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Enterprise AI Engineering (RAG, Agents & Deployment) Masterclass
Building Intelligent Systems with Retrieval-Augmented Generation, Autonomous Agents, and Scalable Deployment Strategies”
Master the future of enterprise AI with our 30‑day structured program on Retrieval‑Augmented Generation (RAG), AI Agents, and scalable deployment strategies. This hands‑on agenda covers Python, LangChain, AutoGen, cloud integration (Azure, AWS, GCP), and advanced visualization tools. Designed for professionals and educators, the course bridges theory with real‑world applications, culminating in a capstone project that delivers an end‑to‑end enterprise AI solution. Upskill with practical labs, agent development, and deployment best practices to stay ahead in the evolving AI landscape.
Enterprise AI Engineering (RAG, Agents & Deployment)
Building Intelligent Systems with Retrieval-Augmented Generation, Autonomous Agents, and Scalable
Deployment Strategies
📅 30-Day Agenda
Week 1: Foundations
- Day 1–2: Introduction to Enterprise AI Engineering – AI in enterprises, use cases, architecture overview
- Day 3–4: Retrieval-Augmented Generation (RAG) Basics – Concept, pipeline design, vector databases
- Day 5–6: Hands-on with RAG – Implementing RAG using LangChain / LlamaIndex
- Day 7: Reflection & mini-project setup
Week 2: Agents & Autonomy
- Day 8–9: AI Agents Fundamentals – Agent architectures, decision loops, tool usage
- Day 10–11: Multi-Agent Systems – Collaboration, orchestration, conflict resolution
- Day 12–13: Hands-on Agent Development – Build custom agents with frameworks (LangChain Agents, AutoGen)
- Day 14: Case study review & peer discussion
Week 3: Deployment & Scaling
- Day 15–16: Deployment Strategies – Containerization (Docker), APIs, microservices
- Day 17–18: Cloud & Enterprise Integration – Azure AI, AWS SageMaker, GCP Vertex AI
- Day 19–20: Monitoring & Governance – Logging, observability, compliance, ethical AI
- Day 21: Mid-program assessment & feedback
Week 4: Advanced Topics & Capstone
- Day 22–23: Optimization & Performance – Prompt engineering, caching, fine-tuning
- Day 24–25: Security & Reliability – Data privacy, adversarial robustness, failover systems
- Day 26–27: Capstone Project Development – End-to-end enterprise AI solution (RAG + Agents + Deployment)
- Day 28–29: Project presentations & peer review
- Day 30: Final assessment, certification, and roadmap for continuous learning
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