Live sessions with practitioners. Ask questions, get answers, apply what you learn.
A few of the sessions we ran before the platform launched.
A hands-on workshop on retrieval-augmented generation. Embeddings, vector search, and wiring it all into a working internal knowledge base.
End-to-end system design for recommendations. Candidate generation, ranking, and the serving layer that keeps latency under 100ms.
The streaming architecture behind your ride ETA. Kafka, stream processing, and the trade-offs engineering teams make at that scale.
Why Spark exists, when to reach for it, and what a real pipeline looks like. Transformations, partitioning, and the mistakes that kill performance.
A case study on how one of India's biggest ethnic wear brands uses analytics to decide what to stock, where, and at what price.
The query language that runs the business world, made approachable. Joins, aggregations, and window functions on a real analytics dataset.
A week-long bootcamp for absolute beginners. Variables, loops, functions, and the building blocks you need before touching any data tool.
