IntermediateLearning Outcomes
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Build Production-Ready LLM Apps: Engineer Python AI applications with structured Pydantic outputs using provider-agnostic APIs (Gemini, Claude, OpenAI, Ollama).
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Master LangChain Framework: Implement conversation memory, tool calling, multimodal capabilities, and interactive Streamlit UI frontends.
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Architect Advanced RAG Pipelines: Design vector database ingestion (Chroma, Pinecone, Qdrant), hybrid semantic search, re-ranking, and agentic retrieval APIs via FastAPI.
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Orchestrate Multi-Agent Systems: Build stateful, autonomous graph workflows, parallel nodes, and supervisor architectures using LangGraph.
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Implement MCP & Safety Guardrails: Connect custom FastMCP tools, handle retries, and integrate Human-in-the-Loop (HITL) authorization gates for secure agent execution.
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Deploy, Trace, & Scale AI Microservices: Containerize AI workflows with Docker, deploy to cloud environments, and track performance using LangSmith tracing, evaluation, and monitoring.
Course Description
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Overview: 3-month hybrid program (36 sessions / 54–72 hours) at NexusBerry Trainings Institute covering end-to-end Agentic AI engineering, multi-agent systems, and production LLM orchestration.
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Core Stack: Python, LangChain, LangGraph, FastAPI, Streamlit, RAG, Vector DBs, MCP, Docker, and LangSmith.
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AI Model Ecosystem: Provider-agnostic development with OpenAI ChatGPT, Anthropic Claude, Google Gemini, Groq, OpenRouter, and local Ollama models.
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Key Topics:
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Foundations: Python AI programming, REST APIs, Git/GitHub, prompt engineering, structured JSON outputs, and tool calling.
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LangChain & RAG: Custom AI chat interfaces, conversation memory, multimodal vision/speech, document chunking, hybrid search, and FastAPI REST endpoints.
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LangGraph & Multi-Agent: Stateful graph execution, parallel routing, Human-in-the-Loop (HITL) approval gates, Model Context Protocol (MCP) integrations, and supervisor-worker teams.
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Production & DevOps: Docker containerization, cloud deployment, LangSmith observability, LLM-as-judge evaluation, and latency/cost optimization.
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Hands-On Outcomes: 5 portfolio-ready projects culminating in a deployed, cloud-hosted production capstone.
Exclusive Bonus Career Workshops
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CV & LinkedIn Optimization for AI & Machine Learning Engineers
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GitHub & Portfolio Presentation to stand out to global recruiters
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Upwork & Fiverr Freelance Setup for high-value AI agency consulting
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Technical Interview Prep covering system design for LLM applications
