Workshops

Hands-on, expert-led sessions with practical skills you can apply right away.

MAY. 13-14 2027
Bengaluru

Workshop 1

Day 1

Designing the Modern Data Stack: Lakehouses, Semantic Layers, and AI-Ready Data Platforms

Your warehouse got you this far. Your lake promised flexibility. But the future lives in between — the lakehouse.

This workshop tears apart the modern data stack and rebuilds it. You'll go deep on Delta Lake, Apache Iceberg, ACID transactions, and schema evolution at scale. You'll discover why semantic layers are quietly becoming the most important piece of the puzzle — turning data chaos into self-service analytics teams actually trust.

And because no data platform is complete without AI, we'll design architectures where feature stores, ML pipelines, and analytics don't just coexist — they reinforce each other. Bring your SQL skills and curiosity. Leave with a blueprint you can use on Monday.

Workshop 2

Day 1

DataOps in Practice: Building Reliable and Observable Data Pipelines

Your pipelines work — until they don't. And when they break at 2 AM, nobody knows why.

This workshop fixes that. You'll learn how to bring real engineering discipline to data — CI/CD, automated testing, version control, and observability applied to pipelines the way software teams have done it for years.

We'll get hands-on with orchestration frameworks like Airflow and Dagster, build data quality checks that catch issues before your stakeholders do, and implement lineage tracking so you always know what went wrong and where. Bring your Python or SQL chops. Leave with pipelines that don't page you at midnight.

Workshop 3

Day 2

LLMOps for Data Engineers: Building Data Pipelines for AI Systems

Everyone's talking about prompts and models. Nobody's talking about the pipes feeding them. Your LLM is only as good as the data infrastructure behind it.

This workshop puts data engineers where they belong: at the center of the AI stack. You'll build the pipelines that power retrieval-augmented generation — from ingestion and transformation to embedding generation and vector store delivery, using tools you already know like Airflow and dbt.

We'll tackle dataset versioning, embedding lifecycle management, and keeping knowledge bases fresh so your LLM doesn't hallucinate last quarter's answers.

Workshop 4

Day 2

Operating LLM Pipelines at Scale: Monitoring, Evaluation, and Data Feedback Loops

You shipped your LLM app. Now the hard part starts. Production AI isn't a launch — it's a living system that drifts, degrades, and surprises you.

You'll learn to instrument the full pipeline — prompt telemetry, retrieval accuracy, embedding quality, and model output evaluation — using tools like LangSmith and Weights & Biases. We'll dig into dataset drift, prompt regressions, and retrieval pipelines that silently rot.

Most importantly, you'll build automated feedback loops that make your system smarter over time. Leave with the operational playbook that keeps your LLM reliable long after the demo hype fades.

Book your separate DES Workshop Pass to dive hands-on with expert-led sessions.

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Meet Your Trainers

Sachin Tripathi

Sachin Tripathi, with 9+ years of expertise in AI, ML, big data, and cybersecurity, is a renowned mentor who simplifies complex concepts and empowers learners through impactful, industry-relevant training.

Abhishek Kumar

Abhishek Kumar, with nearly a decade of experience in AI and data science, is a self-taught coder and applied AI expert known for building intelligent systems across predictive modeling, NLP, generative AI, and agentic systems.

Secure Your Seat at the Frontier of Data + Engineering.

Workshop Passes on sale now.

MAY. 13-14 2027 · Bengaluru

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