid completion certificate
This course is for you:
Aspiring developers: ready to write their first real Python programs.
Marketing analysts: wanting to automate reports and clean data faster.
Career changers: building technical skills to enter the tech industry.
Scientists and researchers: looking to process experimental data with code.
Small business owners: eager to automate repetitive administrative workflows.
Hobbyists and makers: curious about building their own custom software tools.
What our students say
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