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Python & Data Foundations
Prepare and explore data with Python, NumPy and pandas, and build a foundation in the mathematics used in AI.
Machine Learning
Train supervised and unsupervised models, engineer features and evaluate results against useful baselines.
Deep Learning
Explore neural networks and practical approaches to working with text and image data.
LLMs & AI Applications
Integrate language models, embeddings and retrieval-augmented generation into useful applications.
APIs & Model Deployment
Serve models through APIs and connect them to applications with appropriate validation and error handling.
MLOps & Evaluation
Track experiments, version models and monitor deployed systems for quality, reliability and changing data.
Practical Capstone Project
Bring the workflow together: define a problem, prepare data, evaluate a model and deploy an AI application.
Who Can Join?
Students, developers and professionals interested in AI engineering. Speak with our team about prerequisites and a learning path suited to your background.