InnoChase Training Program

Generative AI + Agentic AI Production-Focused Program

A 1-month intensive program designed to help learners build real-world AI solutions using Prompt Engineering, Retrieval-Augmented Generation, Agentic AI workflows, APIs, and deployment practices aligned to current market demand.

4 Weeks
Fast-track bootcamp structure
20 Days
Daily hands-on learning path
100% Applied
Built for production readiness
Program Snapshot

Production-focused and job-oriented

No traditional ML or data modeling detours

Built around real hiring, workflow, and automation use cases

Includes hands-on projects every week

Covers Prompt Engineering, RAG, Agentic AI, APIs, and deployment

Why this program

Built for the skills employers are hired for

This program is designed for organizations and professionals who want practical Generative AI capability without spending months on academic detours. The curriculum concentrates on the technologies and workflows that matter.

Prompt Engineering
Design reliable prompts, structured outputs, and domain-specific instructions.
RAG Pipelines
Ground AI responses with private data using vector search and retrieval workflows.
Agentic AI
Build autonomous agents that reason, call tools, and complete multi-step tasks.
Production Delivery
Integrate with APIs, package with Docker, and deploy usable AI systems.

Who should attend

Ideal for technical teams and future AI builders

Software developers
Technical recruiters and solution consultants
IT professionals transitioning into GenAI
Teams building AI-powered enterprise products

Curriculum Overview

A focused 4-week curriculum with real deliverables

Each week concentrates on one major capability so learners move from foundational understanding to working applications quickly.

Week 1

Foundations + Prompt Engineering

Intensive
LLM fundamentals, tokens, context windows, APIs
Zero-shot, few-shot, and role-based prompting
Structured outputs and recruiter-focused prompt design
Mini project: AI-Powered Content Summarizer
Week 2

RAG Pipelines

Intensive
Embeddings and semantic search
Vector databases such as Chroma and Pinecone
Retrieval-Augmented Generation architecture
Mini project: Document Q&A Chatbot
Week 3

Agentic AI

Intensive
Agents vs workflows orchestration patterns
Tool calling and function calling capabilities
LangGraph-based orchestration frameworks
Mini project: Autonomous Research Assistant Agent
Week 4

Backend + Deployment

Intensive
FastAPI integration for GenAI applications
Docker, deployment, monitoring, and scaling
Production-ready architecture mindset
Capstone: Deployed AI Knowledge Assistant

Learning Outcomes

What participants will be able to build

Build prompt-driven AI applications
Create RAG pipelines using vector databases
Develop autonomous agent workflows
Expose GenAI capabilities through APIs
Deploy usable production AI solutions

Capstone Focus

Build a Deployed AI Knowledge Assistant

The final project unifies the entire curriculum into one production-ready application — a fully deployed AI assistant that ingests documents, reasons over them, and responds intelligently via a live API.

Document upload and text ingestion pipeline
Vector embedding and semantic indexing
RAG-powered question answering engine
Agentic reasoning with tool-calling support
FastAPI backend with live REST endpoints
Containerised and deployed via Docker

Program Format

From prompt to production in just 30 days

This training page can be used for corporate learning, recruitment upskilling, or product-oriented AI enablement. It is especially suitable for companies building practical AI solutions.

Interested in this training program?

Add your inquiry form, scheduling widget, or call-to-action here for admissions, corporate batches, or private team training.