Introduction to Python for AI and Data Analytics

Course Structure

• Duration: 4 Weeks (Onsite | Online) 

• Onsite: Saturdays 10am - 5pm  (GMT+1) 

• Online: Tuesdays & Fridays 5.30pm - 8.00pm  (GMT+1) | Sundays 4.30pm - 8.00pm (GMT+1) 

• Labs: 12 Coding Labs | 3 Core Projects 

• Projects: 1 Capstone — On realworld AI Application

• Theory vs Practical: 30% / 70%

Ideal for

• Business professionals, marketers, writers, and entrepreneurs who use or want to use AI tools daily

• Educators, HR professionals, and administrators looking to automate repetitive tasks with AI

• Executives and managers who want to lead AI adoption in their teams without a technical background

• Content creators, journalists, and communicators who want to supercharge their output with AI

Description

Go from complete coding beginner to confident Python programmer — writing real scripts, analysing real datasets, and building the programming foundation that every AI and data science career is built on. Python is the language of AI, data science, and automation. This course takes participants from absolute zero to writing real Python code that solves data problems, automates tasks, and sets them up for every advanced AI and data course that follows. Built for beginners — delivered at a practical pace — with a dedicated Python foundations module for participants with no prior coding experience

What Participants Will Learn

• Set up a Python development environment and write, run, and debug Python scripts independently

• Apply core Python programming concepts — variables, data types, loops, conditionals, and functions — to real problem-solving scenarios

• Write object-oriented Python code using classes, objects, inheritance, and reusable component design

• Load, clean, filter, group, and transform datasets using Pandas for real-world data analysis

• Perform numerical computing and array operations using NumPy for data manipulation

• Connect to external data sources using file handling and API requests in Python

• Create basic data visualisations — charts, plots, and histograms — using Matplotlib

• Build three complete Python projects demonstrating automation, data analysis, and application development capability