Learn from a leader with 11+ years of experience in Generative AI, Agentic AI, and real-world AI system development.
Expertise in building and deploying Generative AI solutions using LLMs, from prompt engineering to production-ready systems.
Specialized in designing autonomous and semi-autonomous AI agents for decision-making, orchestration, and automation.
Strong foundation in AI, ML, NLP, system design, and scalable architectures using Python and cloud platforms.
Leads end-to-end development of enterprise GenAI products, including chatbots, AI copilots, intelligent search, and real-world AI applications.
Whether you’re a student, fresher, or working professional, our Generative AI & Agentic AI training equips you with real-world AI skills
and the confidence to design, build, and deploy intelligent systems that make you truly job-ready.
Our structured syllabus takes you from AI fundamentals to building real-world Generative & Agentic AI applications. Each module includes
hands-on labs, model fine-tuning exercises, agent workflows, capstone projects, and assessments to ensure practical mastery.
Installing Python (pyenv/conda)
VS Code + extensions setup
Git & GitHub basics
Python package management (pip, requirements.txt)
Installing AI frameworks (PyTorch / TensorFlow)
Introduction to Azure Portal & Azure AI services setup
Using CLI tools (curl, wget)
Python core concepts for AI & automation
Data types, control flow, functions, generators
OOP, dataclasses & pydantic models
File handling, JSON/YAML, logging
Type hints, mypy & clean coding practices
Async programming with asyncio & aiohttp
Essential DS & algorithms for scalable AI apps
Big-O analysis & performance optimization
REST API design using FastAPI
Caching strategies with Redis
Database basics (PostgreSQL, SQLAlchemy)
Cloud system design fundamentals on Azure
Data wrangling with pandas & exploratory analysis
Machine learning pipelines using scikit-learn
Model evaluation, metrics & validation
Deep learning fundamentals (PyTorch / TensorFlow)
Experiment tracking with MLflow
Reproducible ML workflows
Core GenAI concepts: transformers & tokenization
Prompt engineering & evaluation strategies
Azure OpenAI & Azure AI Foundry setup
Embeddings & vector databases (AI Search / FAISS)
End-to-end RAG pipeline development
Content safety, guardrails & responsible AI
Fine-tuning LLMs using LoRA / PEFT
Prompt tuning vs fine-tuning comparison
Latency & throughput optimization techniques
Cost monitoring & token optimization
Streaming & batching responses
Performance evaluation & benchmarking
Agent concepts: planning, tools & memory
Building agents using LangChain & LlamaIndex
Multi-agent systems with AutoGen
Tool calling & function execution
ong-term memory with vector stores
Agent safety, human-in-the-loop & governance
Deploying GenAI apps using FastAPI & Docker
CI/CD pipelines with GitHub Actions / Azure DevOps
Infrastructure as Code (Bicep / Terraform)
Monitoring, logging & observability
Production-ready RAG or Agentic AI system
Capstone project with real-world use cases
LangChain
AutoGenI
Python - fast/flask api/ pedantic models
OpenAI API & Azure
Azure Open AI
PromptGuard & AI Safety
Every learner who successfully completes the training program at AimNxt receives an official Course Completion Certificate. Our certificate validates your practical skills, hands-on project experience, and industry-ready knowledge, making your resume stand out during interviews.
Complete our Generative AI & Agentic AI Course and become industry-ready for the fastest-growing AI careers. Master Python, Prompt Engineering, Azure OpenAI, Azure AI Foundry, LangChain, LlamaIndex, AutoGen, Retrieval-Augmented Generation (RAG), Fine-Tuning, FastAPI, Docker, MLOps and Production AI deployment through hands-on enterprise projects.
Find answers to common questions about our Generative AI & Agentic AI training program, certification, and career opportunities.
