Basic Python Programming Course
Learn Python from the ground up and start writing real, working programs fast. This course takes you from installation to object-oriented design, covering variables, functions, data structures, file handling, and more. Whether you're switching careers or adding a powerful skill to your toolkit, you'll build a rock-solid Python foundation that opens doors.
What you'll learn:
Configure a professional Python development environment using VS Code or PyCharm.
Build programs that use conditionals, loops, and functions to solve practical problems.
Manipulate strings, lists, dictionaries, and files with Python's core built-in tools.
Design reusable, modular code using object-oriented programming principles and class hierarchies.
Handle runtime errors gracefully with structured exception handling and custom exceptions.
Automate repetitive tasks, manage packages, and organise projects with modules and virtual environments.
How you study in practice Basic Python Programming Course
How you practise Basic Python Programming Course
For businesses looking to train their team
With Dedika for businesses, the course includes exercises and examples tailored to your own business and the way your company needs.
Course content
8 Chapters • 32 LessonsDuration between 4 and 360 hours (you decide)
Chapter 1HideHide detailsSee detailsPython Environment and First Steps
Python Environment and First Steps
Lesson 1 • Installing Python and Tools
Covers downloading Python, choosing an IDE, and verifying installation. Establishes the technical foundation every subsequent chapter depends on.
Lesson 2 • Code Style and Readability
Introduces PEP 8 conventions, indentation rules, and inline comments. Builds habits that improve code quality throughout the entire course.
Lesson 3 • Writing and Running Your First Script
Introduces the script execution model and the print function. Students produce their first working program and understand how Python runs code.
Lesson 4 • Python Interactive Shell Basics
Explores the REPL for rapid experimentation and immediate feedback. Reinforces syntax awareness before students write longer programs.
Chapter 2HideHide detailsSee detailsVariables, Data Types, and Operators
Variables, Data Types, and Operators
Lesson 1 • Variables and Assignment
Explains variable naming, dynamic typing, and assignment syntax. Provides the vocabulary needed to store and reference data in all future programs.
Lesson 2 • Strings and Text Manipulation
Introduces string literals, indexing, slicing, and common methods. Students can process and format text, a skill used in nearly every program.
Lesson 3 • Type Conversion and Input
Teaches explicit type casting and reading user input with input(). Connects data types to real program interaction and error prevention.
Lesson 4 • Numeric and Boolean Types
Covers int, float, and bool types with their arithmetic and logical operators. Students compute expressions and understand truthiness in Python.
Chapter 3HideHide detailsSee detailsControl Flow and Decision Making
Control Flow and Decision Making
Lesson 1 • Combining Conditions and Loops
Applies conditionals inside loops to solve practical filtering and counting problems. Prepares students for data processing patterns used throughout the course.
Lesson 2 • While Loops and Loop Control
Introduces while loops, break, continue, and infinite loop prevention. Students implement repetition patterns that depend on dynamic conditions.
Lesson 3 • Conditional Statements
Covers if, elif, and else syntax with nested conditions. Students direct program execution based on runtime values and logical tests.
Lesson 4 • For Loops and Iteration
Teaches for loops over sequences and the range() function. Connects iteration to lists and strings introduced in the previous chapter.
Chapter 4HideHide detailsSee detailsFunctions and Code Reuse
Functions and Code Reuse
Lesson 1 • Defining and Calling Functions
Introduces def syntax, parameters, and return statements. Students replace repeated code blocks with named, callable functions.
Lesson 2 • Lambda Functions and Built-ins
Introduces anonymous lambda functions and key built-in functions. Students write concise expressions and leverage Python's standard toolkit.
Lesson 3 • Default and Keyword Arguments
Covers default parameter values and keyword argument syntax. Students write flexible functions that handle optional inputs gracefully.
Lesson 4 • Variable Scope and Namespaces
Explains local, global, and enclosing scopes with the LEGB rule. Students avoid common bugs caused by unintended variable shadowing.
Chapter 5HideHide detailsSee detailsLists, Tuples, and Dictionaries
Lists, Tuples, and Dictionaries
Lesson 1 • List Comprehensions
Teaches concise list-building syntax with optional filtering. Students replace verbose loops with readable one-line expressions.
Lesson 2 • Tuples and Immutability
Introduces tuples as fixed sequences and explains when immutability is advantageous. Students use tuples for data integrity and multiple return values.
Lesson 3 • Lists and List Operations
Covers list creation, indexing, slicing, and mutation methods. Students manage ordered, changeable sequences of any data type.
Lesson 4 • Dictionaries and Sets
Covers key-value storage with dicts and unique-element sets. Students model real-world mappings and perform fast membership tests.
Chapter 6HideHide detailsSee detailsFile Handling and Exceptions
File Handling and Exceptions
Lesson 1 • Exception Handling Fundamentals
Teaches try, except, else, and finally blocks for controlled error handling. Students prevent crashes and provide meaningful feedback to users.
Lesson 2 • Working with CSV Files
Covers the csv module for structured tabular data. Students parse and generate CSV files, a common format in professional data workflows.
Lesson 3 • Reading and Writing Text Files
Introduces open(), read modes, and the with statement for safe file access. Students load external data and save program output to disk.
Lesson 4 • Custom Exceptions and Validation
Shows how to define custom exception classes and validate input data. Students enforce data contracts and produce informative error messages.
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, random, and datetime modules. Students solve common tasks without third-party dependencies.
Lesson 2 • Creating and Importing Modules
Explains module creation, import syntax, and the module search path. Students split programs into logical files for better maintainability.
Lesson 3 • Managing Third-Party Packages
Introduces pip, virtual environments, and requirements files. Students install and isolate dependencies for reproducible project setups.
Lesson 4 • Organising Code into Packages
Covers package directories, __init__.py, and relative imports. Students build scalable project structures used in professional Python development.
Chapter 8HideHide detailsSee detailsObject-Oriented Programming Fundamentals
Object-Oriented Programming Fundamentals
Lesson 1 • Inheritance and Polymorphism
Teaches single inheritance, method overriding, and super(). Students extend existing classes and write code that works with multiple object types.
Lesson 2 • Encapsulation and Properties
Explains private attributes, name mangling, and the @property decorator. Students control attribute access and enforce data validation in classes.
Lesson 3 • Classes and Objects
Introduces class definition, __init__, and instance attributes. Students create objects that bundle data and behaviour into a single unit.
Lesson 4 • Methods and Special Methods
Covers instance methods, class methods, static methods, and dunder methods. Students customise object behaviour and string representation.
Your valid completion certificate
This course is for you:
Career changers: seeking technology roles without a computer science degree.
Marketing professionals: wanting to automate reports and repetitive data tasks.
College students: building a practical coding skill alongside their main studies.
Small business owners: looking to script solutions for everyday operational problems.
Aspiring data analysts: needing Python basics before tackling data tools.
Hobbyists: eager to turn creative project ideas into working software.
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