Master Gen AI-powered
data engineering in 5 weekends

Automate pipelines, generate code instantly, and build production-ready
RAGsystems that will 10x your productivity and make you indispensable in AI era

🎓 Offline Classroom Training

⌛ 4 Weekends

📍 Pimple Saudagar, Pune

GenDataEngineering Video

Gen AI for Data Engineering

Generative AI for Data Engineering is a 30-hour hands-on program that empowers data professionals to integrate AI into every stage of the data lifecycle. Learn to build self-healing ETL pipelines, automate code generation, parse unstructured data, and deploy AI-powered solutions with real-world labs and a capstone project.

Who Is This Course For?

Data Engineers seeking AI-augmented pipelines

Analytics Engineers and Data Analysts

Data Scientists focusing on MLOps

Technical Leaders and Solution Architects

Why This Course

45% hands-on labs with live code exercises
Real-world capstone showcasing end-to-end AI workflows
Immediate productivity gains—automate 70% of repetitive tasks
Covers multiple platforms: commercial and open-source LLMs
Production-ready MLOps, governance, compliance

Tools You Will Master

Group 47
Group 49
Group 48
Group 50
Group 55
Group 52 1

Delivery Methods

Offline Classroom
Training
Cloud-based lab environment with preconfigured APIs
Mini-projects, quizzes, and capstone review

Frequently Asked Questions

Who should join this course?

● Data Engineers automating pipelines and integrating AI
● Analytics Engineers working with dbt, Airflow
● Data Analysts seeking task automation
● Data Scientists focusing on MLOps
● Technical Leaders evaluating Gen AI strategies

10+ hands-on projects including:
Data augmentation app with API and frontend​
Self-healing ETL pipeline with automated recovery​
Text-to-SQL query interface​
RAG-powered data assistant with vector databases​
Real-time data enrichment service​
PDF/document extraction tool​
Automated code generator for data pipelines​
Capstone: End-to-end Gen AI solution integrating all skills​

AI Platforms: OpenAI GPT-4, Claude, Gemini, GitHub Copilot​
Frameworks: LangChain, LlamaIndex, Haystack​
Vector DBs: Pinecone, Weaviate, Qdrant​
Data Stack: Airflow, dbt, Spark, Kafka​
Cloud: AWS, Azure, GCP​
Dev Tools: Python, SQL, FastAPI, Streamlit, Jupyter​

Continuous Assessment (70%):
Module quizzes (20%)
Lab exercises (30%)
Mid-course project (20%)
Final Capstone (30%):
Build end-to-end Gen AI solution​
Present to instructors and peers
70% overall score required for certificate

Yes! Designed for working professionals:
Flexible Options:
Part-time: 3 sessions/week, evenings or weekends (2.5-3 hrs each)
Full-time: 5-day intensive bootcamp
Corporate: Custom scheduling
Professional-Friendly:
Immediately applicable skills​
Recorded sessions for missed classes
24/7 lab access​
8-10 hours/week commitment over 3-4 weeks
80% of participants complete while working full-time

Be Among the First to
Master Agentic AI in Data Engineering