🎓 Offline Classroom Training
⌛ 4 Weekends
📍 Pimple Saudagar, Pune
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.
Data Engineers seeking AI-augmented pipelines
Analytics Engineers and Data Analysts
Data Scientists focusing on MLOps
Technical Leaders and Solution Architects
â—Ź Data Engineers automating pipelines and integrating AI
â—Ź Analytics Engineers working with dbt, Airflow
â—Ź Data Analysts seeking task automation
â—Ź Data Scientists focusing on MLOps
â—Ź 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