Pranav Srivastava

Learning Platform

From AI foundations to production systems.

Five structured tracks — each a focused sub-topic with its own courses, prerequisites, and clear outcomes. Grounded in academic rigour, built for practical application.

Want one runnable thing in under an hour instead? Try a hands-on lab.

How it all connects

Not a pile of topics — a path. Foundations feed the applied work, and it all comes together in the capstone. You can enter at any stage; hover a track to see what it needs and what it unlocks.

1

Start here

No prior AI knowledge required

2

Build deeper

Apply foundations to real data and systems

3

Capstone

Integrate everything into a running system

Hover a track to trace the path it needs — and the ones it unlocks.

Topics covered

Mathematics for AIMachine LearningDeep LearningNatural Language ProcessingComputer VisionKnowledge GraphsMetaheuristic OptimisationData PipelinesApache SparkDatabricksFeature EngineeringVector DatabasesLLMs in PracticeSemantic SearchAI AgentsMCPAI ObservabilityMLOpsREST API DesignGraphQLAWS ArchitectureDevOps / CI-CDPersonal AI OS

How this platform was built

These courses are written from real experience — not assembled from documentation. The AI Foundations track draws from academic research including an MSc in AI at Munster Technological University. The Applied AI and Personal AI OS tracks document systems built and running in practice. Nothing is invented; everything is tested.

About the author