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6-month career track to become a Developers AI Expert

Ship production AI: agents, RAG systems, evaluations and deployment on real infrastructure.

₹24,999₹50,00050% OFF

Get 100% fees back as a reward if you complete the 6-month challenge.

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AI for Developers programme illustration

AI for Developers

Foundation → Professional → Master · ₹8 – 45 LPA

1:1

Live mentors

3+

Projects

3 levels

Certificate

Mentors live now

1-on-1 live doubt solving with expert mentors

Never stay stuck. Real practitioners join you on call, review your screen and unblock you the same evening.

Daily live doubt support

Mentors online 7 PM – 11 PM, every single day.

7 days / week

Instant doubt clearing

Audio + screen share sessions until it truly clicks.

< 5 min wait

Personalised guidance

Project reviews and 1:1 career mapping with your mentor.

1:1 sessions

Portfolio & CV building

Line-by-line help to make you recruiter-ready.

Recruiter-ready
Overview

Everything in this career track

Earning potential

₹8 – 45 LPA

Typical range for AI for Developers roles after completing all three levels and building a recruiter-ready portfolio.

Certification

Level-wise ACRY certificate

Commitment

6–8 hrs / week, self-paced

Tools you'll master

Hands-on with the exact AI stack hiring teams ask for in AI for Developers interviews.

PythonLangChainPyTorchFastAPIDocker

3 levels

Foundation → Master

100%

Project-based learning

Curriculum

Foundation Professional Master

One ladder, three levels. Each level ends with a shippable project, a certificate and a clear next step.

01

Foundation

AI fundamentals mapped to developers

Weeks 1-4 · 40 hrs 4 modules · 11 topics

01. How AI actually works

6 hrs
  • LLMs, tokens, context windows and hallucinations explained simply
  • Where AI genuinely helps in developers — and where it fails
  • Responsible use, data privacy and review checkpoints

02. Prompt engineering for Developers

10 hrs
  • Role, context, constraint and example-driven prompt frameworks
  • Reusable prompt library for recurring developers tasks
  • Chain-of-task prompting and output quality scoring

03. Core toolkit — Python, LangChain, PyTorch

12 hrs
  • Hands-on setup and real workflows in Python
  • Hands-on setup and real workflows in LangChain
  • Hands-on setup and real workflows in PyTorch

04. Foundation mini project

12 hrs
  • Build a starter version of the multi-agent assistant
  • Mentor review, rework and Foundation certificate

Level outcome: Confidently use AI copilots inside day-to-day developers work.

Most chosen02

Professional

Job-ready developers systems

Weeks 5-12 · 90 hrs 4 modules · 12 topics

01. Data, automation and workflow design

20 hrs
  • Map and automate the highest-value developers workflows
  • Connect FastAPI with APIs, Zapier / n8n style automation
  • Quality gates, human-in-the-loop and error handling

02. RAG, agents and custom copilots

24 hrs
  • Vector databases, retrieval and grounding on your own documents
  • Build a developers agent that completes multi-step tasks
  • Evaluation: accuracy, cost and latency tracking

03. Applied build — Enterprise RAG search

26 hrs
  • End-to-end build of the enterprise rag search
  • Deploy and monitor models
  • Weekly mentor code / work reviews

04. Portfolio, resume and interviews

20 hrs
  • Case-study style portfolio with before/after metrics
  • Resume and LinkedIn rewritten for AI Engineer roles
  • AI-scored mock interviews with feedback

Level outcome: Build RAG & agent systems

03

Master

Leadership, strategy and placement

Weeks 13-20 · 80 hrs 4 modules · 11 topics

01. Capstone — Vision QC system

30 hrs
  • Enterprise-scale build of the vision qc system
  • Architecture review, cost model and documentation
  • Live demo day in front of a mentor panel

02. AI strategy and team enablement

18 hrs
  • Build an AI adoption roadmap for a developers function
  • Governance, risk, vendor selection and ROI modelling
  • Train and lead a team on new AI workflows

03. Consulting and freelance practice

14 hrs
  • Scoping, proposals and pricing for AI projects
  • Client discovery calls and delivery playbook

04. Placement accelerator

18 hrs
  • Referrals and applications for AI Engineer, ML Engineer, LLM Application Developer
  • 1:1 career mapping, salary negotiation and offer review
  • Master certificate and lifetime alumni access

Level outcome: Master AI engineering patterns

Outcomes

What you walk away with

Skills, job titles and a portfolio — the three things a recruiter actually checks.

3 skills

Learning Outcomes

  • Build RAG & agent systems
  • Deploy and monitor models
  • Master AI engineering patterns
3 roles

Career Opportunities

  • AI Engineer
  • ML Engineer
  • LLM Application Developer
3 projects

Portfolio Projects

  • Multi-agent assistant
  • Enterprise RAG search
  • Vision QC system
Roadmap

Your 6-month AI for Developers roadmap

Six focused months — what you learn, what you build and what you can show at the end of every month.

6-Month Roadmap

AI for Developers — month 1 to month 6

6 phases · 1 month each
  1. Month 101

    AI foundations

    Understand AI and set up your developers toolkit

    • Career assessment and personalised roadmap
    • Prompt engineering fundamentals
    • Set up Python and LangChain

    Personal prompt library

  2. Month 202

    Applied tools

    Daily developers workflows run with AI

    • Automate 3 recurring developers tasks
    • Deep dive into PyTorch
    • Mini project #1 with mentor review

    Multi-agent assistant

  3. Month 303

    Systems build

    Data, automation and integrations

    • Connect tools with APIs and automation
    • Design quality checks and review loops
    • Weekly live doubt rooms

    Automated workflow with metrics

  4. Month 404

    AI agents & RAG

    Build an intelligent developers assistant

    • Vector database and retrieval on your own data
    • Multi-step agent with tool calling
    • Evaluate accuracy, cost and speed

    Enterprise RAG search

  5. Month 505

    Portfolio & proof

    Turn work into recruiter-ready evidence

    • Case-study portfolio with before/after numbers
    • Resume and LinkedIn rewrite
    • Deploy and document the capstone

    Vision QC system

  6. Month 606

    Interview & launch

    Land AI Engineer

    • AI-scored mock interviews and feedback
    • Referrals, applications and outreach plan
    • Salary negotiation and 30-60-90 day job plan

    Certificate + interview pipeline

Included

AI career services bundled free

AI Resume Builder

ATS-ready resumes tailored to each AI role.

AI Portfolio Builder

Turn projects into a recruiter-ready portfolio.

AI LinkedIn Optimizer

Positioning that attracts inbound recruiters.

AI Mock Interview

Realistic interviews with instant scoring.

AI Skill Gap Analysis

Know exactly what to learn next.

AI Career Roadmap

A personalised month-by-month plan.

Ready to start AI for Developers?

Join the 6-month challenge, build real projects and get placement support from day one.

Learner reviews

What learners say about AI for Developers

Verified reviews from learners who completed the AI for Developers track and moved into roles like AI Engineer.

Excellent

Rated 4.8 out of 5 based on 12 verified learner reviews for the AI for Developers programme.

Every review collected from enrolled learners after course completion

  • 5-star83%
  • 4-star17%
  • 3-star0%
  • 2-star0%
  • 1-star0%
23 June 2026

Intense, but the pace is honest

Be ready to put in real hours — the assignments are graded and you get sent back if the Enterprise RAG search does not work. I lost a weekend to it and learned more than a year of videos. Only wish the recordings were indexed better.

PN

Priya Nair

AI Engineer · Chandigarh

Verified
17 July 2025

Good fit for software engineers

I was worried it would be too engineering-heavy for my background. It was not. The concepts are taught through the actual work software engineers do, and the PyTorch module clicked immediately.

JM

Joseph Mathew

ML Engineer · Hyderabad

Verified
9 July 2026

Salary went up 80%

Two projects, one certificate and a much sharper way of explaining what I do with Python and LangChain. I negotiated with a number in my head for the first time and got it.

NR

Nandini Rao

Software Engineers · Mumbai

Verified
11 January 2025

Practical, not theoretical

Zero fluff slides. Every session ended with something in my repo. The Enterprise RAG search in particular is the closest thing to real production work I have done outside a job.

MY

Manish Yadav

AI Engineer · Ahmedabad

Verified
21 February 2025

Interview prep was brutally useful

The mock panel asked exactly the kind of questions I later faced for the AI Engineer interview — trade-offs, cost, failure modes. Walking in the second time felt like revision, not an exam.

NS

Neha Saxena

ML Engineer · Coimbatore

Verified
19 August 2025

Moved into AI Engineer

I was stuck doing the same reporting work for four years. The AI for Developers track gave me a portfolio, a story and enough LangChain depth to defend it. Offer letter for the AI Engineer role came in nine weeks after finishing.

AM

Abhinav Mishra

Software Engineers · Bhubaneswar

Verified

FAQs

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