About the course
Dive into Python programming with our streamlined course, perfect for those new to coding or looking to solidify their Python skills. Python stands as the foundational language for Artificial Intelligence (AI) and Machine Learning (ML), driving innovation across countless industries. Its clear, readable syntax and expansive ecosystem make it the ideal starting point for anyone aspiring to work in AI, data science, automation, or general programming. This 3-day intensive and hands-on training course, "AI Augmented Python Programming," aims to start you on your journey to mastering Python, balancing theoretical knowledge sharing and practical hands-on exercises.
Crucially, this course goes beyond traditional programming instruction. You'll learn to effectively augment your coding skills with Large Language Models (LLMs) such as ChatGPT, Copilot, Gemini, or DeepSeek Coder. We will guide you on how and when to trust AI for on-the-spot clarifications, additional explanations, and direct coding assistance, showing you how to leverage these powerful tools to accelerate your learning process and enhance your ongoing projects. This approach ensures you not only learn Python fundamentals but also gain proficiency in modern, AI-assisted development workflows.
The curriculum covers essential Python fundamentals: from setting up your development environment and understanding Basic Syntax and Concepts, to mastering Variables and Data Types, Operators and Expressions, and fundamental Control Structures. You'll delve into Python's powerful Data Structures and Collections (Lists, Tuples, Dictionaries, Sets) and learn to write reusable code through Functions and Modular Programming. Essential practical skills like Basic Exception Handling and Basic File Operations are included for robust application development. The course concludes by introducing you to Working with External Libraries using pip and virtual environments, all reinforced through practical exercises and a culminating mini-project.
This Python foundation training course is available as part of a wider training programme or as a standalone workshop - we are happy to customise the syllabus to suit you and your team's learning goals, project requirements, and accommodate your preference for on-site / remote delivery.
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- Understand the fundamental concepts of Python programming and effectively set up a functional development environment.
- Leverage Large Language Models (LLMs) such as ChatGPT or Copilot for coding assistance, on-the-spot clarifications, and accelerating the learning process.
- Apply core programming principles, including variables, data types, operators, and expressions, to write simple Python scripts.
- Control the flow of program execution using conditional statements (if-else) and loop constructs (for, while).
- Effectively use and manipulate Python's built-in data structures and collections, including lists, tuples, dictionaries, and sets.
- Define and call functions, understand basic variable scope, and create simple reusable code modules.
- Implement basic error handling using try-except blocks to create more robust programs.
- Perform fundamental file input and output operations to read from and write to text files.
- Install and manage external Python libraries using pip and utilise virtual environments for project isolation.
- Apply foundational Python programming concepts by completing practical exercises and a reinforcing mini-project.
- Possess the essential Python skills required as a launchpad for further learning in AI, Machine Learning, and data science.
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This 3-day intensive hands-on training course is perfectly suited for absolute beginners to programming or individuals with minimal coding experience who are looking for a structured, practical, and comprehensive introduction to the Python language. It is ideal for:
Anyone new to programming eager to learn Python as their first language.
Professionals from non-technical backgrounds looking to acquire foundational coding skills for data analysis, automation, or general problem-solving.
Aspiring data scientists or AI practitioners who need to build a strong Python programming base before diving into more advanced topics.
Students or researchers who require Python skills for their academic or project work and wish to integrate modern AI assistance tools.
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No prior programming experience is required, however, participants should have:
Basic computer literacy and comfort with navigating a graphical user interface (GUI).
Ability to install software on their computer (guidance will be provided if needed).
A logical approach to problem-solving.
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This Python course is available for private / custom delivery for your team - face-to-face, on-site at your location of choice, or remotely via MS Teams or your own platform of choice - get in touch to find out how we can deliver tailored training which focuses on your project requirements and learning goals.
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Introduction to Python
Python Overview: Understanding what Python is, its common uses, and its role in AI/data.
Setting up the Environment: Installing Python, choosing a code editor/IDE (e.g., VS Code, PyCharm Community), and running your first Python program.
Basic Syntax and Concepts: Understanding Python syntax, comments, basic print statements, and how Python code executes.
Core Programming Principles
Variables and Data Types: Exploring Python variables, standard data types (integers, floats, strings, booleans), and basic type conversion.
Operators and Expressions: Learning about arithmetic, comparison, assignment, and logical operators.
Control Structures: Introducing if-else statements for decision-making, and for and while loops for repetitive tasks. Understanding break and continue statements.
Day 2: Python Data Structures and Functions
Data Structures and Collections
Lists: Understanding ordered, mutable sequences. Creating, accessing, modifying, and common list methods (append, remove, sort).
Tuples: Understanding ordered, immutable sequences. When and why to use tuples.
Dictionaries: Exploring key-value pairs for efficient data storage and retrieval. Common dictionary operations (creation, access, adding, deleting).
Sets: Basics of unordered collections of unique elements and simple set operations.
Functions and Modular Programming
Defining and Calling Functions: Basics of creating reusable blocks of code using the def keyword.
Function Parameters and Return Values: Passing information into functions and getting results back.
Scope of Variables: Understanding local versus global variables (basic concepts).
Introduction to Modules: How to import and use standard Python modules (e.g., math, random) for additional functionality.
Day 3: Practical Tools and Application Foundations
Basic Exception Handling
Understanding Errors & Exceptions: What happens when code goes wrong.
Try-except blocks: Catching and handling common exceptions (ValueError, FileNotFoundError, ZeroDivisionError).
Providing user-friendly error messages.
Basic File Operations
Reading from files: Opening text files and reading their content.
Writing to files: Creating and writing new text files.
Using the with open(...) as ... statement for safe file handling.
Working with External Libraries
Introduction to pip: Python's package installer for managing third-party libraries.
Installing and using external packages (e.g., requests for simple web data, or pandas for reading a CSV - focusing on installation and basic interaction rather than deep library use).
Virtual Environments: Understanding why they are crucial and how to create and activate a basic virtual environment (venv).
Consolidating Practical Exercises / Mini-Project
A guided, hands-on mini-project that integrates concepts learned throughout the course (e.g., a simple command-line application that reads data from a file, performs some calculations using functions and data structures, and handles basic user input errors).
Q&A and next steps for continued learning.
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Here are some key online resources for continuing your Python learning journey after this course, particularly for those interested in AI and data-driven applications, and leveraging AI tools:
Official Python Documentation: The definitive guide for the Python language.
PyPI (Python Package Index): The official repository for Python packages.
Guides for Recommended IDEs/Editors:
Visual Studio Code (VS Code): Free, powerful, and excellent Python support.
PyCharm Community Edition: A dedicated Python IDE with many features, free version available.
Jupyter Notebooks / Lab: Ideal for interactive coding, data exploration, and learning.
Virtual Environments Documentation:
venv (Python's built-in tool): https://docs.python.org/3/library/venv.html
PEP 8 - Style Guide for Python Code: Learn about Python's recommended coding style for readability.
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