Details

This comprehensive Python Programming course provides a practical introduction to one of the most versatile languages used in modern business automation and data analysis. Participants begin by mastering core syntax, variables, and control structures like loops and conditional logic. The curriculum then advances into essential data structures such as lists and dictionaries, and the development of modular, reusable code through functions and custom modules.

Beyond the basics, the course explores advanced programming techniques, including Object-Oriented Programming (OOP), functional decorators, and professional error handling and logging to ensure program reliability. The final stages of the course focus on real-world integration, training participants to process external files (Text and CSV), utilise regular expressions for text extraction, and build Graphical User Interfaces (GUIs) using PyQt. To conclude, students learn to connect their applications to SQLite databases, enabling them to create complete, data-driven software solutions.

To accommodate the 4-day duration, this course is structured to deliver four chapters per day. This pace moves from foundational syntax on Day 1 to building fully functional, data-driven applications by Day 4, with the shift towards data analysis and applied processing occurring at the start of Day 3.

Learning Objectives:

Foundations and Environment

Understand the Python ecosystem, including its business applications in automation and data analysis, and the differences between Python versions.
Navigate development environments to run code in interactive mode, script mode, or notebook environments.
Master basic syntax, including strict indentation rules, naming conventions, and the effective use of comments.
Manage variables and data types, including whole numbers (int), decimals (float), text (str), and logical values (bool), while performing necessary type conversions.

Logic and Control Flow

Perform calculations and comparisons using arithmetic, comparison, assignment, and logical operators.
Implement decision-making logic using if, elif, and else statements to control the path of a program.
Automate repetitive tasks through for and while loops, while utilising control statements like break and continue.

Data Management and File Processing

Organise complex data using structured collections such as lists and dictionaries, and understand the implications of mutability.
Manipulate text data through advanced string methods, slicing, and professional formatting with f-strings.
Handle external data by reading from and writing to text and CSV files, and using regular expressions for pattern matching and extraction.

Advanced Programming and Reliability

Build modular code by creating custom functions with parameters and return values, and organising them into reusable modules and packages.
Implement professional function techniques, including variable-length arguments (*args, **kwargs), closures, and decorators for tasks like logging.
Create robust applications using try and except for error handling and the logging module for debugging and progress tracking.
Apply Object-Oriented Programming (OOP) to group data and behaviour into classes, utilising inheritance and properties to model real-world business objects.

Specialized Applications

Develop Graphical User Interfaces (GUIs) using the PyQt library to build interactive forms and windows.
Manage structured data with databases by connecting to SQLite, performing SQL queries (insert, update, delete), and integrating database storage with GUI application

Delivery Methods

Delivery Method	Duration
Classroom Instructor-led classroom-based training. Classes are scheduled at various conference centres in the Sandton area or your premises. Stationary and printed manuals or online resources are included. Refreshments, including 2 tea breaks and a cooked meal for lunch are provided. Training is between 9 am to 4 pm. Classroom	4 days	Get a Quote
Live Virtual Training This course is delivered live via Microsoft Teams. You will be able to see and hear the instructor, view their whiteboard, and ask questions or communicate in the chat. Attend from the comfort of your own home or private office. Live Virtual Training	4 days	Get a Quote

Discounts Available

Brochure:

Information may change without notice.

Customer Testimonials

University of Venda

This course was an outstanding learning experience. The content was clear, practical, and easy to follow, making Python accessible even for beginners. I especially appreciated the hands-on approach, which helped me build confidence in applying my skills to real-world tasks. I would highly recommend this course to anyone looking to improve their programming and problem-solving abilities.

University of Venda

The Training had new concepts about Python using ipython

University of Venda

High quality training, The trainer takes training very seriously.

Audience

Aspiring Developers: Individuals looking to start a career in programming with Python.
Existing Programmers: Developers seeking to add Python to their skill set.
Data Analysts and Scientists: Professionals aiming to leverage Python for data analysis and machine learning.
Automation Enthusiasts: Anyone interested in automating tasks and improving workflow efficiency.

Pre-Requisites

It is essential that you have had recent basic programming experience in any programming language (ie not just 10 years ago while at College and nothing since).

If you don't, you must first complete our Introduction to Programming Course. This course will help you prepare for the Python Course.

Course Outline / Curriculum

This Python Programming course is designed to take learners from basic syntax to building professional, data-driven applications. The curriculum is divided into 16 chapters, transitioning from foundational logic to practical data analysis and application development after Chapter 8.

Part 1: The Foundations of Python (Chapters 1–8)

This section establishes the core programming logic and data handling skills.

Chapter 1: Introduction to Python and Its Ecosystem
- Overview of Python's business uses (automation, data analysis).
- Understanding Python 3 as the current standard and its basic execution model.
Chapter 2: Getting Started with Python
- Running code in interactive mode (quick tests) vs. script mode (reusable programs).
- Choosing environments like Jupyter Notebooks, IDLE, or VS Code.
Chapter 3: Basic Syntax and Structure
- Mastering indentation (4 spaces) to define code blocks.
- Distinguishing between statements and expressions.
Chapter 4: Variables and Data Types
- Working with core data types: int, float, str, and bool.
- Techniques for type conversion (e.g., int() or str()).
Chapter 5: Operators
- Performing calculations with arithmetic operators and making decisions with comparison/logical operators.
- Understanding the order of operations in business scenarios.
Chapter 6: Control Structures
- Decision-making using if, elif, and else.
- Repeating tasks with for loops (over sequences) and while loops (while conditions are true).
Chapter 7: Functions
- Defining reusable blocks of code with def and using parameters to pass information.
- Understanding the power of return values vs. just printing output.
Chapter 8: Data Structures
- Managing collections of data using lists (ordered) and dictionaries (key-value pairs).
- Learning about mutability and how it affects data handling.

Part 2: Applied Processing and Data Analysis (Chapters 9–12)

Following the foundations, the course shifts towards processing external data and structuring programs for professional use.

Chapter 9: Strings and Text Processing
- Advanced text cleaning using methods like strip(), split(), and replace().
- Professional output formatting using f-strings.
Chapter 10: Input, Output, and Working with Files
- Handling user input and reading/writing text files safely.
- Working with CSV files for tabular data and using Regular Expressions (Regex) to parse complex text.
Chapter 11: Modules and Packages
- Organising code into modules (.py files) and packages (folders).
- Using pip to install external libraries and managing virtual environments.
Chapter 12: Error Handling, Debugging, and Logging
- Using try and except to prevent program crashes.
- Implementing structured logging as a professional alternative to print() for debugging.

Part 3: Advanced Logic and Application Development (Chapters 13–16)

The final section covers high-level programming paradigms and building complete software interfaces.

Chapter 13: Advanced Functions
- Using *args and **kwargs for flexible inputs.
- Understanding closures and decorators to add reusable behaviour to functions (e.g., a logging decorator).
Chapter 14: Classes and Object-Oriented Programming (OOP)
- Modeling real-world entities by grouping data (attributes) and behaviour (methods) in classes.
- Learning inheritance to extend existing code and special methods like __init__ and __str__.
Chapter 15: Building GUI Applications with PyQt
- Creating desktop windows with buttons, text inputs, and labels.
- Building interactive forms that include data validation and event handling.
Chapter 16: Database Programming (SQLite)
- Transitioning from text files to relational databases for structured storage.
- Performing CRUD operations (Create, Read, Update, Delete) and integrating a database into a PyQt GUI.

Schedule Dates and Booking

To apply for a booking, click on the relevant "Book Now" button below.
Note: places are only fully secured once payment has been made.

Start Date	End Date	Branch	Status
Mon 6 Jul 2026	Thu 9 Jul 2026	Not Applicable	Scheduled	Book Live Virtual Training

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