SKILLURON · AI ENGINEERING WORK-SIMULATION PROGRAM
Don't Just Learn AI Engineering. Experience the Work of an AI Engineer.
Build practical AI applications through structured learning, hands-on projects, and engineering workflows that take you from an idea to a working application.
Learn on weekends. Build throughout the week. Experience an industry-style remote engineering workflow. Develop the skills to become industry-ready.
- Starts 12 Dec 2026
- Live: Sat & Sun, 8-11 PM
- Doubt clearing: Wed, 8-10 PM
- Python
- Machine Learning
- LLMs
- RAG
- AI Agents
- FastAPI
- Capstone
- Weekend Learning
- Weekly Engineering Assignments
- Simulated Remote Workflow
- Assessed Capstone
- Online + Kolkata Offline
- Career & Placement Support
Why Skilluron
What Makes This Program Different?
You do not just study AI concepts. You build applications and practise the workflow around them.
Practical AI application development
Build working applications with LLM APIs, RAG and tool-using workflows, not only exercises.
Structured weekly assignments
Weekend sessions teach the concepts. Weekly assignments, with requirements and acceptance criteria, apply them.
Software engineering workflows
Practise tickets, Git and GitHub, design, testing and documentation in a simulated remote environment.
Demonstrable projects
Leave with documented projects and an assessed capstone you can walk someone through.
Modern AI tools
Work with ChatGPT, Claude, Gemini, LangChain and LangGraph, and learn to review AI-generated code responsibly.
Explain, test and document
Evaluate AI output, test your application and explain your technical decisions.
YOUR SIMULATED REMOTE ENGINEERING ENVIRONMENT
Experience a Structured Engineering Workflow.
Each assignment moves from requirements to delivery, the way engineering work is typically organised on a remote team.
- 01
RECEIVE
Understand the problem, requirements, ticket, and acceptance criteria.
- 02
PLAN
Break work into tasks and identify dependencies.
- 03
DESIGN
Prepare architecture, data models, API contracts, HLD, and LLD as appropriate.
- 04
BUILD
Implement features, integrate APIs, and manage dependencies and environments.
- 05
COLLABORATE
Use Git branches, meaningful commits, pull requests, and review workflows where supported.
- 06
TEST
Debug failures, validate functionality, and evaluate AI outputs.
- 07
DOCUMENT
Update README files, setup instructions, technical documentation, and design records.
- 08
DELIVER
Demonstrate the result and explain technical decisions, limitations, and improvements.
Learn on weekends. Build through the week. Each weekly assignment follows this workflow.
This is a simulated learning environment. It is not employment, an internship, or live client work.
What You Will Learn and Build
From Engineering Foundations to Working AI Applications
Software Engineering Foundations
- Python application development
- Code organisation and maintainability
- Git and GitHub workflows
- Requirements, tickets and design (HLD and LLD)
AI Application Development
- Integrating large language models
- Prompt design and structured outputs
- Building AI-powered applications
- Working with external APIs
Retrieval and AI Workflows
- Retrieval-augmented generation (RAG)
- Embeddings and vector search
- Tool-using workflows and AI agents
- Connecting applications to data sources
Testing and Delivery
- Testing, debugging and AI output evaluation
- API development with FastAPI
- README, setup and architecture documentation
- Project demonstrations and technical explanation
- Python
- FastAPI
- Git
- GitHub
- ChatGPT
- Claude
- Gemini
- LangChain
- LangGraph
Also introduced as the cohort requires
BUILD WITH PURPOSE
Practical Projects. Demonstrable Skills.
Apply AI engineering concepts to high-stakes problem scenarios across finance, healthcare, legal and research. Progress from guided implementation to a capstone that you can demonstrate and explain.
AI Financial Analyst
Upload a company's annual report or earnings PDF, ask questions and get source-grounded answers, with an auto-generated summary and risk flags.
RAG · Citations · FastAPI
Clinical / Medical Report Assistant
Read sample lab reports or discharge summaries, explain them in plain language and flag values outside range, with safety guardrails and disclaimers.
Extraction · Guardrails · Validation
Legal Document Intelligence
Upload a contract to extract clauses, highlight risks, get a plain-English summary and check what is missing.
Structured Extraction · Validation · Human Review
Autonomous Research Agent
Give a topic and the agent plans, searches approved sources, calls tools and writes a cited report, with a human-review gate before it is finalised.
AI Agents · Tool Calling · Human Review
ILLUSTRATIVE ASSIGNMENT
One AI Project, Start to Finish: the AI Financial Analyst
Example tickets
What you hand in
Illustrative example of the workflow and its deliverables. Ticket names are examples, not student work.
Who It's For
Who Is This Program For?
Designed for aspiring AI engineers who want to move beyond theory and build practical AI-powered applications.
College Students
Students pursuing undergraduate or postgraduate degrees who want to develop practical AI skills, work on projects, and strengthen their technical portfolios.
Final-Year Students and Recent Graduates
Learners preparing for technology roles who want practical experience building AI-powered applications.
Working Professionals
Professionals looking to expand their technical skills or explore a transition towards AI engineering.
Python Developers
Developers who want to extend their existing programming knowledge into LLM-powered applications and modern AI workflows.
Basic programming knowledge is expected: variables, conditions, loops and functions in any language. Python is used throughout, and Phase 1 revisits it quickly. New to coding? Build the basics first, then join a later cohort. Python Developer course.
Curriculum
Four Phases. Sixteen Weeks. One Capstone.
Software-engineering foundations, then generative AI and LLM engineering, then AI application engineering, then project delivery and career preparation.
- 16 Weeks
- 4 Phases
- 11 Modules
- Hands-on Projects
- Capstone Defence
Program Modules
Module 01 of 11
Module 01
Python for AI Engineering
Phase 1 · Weeks 1–4
Write structured, readable Python and use the version-control habits every engineering team expects.
Software Engineering and AI Foundations
Core Topics
- Python programming and data structures
- Functions, modules, classes, and exceptions
- Virtual environments and dependency management
- Working with JSON and files
- Logging and debugging
- Type hints and readable code
- Git and GitHub fundamentals
Practical Outcome
Build a structured Python application with documented functions, error handling, version control, and basic tests.
Phase Assessment
Python assignment, API integration exercise, and machine-learning mini-project.
Want to Explore the Projects in Detail?
Discover the project requirements, expected deliverables, technologies, evaluation criteria, and the skills each project is designed to demonstrate.
The brochure includes
- Detailed project descriptions
- Requirements and features
- Technology stack
- Expected deliverables
- Skills demonstrated
- Assessment criteria
- Capstone requirements
- Curriculum details
- Certificate eligibility criteria
Program Details
Format, Assessment and Certificates
- Duration
- Four months: 16 weeks, 4 phases, 11 modules
- Format
- Weekend sessions plus weekly project assignments
- Delivery
- Online, or Kolkata offline (subject to batch availability)
- Certificates
- Skilluron-issued educational certificates, for learners who meet the criteria
Your weekly schedule
Saturday and Sunday
8 PM to 11 PM
Live classes
Concepts, demonstrations and guided implementation, online.
Monday to Friday
Daily stand-ups and scrum calls
Industry-style project work
Work on your assignment the way an engineering team does, with a daily check-in.
Every Wednesday
8 PM to 10 PM
Doubt-clearing sessions
Get unstuck with your mentor. Offline option subject to available slots.
How you are assessed
Phase assessments
A check at the end of each of the four phases.
Capstone
Marked on a 100-point rubric covering design, code, testing, documentation and your demonstration.
Mock interviews
Scheduled any time, based on your and the interviewer's availability, so you can retake to improve. At least 75% is needed for placement assistance.
Final portfolio
Your documented projects, with repositories, design documents and tests, reviewed at the end of the program.
Certificates
Program Completion Certificate
Awarded to learners who satisfy the published attendance, assessment, assignment, capstone, and completion requirements.
Applied AI Project Experience Certificate
Awarded to eligible learners who submit and successfully defend assessed project work. It records your capstone rubric result band.
Certificate requirements in detail
Program Completion Certificate
- Attend at least 75% of scheduled live sessions (unless an approved alternative is defined).
- Complete required assignments.
- Achieve at least 60% (proposed) of the total assessment score.
- Submit the required capstone.
- Meet all published academic and administrative requirements.
Identifies: The educational program and the completion date.
Applied AI Project Experience Certificate
- Submit an eligible project.
- Provide a working demonstration or reproducible implementation.
- Submit the GitHub repository or another approved evidence package.
- Provide project documentation.
- Explain the architecture and key implementation decisions.
- Pass a technical review.
- Submit documentation and testing evidence for your capstone.
Identifies: Project title, technologies used, project completion period, skills demonstrated, the nature of your contribution, and your capstone rubric result band.
An educational project-experience certificate. It is not an employment experience letter, client-work certificate, or internship certificate.
Score thresholds marked “proposed” are subject to final approval and will be confirmed before the cohort starts.
How your capstone is assessed (100-point rubric)
| Assessment area | Weight |
|---|---|
| Problem definition and requirements | 10 |
| Architecture and engineering decisions | 15 |
| Functional implementation | 20 |
| Code quality and maintainability | 10 |
| Testing and evaluation | 15 |
| Data handling and basic security | 10 |
| Deployment and reliability, where applicable | 5 |
| Documentation and reproducibility | 5 |
| Demonstration and technical defence | 10 |
| Total | 100 |
- Program completion: at least 60% (proposed) of the total assessment score, plus the other published requirements.
- Your capstone result on this rubric is recorded as a result band on the Applied AI Project Experience Certificate.
- A polished interface alone does not make a project technically successful. Functionality, testing and your ability to explain the system carry most of the marks.
CAREER GROWTH & PLACEMENT SUPPORT
Career Growth Starts With What You Can Build.
Build practical AI engineering skills, develop a portfolio of working applications, and prepare for career opportunities with Skilluron's career and placement support.
Career Preparation
Present your skills professionally, showcase your project work, and prepare to explain your technical decisions with confidence.
- Resume and LinkedIn optimization
- GitHub and portfolio review
- Technical interview preparation
- Mock interviews and project discussions
Placement Assistance
Get structured guidance to identify relevant opportunities, prepare applications, and navigate your career search.
- Guidance on relevant AI and technology roles
- Job-search and application support
- Career-readiness guidance
- Assistance navigating the application process
Hiring-Partner Interview Support
Explore relevant opportunities through Skilluron's hiring-partner network and receive support preparing for interview processes.
- Relevant opportunities shared through hiring partners
- Guidance preparing for partner-led interview processes
- Support presenting technical projects and skills
- Assistance navigating relevant interview opportunities
Placement-assistance terms
- Who is eligible
- Learners enrolled in the AI Engineer Program who have attended at least 75% of sessions, scored above 50% in assignments, scored at least 75% in mock interviews, and submitted the capstone. Mock interviews can be scheduled at any time, based on your and the interviewer's availability, so you can retake one to improve your score.
- What it includes
- The career preparation, placement assistance and hiring-partner interview support described above, provided as part of the program fee.
- Full placement assistance
- Skilluron provides full placement assistance through our hiring partners. Selection depends on your performance and the employer's decision.
- Hiring partners
- Opportunities are shared through Skilluron's hiring partners based on their requirements and openings at the time.
- How long support lasts
- Placement support is available for 12 months after the program ends, or until you are placed, whichever comes first.
- Your part
- Keep your resume, GitHub and portfolio up to date, take part in preparation sessions, and respond promptly to opportunities shared with you. We share your resume and project details with hiring partners only with your consent.
What's Included
Everything You Get in Both Options
Learn
Structured curriculum
16 weeks, 4 phases and 11 modules.
Live classes
Saturday and Sunday, 8 PM to 11 PM.
Class recordings
Recordings after every live class.
Build
Weekly project work
Assignments with daily stand-ups and scrum calls.
Doubt clearing
A session every Wednesday, 8 PM to 10 PM.
Strong professional portfolio
Documented projects with repositories and tests.
Grow
Assessed capstone
Plus mock interviews to practise.
Certificates
For learners who meet the criteria.
Career and placement support
Through our hiring partners, for 12 months.
Founding cohort · starts 12 December 2026
Choose How You Want to Learn
Both options follow the same core curriculum and learning outcomes.
Kolkata Offline
Skilluron Kolkata centre
₹39,999
Includes everything listed above.
Subject to confirmed batch availability
Transparent terms
Fees and policies
Registration fee
The program fee includes a ₹10,000 registration fee. This portion is non-refundable.
Instalments and EMI
EMI is available through the options offered on Razorpay at checkout. Availability depends on your card or bank.
Refunds
A refund can be requested within 30 calendar days of enrolment. The ₹10,000 registration fee is not refundable, so the most you can get back is ₹19,999 on the Online fee and ₹29,999 on the Offline fee. Full terms are in the Refund Policy.
Free demo class first, no payment required to start. Offline delivery is subject to confirmed batch availability.
Read the full Refund PolicyFAQs
Frequently Asked Questions
Everything you want to know before booking your free demo.
FOUNDING COHORT · STARTS 12 DECEMBER 2026
Ready to Build Your First AI-Powered Application?
Explore the program, understand the learning approach, and find out whether it fits your goals.
Free Demo + Counselling
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+ Get a Personal Learning Plan
Tell us a little about yourself and a counsellor will get in touch to schedule your demo and answer questions about the founding cohort starting 12 December 2026. No payment, no commitment.
- Free counselling call
- Free live demo class, no payment
- Online or Offline — Kolkata Centre
- WhatsApp support
- Basic programming knowledge expected
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