AI & Machine Learning
Structured, project-led training covering the complete learning path from foundations to practical delivery.
- AI foundations and career overview
- Python for AI and data science
- Mathematics, statistics and probability
- Data collection, cleaning and visualisation
- Supervised learning and model evaluation
- Unsupervised learning and clustering
- Feature engineering and dimensionality reduction
- Deep learning and neural networks
- Natural language processing
- Computer vision
- Reinforcement learning fundamentals
- Generative AI and large language models
- Prompt engineering and AI applications
- Model deployment and APIs
- MLOps, monitoring and versioning
- Responsible AI, bias and ethics
- Capstone projects and portfolio
- AI career preparation and interview skills