You have successfully registered
CertifiedDatabricks Engineers & Architect role learning with Generative AI & Agentic AI With Pyspark– (Supply Chain, Manufacturing, Chemical & Petrolium, Retailed and Automobiles area)
Course contained 4 modules:
Module -1: Databricks Engineering & Architect
Module – 1.1 Databricks + PySpark (Data Engineer → Enterprise Architect)
Module 1.2: Databricks Technical & Enterprise Architecture (Only for Architect Role)
Module -2 Enterprise Data & AI Master Curriculum with Databricks
Module-3: DBT (Data Build Tool Developer) With Databricks
Module-4: Enterprise Analytics & GenAI using Databricks + Snowflake
Module -5: Any one-use case will be discussed and worked as POC by students.
TRACK A – Generative AI Engineering & Enterprise AI Architecture
- AI Strategy for Enterprises: ROI-driven GenAI adoption, failure patterns of POCs, AI maturity models
- LLM Fundamentals: Transformers, MoE, reasoning models, tokenization, context windows
- Model Landscape: Open-source vs Closed-source, sovereign AI, domain models
- Prompt Engineering at Scale: Prompt-as-code, templates, versioning, testing, guardrails
- Retrieval-Augmented Generation (RAG): vector search, hybrid retrieval, GraphRAG, document chunking strategies
- Agentic AI Systems: tool agents, planner/executor patterns, memory, human-in-the-loop control
- Multi-Agent Architecture: orchestration, task routing, failure handling
- LLMOps & AgentOps: evaluation pipelines, hallucination detection, semantic monitoring
- AI Governance: security, access control, auditability, compliance, data sovereignty
- Cost & Performance Engineering: token optimization, caching, batch vs real-time inference
- Enterprise AI Reference Architectures across regulated industries
View this Course
Certified
