AI Engineering
Become a job-ready professional in 5 months — offline bootcamp in Indore.
duration
5 months
hours/lessons
260 hours · 80 lessons
mode
Offline bootcamp, Indore (hybrid support)
language
English (Hindi support)
certificate
Yes, on completion
fees
Enquire for fees
// 01 — what_you_learn
What you'll learn
- Explain how LLMs work: transformers, tokens, context windows
- Engineer prompts and evaluate outputs systematically
- Build RAG pipelines with embeddings and vector databases
- Fine-tune and compare open vs closed models on cost/quality
- Build GenAI apps with Python, FastAPI and Next.js frontends
- Add guardrails: safety filters, PII handling, rate limits
- Deploy AI apps with Docker and cloud basics
- Present an AI portfolio that passes technical interviews
// 02 — full_syllabus
Full syllabus
Complete module-by-module syllabus with every lesson taught in class.
M1Module 1 — Python & ML foundations (Weeks 1–4)
- 01Python for AI: data structures, functions, OOP
- 02NumPy and pandas for data handling
- 03Statistics refresher: distributions, correlation, evaluation
- 04Classical ML map: regression, classification, clustering
- 05Scikit-learn end-to-end mini project
- 06Jupyter workflows and experiment tracking
- 07Git for ML projects
- 08Mini project: churn prediction notebook
M2Module 2 — LLM fundamentals (Weeks 5–8)
- 01Transformer intuition without heavy maths
- 02Tokens, embeddings, context windows
- 03Prompt patterns: zero/few-shot, chain-of-thought, structured output
- 04Function calling and tool use
- 05Evaluation: accuracy, faithfulness, latency, cost
- 06Playground vs API: versioning and reproducibility
- 07Project: prompt-evaluation harness
M3Module 3 — RAG & knowledge apps (Weeks 9–12)
- 01Chunking strategies for documents
- 02Embeddings and vector stores (pgvector/Qdrant concepts)
- 03Retrieval tuning: top-k, hybrid search, reranking
- 04Citation and faithfulness checks
- 05FastAPI backend for a docs Q&A service
- 06Next.js chat UI with streaming
- 07Project: company-docs assistant with citations
M4Module 4 — Agents & fine-tuning intro (Weeks 13–16)
- 01When to fine-tune vs prompt vs RAG
- 02Dataset preparation and quality checks
- 03LoRA/PEFT concepts and cost awareness
- 04Agent loops: plan, act, observe
- 05Tool design: safe, typed, testable tools
- 06Human-in-the-loop and approvals
- 07Project: research agent with guarded tools
M5Module 5 — Shipping & MLOps basics (Weeks 17–20)
- 01Docker for AI apps
- 02Env, secrets and model-key safety
- 03Logging, tracing and cost dashboards
- 04Caching and batching to control bills
- 05Evals in CI: regression tests for prompts
- 06Deployment walkthrough on cloud/Vercel
- 07Capstone build weeks
- 08Career: AI portfolio reviews and mocks
// 03 — capstones
Capstone projects
Docs Q&A Assistant with Citations
RAG app over real documentation with chunking experiments, eval scores and streaming UI.
Prompt Evaluation Harness
Repeatable test suite comparing prompts and models on quality, latency and cost.
Guarded Research Agent
Tool-using agent with approvals, logging and budget caps.
AI Interview Coach
Role-play interviewer with structured feedback and progress tracking.
// 04 — fit_check
Who this is for
- Developers moving into AI roles
- Data science students who want applied LLM skills
- Working professionals building AI features at work
- Final-year students targeting AI engineer openings
Prerequisites
Basic Python helps but is not required — Module 1 covers it. Comfort with English documentation is needed.
// 05 — deep_dive
Course details
Become a job-ready AI engineer in 5 months
The AI Engineering course at Coding Guru, Indore, teaches you to build production-style LLM applications — not just chat with models, but retrieve knowledge, call tools, evaluate quality and deploy safely.
You will work in Python and JavaScript, build RAG systems over real documents, design guarded agents and learn the cost, latency and safety trade-offs that interviewers probe for. Small classroom batches mean your prompts, evals and architectures get reviewed by a mentor line by line.
Why AI engineering now
Indian product and services companies are hiring engineers who can ship GenAI features: docs assistants, support copilots, extraction pipelines and internal tools. This course focuses on exactly that applied layer — APIs, retrieval, evaluation and deployment — while giving you enough ML foundation to talk confidently in interviews.
How you will learn
Classroom sessions plus long lab hours. You will maintain an experiment log, publish eval scores for your RAG app and demo monthly. The capstone is a deployed AI app with cost tracking and guardrails — the artefact hiring managers actually open.
Career support
Portfolio reviews, AI-focused mock interviews, resume teardowns and placement drives. {{TESTIMONIAL_AIENG_1}} {{PLACEMENT_STATS}}
// 06 — faq
Frequently asked questions
What is the fee of the AI engineer course in Indore?
Fees depend on batch timing and payment plan. Contact us for the current fee — we share the complete structure in writing with no hidden charges.
Is placement provided after the AI engineering course?
Yes, placement support is included: portfolio reviews, mock interviews and referral drives. Hiring depends on your project depth and interview performance.
Is the course online or offline?
Offline classroom bootcamp in Indore with mentor-led labs. Hybrid doubt support is available.
Who is eligible for the AI engineer course?
Students and professionals with basic programming comfort. Python is taught from the start, so motivated beginners can join after a counselling demo.
Do I get a certificate?
Yes, on completing the syllabus, projects and assessments you receive a course-completion certificate.
What job roles follow this course?
AI engineer, LLM application developer, GenAI developer, ML engineer (junior) and AI solutions associate roles.
What salary can AI engineers expect?
Compensation varies widely by city, company and skill proof. We do not promise fixed packages; mentors share current market ranges during counselling.
Do I need prior coding experience?
Basic coding comfort helps. Module 1 rebuilds Python foundations, and mentors give extra lab time to beginners.
// 07 — enquire
Book a free demo class
Seats per batch are limited. Get a callback from our Indore counsellor.
$ ./book_demo --free
Start your coding journey
Visit our Indore classroom, meet the mentors, get honest career guidance.
Book Free Demo> course: ai-engineering > duration: 5 months > fees: Enquire for fees > next batch: October 2026_
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