AI & Machine Learning
This program moves from the mathematical foundations of machine learning through to building, evaluating, and deploying deep learning models in production. You will implement algorithms from scratch to understand how they work, then apply industry-standard frameworks (TensorFlow, PyTorch) to solve real problems in computer vision, natural language processing, and generative AI. The capstone project requires you to scope, build, and present an end-to-end ML product that solves a real African business or social challenge.
What You'll Learn
- Mathematics for ML: linear algebra,calculus, probability, statistics Supervised learning: regression, classification, decision trees
- SVMs Unsupervised learning: clustering dimensionality reduction (PCA, t-SNE)\ Model evaluation, cross-validation, and hyperparameter tuning
- Feature engineering and selection
- Neural networks and deep learning fundamentals
- Convolutional Neural Networks (CNNs) for computer vision
- Recurrent Neural Networks (RNNs) and LSTMs for sequence data
- Natural language processing (tokenization, embeddings, transformers)
- Introduction to large language models (LLMs) and prompt engineering
- Generative AI: GANs and diffusion model concepts
- MLOps: model deployment, monitoring, and versioning
Who This Course is For
- Developers and data analysts who want to specialise in AI/ML
- Data Science graduates looking to deepen their ML engineering skills
- Engineers and researchers from any domain with strong Python skills
- Ambitious learners who have completed the Data Science and Analytics course
Prerequisites
- Solid Python programming skills
- Comfortable with statistics and basic linear algebra
- Prior exposure to data analysis (Pandas, NumPy) recommended
- Completion of Data Science and Analytics course or equivalent experience
What's Included
This course features a robust hybrid learning model:
- Physical Classes: 3 days per week — hands-on coding, collaborative projects, and core lectures.
- Online Classes: 2 days per week — code reviews, debugging, Q&A, and deep dives.
- Physical Weekend Sessions: Admits students who can only attend weekend classes - Saturdays and Sundays.
- Course Materials
- Code Mentorship
- Portfolio Development
- Certificate of Completion
Tools & Technologies You Will Use
- Python
- TensorFlow / Keras
- PyTorch
- Scikit-learn
- Hugging Face Transformers
- Jupyter Notebook
- MLflow
- Docker
- Git & GitHub
Capstone Project
End-to-End AI Product
Identify a real African business or social challenge and build a deployable AI product to address it — from data collection and model training to a live API or web interface — presented as both a technical paper and a live product demo.