Description
Who Should Attend
This course is suitable for individuals who are new to Python or looking to build a solid programming foundation, including:
• Developers new to Python
• Professionals transitioning from other programming languages
• Individuals entering data, AI, or software development roles
• Technical professionals requiring Python for automation or scripting
Prerequisites
No prior experience with Python is required.
A basic understanding of general programming concepts is helpful but not essential.
Learning Objectives
By the end of this course, participants will be able to:
• set up Python and develop a simple working application
• declare and work with core data types including strings, numbers, and dates
• use and manipulate data structures such as lists, tuples, dictionaries, and sets
• implement program logic using conditional statements and loops
• structure code using functions, classes, and modules
• read from and write to files and directories
• handle and manage exceptions and errors effectively
Course Content
Setting Up Python and Developing a Simple Application
Participants begin by setting up their environment and building their first Python application.
Topics typically include:
• setting up the Python development environment
• writing Python statements
• creating and running a Python application
• identifying and preventing common errors
Processing Simple Data Types
Participants learn how to work with Python’s fundamental data types.
Topics typically include:
• working with strings and integers
• processing decimal and floating-point values
• handling mixed number types
• performing operations on basic data types
Processing Data Structures
This section focuses on organising and manipulating collections of data.
Topics typically include:
• working with ordered data structures (lists, ranges, tuples)
• working with unordered data structures (dictionaries, sets)
• selecting appropriate structures for different use cases
• manipulating and accessing data efficiently
Writing Conditional Statements and Loops
Participants learn how to control program flow and implement logic.
Topics typically include:
• writing conditional statements
• implementing loops
• controlling execution flow
• building structured and readable logic
Structuring Code for Reuse
This section introduces techniques for building reusable and maintainable code.
Topics typically include:
• defining and calling functions
• creating and using classes
• importing and using modules
• structuring code for clarity and reuse
Processing Files and Directories
Participants learn how to interact with the file system.
Topics typically include:
• writing to text files
• reading from text files
• retrieving directory contents
• managing files and directories programmatically
Dealing with Exceptions
This section focuses on handling errors and improving program robustness.
Topics typically include:
• handling exceptions
• raising exceptions
• writing reliable and fault-tolerant code
Additional Topics
Participants are introduced to supporting concepts and best practices.
Topics include:
• key differences between Python 2 and Python 3
• Python style guidelines and coding standards
• alignment with Python Institute certification pathways
Delivery Approach
This is a hands-on, structured programme designed to build practical capability.
It includes:
• instructor-led sessions
• guided exercises and practical examples
• step-by-step development of working applications
• real-world programming scenarios
Duration
3 Days
Delivery Options
This course can be delivered as:
• a public scheduled course
• a private team programme
• virtual delivery
• on-site classroom training
Outcomes
After completing this course, participants will be able to:
• develop structured and functional Python applications
• work confidently with data types and data structures
• implement logic using conditions and loops
• write reusable code using functions, classes, and modules
• manage files and handle errors effectively
• build a strong foundation for further learning in data science, AI, or software development
Additional Notes
This course provides a strong foundation for progression into areas such as:
• data analysis and data science
• machine learning and artificial intelligence
• web development using Python frameworks
• automation and scripting
Participants will leave with a practical understanding of Python that can be applied immediately in real-world environments.
Senior Software Architect & Development Instructor
Microsoft MVP | 30+ Years Engineering Experience
This course is presented by Peter
Peter brings more than 30 years of experience in software architecture, development, and technical training, helping engineering teams design, modernise, and improve complex systems across enterprise, cloud, embedded, and data-driven environments.
He has been exploring the role of AI in software engineering since the early wave of modern AI tooling, focusing on how development teams can use AI productively while maintaining strong engineering standards, governance, and architectural discipline.
Alongside his engineering background, Peter has a Master’s level background in Mathematics and is currently working towards a PhD, bringing deep analytical insight into how AI systems behave and how engineers should evaluate and integrate them responsibly.





