Data Science & AI
AI Engineer Bootcamp
A 288-hour live bootcamp on engineering, evaluating, deploying and scaling AI applications
- Duration
- 288 hours
- Format
- Live online
- Modules
- 10 modules
- Certificate
- On completion
- ✓288 hours of live online instructor-led training in scheduled batches
- ✓Python engineering, machine learning and deep learning foundations
- ✓LLM applications: prompting, RAG, tool use and multi-step agents
- ✓Evaluation, guardrails, observability and cost control for AI systems
- ✓Deployment with APIs, containers and cloud services; MLOps and LLMOps basics
- ✓Assure Success course-completion certificate after reviewed projects and capstone
About the course
What this course covers
The AI Engineer Bootcamp is aimed at people who want to build and run AI-powered software, not only train models in notebooks. It treats AI engineering as software engineering plus applied machine learning: clean code, testing, APIs, data pipelines, evaluation and monitoring all matter as much as model choice.
The programme starts with Python engineering practice and the machine learning and deep learning concepts you need to reason about models. It then moves to the modern application layer: working with LLM APIs and open models, structured outputs, embeddings and vector search, retrieval-augmented generation, tool calling and agent workflows. A large part of the course is about what goes wrong in production, such as hallucinations, prompt injection, latency, cost and drift, and how to evaluate and monitor systems systematically.
There is no external exam. You complete several projects and a capstone, and receive an Assure Success course-completion certificate. We do not promise jobs or placements.
Who should attend
- ● Software developers who want to build AI features and products
- ● Data scientists who want to move from notebooks to deployed systems
- ● Backend and cloud engineers moving into AI engineering roles
- ● Graduates with programming skills targeting applied AI careers
- ● Technical team leads responsible for delivering AI projects
Prerequisites
- Working programming skills, preferably in Python
Key skills
Skills you will walk away with
Production Python
Write typed, tested, packaged Python and use Git, Docker and CI practices.
Machine learning and deep learning
Understand and apply core models, and fine-tune pretrained networks.
LLM application development
Build features with LLM APIs, structured outputs and prompt design.
Retrieval-augmented generation
Chunk, embed, index and retrieve documents, and measure retrieval quality.
Agents and tool use
Design multi-step workflows where models call tools, with limits and human checkpoints.
Evaluation and guardrails
Create test sets, automated and human evaluation, and safety checks.
Curriculum
Module-by-module syllabus
10 modules · 44 topics · 288 hours
1Module 1: Python Engineering, Data and APIs6 topics ▾
Learning objective: Write maintainable code and work with data services.
- ▸ Advanced Python and typing
- ▸ Testing with pytest
- ▸ Git workflows and code review
- ▸ SQL and NoSQL basics
- ▸ REST APIs with FastAPI
- ▸ Authentication and rate limits
2Module 2: Machine Learning Foundations4 topics ▾
Learning objective: Understand core ML.
Schedules
Upcoming live batches
Enroll now and choose your batch dates
Send an enquiry and we'll reserve your seat in the next batch.
Certification
How you get certified
- 1Enrol in a scheduled live batch and receive the learning plan and tool list
- 2Attend sessions and submit the module assignments
- 3Complete the reviewed projects and the capstone
- 4Meet the attendance and assessment criteria stated for the bootcamp
- 5Receive your Assure Success course-completion certificate
Career outcomes
Roles this opens up
AI Engineer
₹8–22 LPA (approx.)Builds and maintains AI-powered features and services.
Machine Learning Engineer
₹8–22 LPA (approx.)Trains, deploys and monitors models in production.
LLM / GenAI Application Developer
₹7–20 LPA (approx.)Implements RAG, agents and assistant features for products.
MLOps Engineer (junior)
₹7–18 LPA (approx.)Automates deployment, testing and monitoring for ML systems.
Salary ranges are approximate figures for India and vary by city, company and experience.
Why this certification is worth it
Engineering focus
Goes beyond demos to testing, deployment and operations.
Modern AI stack
Why Assure Success
Learn it once, pass it once
Trainers from the field
Every session is led by a practitioner who uses this material at work.
Batches that fit your week
Weekday and weekend batches in IST, scheduled for working professionals.
Exam-style practice
Practice questions and, where available, a full simulator free with the course.
Exam voucher help
Discounted vouchers and step-by-step help booking your exam.
Human support
WhatsApp support Mon–Sat, 9 AM–8 PM IST — a person answers.
Pay your way
UPI, cards, netbanking and EMI in India; international cards accepted.
FAQs
Questions learners ask us
Q.How is this different from the Data Science with AI Bootcamp?
That bootcamp is broader and starts from zero, with data analysis and BI. This one assumes you can program and concentrates on building, evaluating and deploying AI systems.
Q.Do I need to know machine learning already?
No, but you need programming ability. Machine learning and deep learning foundations are covered in the first modules.
Q.Will I pay for LLM API usage?
Many labs use free tiers or open-source models. If a project needs paid credits, the coordinator will say so before the batch starts.
Q.Is there an external exam?
No. You receive an Assure Success course-completion certificate.
Q.Will you teach a specific agent framework?
We use current popular libraries in labs, but the focus is on principles such as tool design, state, evaluation and safety, because libraries change quickly.
Q.Does it include a job guarantee?
No. We cannot guarantee jobs. You build projects and receive interview preparation.
Can a fresher without projects join?
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₹42,999
AI Engineer Bootcamp