← All programmesStart with curiosity.
FDE FOR FRESHERS / CORE PROGRAMME
Start with curiosity.
Learn to ship.
FDE for Freshers
Your first engineering role starts with the foundations. Build Python, APIs, cloud and AI skills, then practise the client conversations that turn a working system into a useful delivery.
FDE for Freshers · No coding background needed
YOUR FIRST DELIVERY JOURNEYEXPLORE ↓
Build your engineering foundation.
Start with Python, Git and the command line. Learn to test your work and explain it in a clear README.
YOU BUILDTested Python CLI tool
Illustrative learning workflow · Select a stage to explore
6–7 months
Programme duration
7
Learning phases
Live
Practitioner-led learning
Build
Projects & capstone
A STARTING POINT THAT FITS YOU
Bring your curiosity. Build your capability.
Build your engineering foundations, then take AI from discovery to delivery.
Early-career professionals (0–2 yrs) — in QA, support, testing or non-dev roles moving into AI engineering.
Plan my starting point ↗Freshers who want more than a 'course' — a client-facing, build-and-ship engineering career in AI.
Plan my starting point ↗NeuraPath DS / GenAI learners — who want the capstone tier that makes them client-ready.
Plan my starting point ↗THE CAPABILITIES YOU DEVELOP
Write clean, tested, production-quality Python — starting from absolutely zero.Use the professional toolkit daily: Git/GitHub, Linux/CLI, VS Code, AI coding copilots (validated, never blind).Query and model data with advanced SQL, and integrate files, databases and SaaS/enterprise APIs.Build and secure real APIs with FastAPI — auth, webhooks, background jobs.Ship software the industry way: pytest, CI/CD with GitHub Actions, Docker, cloud deployment & monitoring.Build production LLM systems: structured outputs, RAG pipelines with evals, agents, tool-use and MCP servers.Guardrail, secure and observe AI systems — OWASP LLM Top-10, PII handling, LangSmith/Langfuse.Run client discovery, manage stakeholders and deliver demos that win — the consulting craft no fresher course teaches.Graduate with a deployed FDE capstone engagement and a portfolio that reads like work experience.
Already experienced in IT and comfortable with coding, APIs and deployment? Explore the accelerated FDE for Professionals pathway →
YOUR LEARNING JOURNEY
Seven phases. Your first complete delivery.
Start at software foundations and build toward cloud, AI and client delivery across approximately 30 weeks. Each phase adds a portfolio artefact.
MODULE 01 / 0760 learning hours
Software Engineering Foundations
WHAT YOU WILL EXPLORE- The FDE Landscape & Mindset
- Python — Zero to Engineer
- The Professional Toolkit
- Problem Solving & Core CS
THE WORK YOU BUILD
Build, test and publish a real Python CLI tool to GitHub — with a README, tests and a code-reviewed PR workflow.
MODULE 02 / 0748 learning hours
Data, SQL & APIs — the Integration Core
WHAT YOU WILL EXPLORE- SQL & Databases
- Building & Consuming APIs
- Data Wrangling & Integration Pipelines
THE WORK YOU BUILD
Build an integration service that pulls from a database + a live third-party API, cleans and joins the data, and serves it through your own FastAPI endpoint with a Streamlit dashboard.
MODULE 03 / 0740 learning hours
Production Engineering & Cloud
WHAT YOU WILL EXPLORE- Testing, Quality & CI/CD
- Docker & Deployment
- Cloud Fundamentals
THE WORK YOU BUILD
Containerise your Phase-2 integration service, add a full CI/CD pipeline, deploy it to the cloud, and wire up monitoring — a live URL you can put on your resume.
MODULE 04 / 0744 learning hours
Applied ML & GenAI Foundations
WHAT YOU WILL EXPLORE- ML & AI Literacy for FDEs
- LLM Fundamentals & APIs
- Prompt & Context Engineering
- Production RAG
THE WORK YOU BUILD
Build a production RAG assistant over a real enterprise document set — chunking, vector DB, reranking, a RAGAS evaluation suite and a clean demo UI.
MODULE 05 / 0736 learning hours
Agentic AI, MCP & LLMOps
WHAT YOU WILL EXPLORE- Agents, Tools & MCP
- Evals, Guardrails & Security
- Deploying & Observing AI Systems
THE WORK YOU BUILD
Ship a deployed agent system: an MCP server exposing internal tools + a LangGraph agent that uses it — with guardrails, an eval suite and observability dashboards.
MODULE 06 / 0722 learning hours
The Consulting & Client-Facing Craft
WHAT YOU WILL EXPLORE- Discovery, Scoping & Stakeholders
- Demos, Communication & Client Environments
THE WORK YOU BUILD
Live roleplay: run a mock discovery session and deliver a winning demo, with your mentor playing a difficult enterprise client — recorded, reviewed and re-run until it's strong.
MODULE 07 / 0730 learning hours
Capstone Engagement & Career Launch
WHAT YOU WILL EXPLORE- The Full FDE Capstone
- Interviews & Career Launch
THE WORK YOU BUILD
Capstone: run a full FDE engagement end-to-end for a fictional enterprise client — the single strongest artefact a fresher can show a hiring manager.
MAKE ROOM FOR THE PRACTICE
Project-first learning across approximately 30 weeks; 9–12 hours per week
Discuss the schedule →YOUR WORKING TOOLKIT
Python (zero → production), Git & GitHub, Linux/CLI, VS Code, typing & packagingGitHub Copilot / Claude / Cursor — AI-assisted engineering, with validation disciplineSQL (PostgreSQL, MySQL), MongoDB (intro), pandas, ETL basics, REST & SaaS APIsFastAPI, Pydantic, auth (API keys/OAuth/JWT), webhooks, task queues (intro)OpenAI & Anthropic APIs, RAG (vector DBs, reranking, RAGAS), LangGraph, MCP serverspytest, GitHub Actions (CI/CD), Docker, AWS/GCP basics, monitoring & loggingArchitecture diagrams, scoping docs, Streamlit demo UIs, security & compliance basicsDiscovery, requirements, stakeholder mapping, technical writing, demos
BUILD AS YOU LEARN
A portfolio with a story behind every piece.
Explore the work attached to each module. Follow the progression from your first exercise to the final capstone.
PROJECT MILESTONE 01
Software Engineering Foundations
Build, test and publish a real Python CLI tool to GitHub — with a README, tests and a code-reviewed PR workflow.
CURRICULUM PROJECT / LEARNING ARTEFACT- 01Understand
- 02Build
- 03Review
- 04Explain
CONNECT THE LEARNING TO THE WORK
The FDE Landscape & Mindset; Python — Zero to Engineer; The Professional Toolkit; Problem Solving & Core CS
MAKE YOUR WORK EASY TO DISCUSS
What question did you start with? What did you build? Explain one decision, one limitation and what you would improve next.
YOUR PROGRAMME PORTFOLIO
- Build, test and publish a real Python CLI tool to GitHub — with a README, tests and a code-reviewed PR workflow.
- Build an integration service that pulls from a database + a live third-party API, cleans and joins the data, and serves it through your own FastAPI endpoint with a Streamlit dashboard.
- Containerise your Phase-2 integration service, add a full CI/CD pipeline, deploy it to the cloud, and wire up monitoring — a live URL you can put on your resume.
- Build a production RAG assistant over a real enterprise document set — chunking, vector DB, reranking, a RAGAS evaluation suite and a clean demo UI.
- Ship a deployed agent system: an MCP server exposing internal tools + a LangGraph agent that uses it — with guardrails, an eval suite and observability dashboards.
- Live roleplay: run a mock discovery session and deliver a winning demo, with your mentor playing a difficult enterprise client — recorded, reviewed and re-run until it's strong.
- Capstone: run a full FDE engagement end-to-end for a fictional enterprise client — the single strongest artefact a fresher can show a hiring manager.
WHAT THE WORK ADDS UP TO
Learn it. Build it. Explain it.
Build like an engineer
Practise Python, version control, testing and code review from the start.
Connect and deploy
Integrate data and APIs, then add containers, CI/CD and cloud deployment.
Engineer useful AI
Build RAG and agent systems with tools, evaluations and guardrails.
Deliver to a client
Practise discovery, scoping, demonstrations and a full engagement simulation.
CAPABILITY DIRECTIONS
Forward Deployed EngineerAI Solutions EngineerJunior AI Engineer
These roles describe directions the curriculum supports. They are not a guaranteed job title, employer or salary.
PLAN YOUR STARTING POINT
Turn your interest into a learning plan.
Select what describes you today. Use it to prepare for a conversation about the course, your goals and the time you can commit.
0 / 4
Select the statements that fit. You can still enquire with any number selected.
This pathway starts from zero coding experience. Already comfortable building and operating services? Explore FDE for Professionals for the accelerated route.
Instructors
Taught by practitioners, not presenters
Both instructors hold full-time senior data science roles. You are learning from people who ship this work every week.
PK
Pankit Kumar
Lead Instructor
Sr. Data Scientist, Parexel (a Goldman Sachs–backed company)
10 years in Data Science & AI, building and shipping production systems in regulated pharma/clinical environments. Freelance trainer at BIA, AnalytixLabs and Scaler — he has taught this material to thousands of working professionals.
Data ScienceMLOpsClient deliveryTeaching
IS
Ishaan Sharma
Co-Instructor — AI / GenAI
Senior Data Scientist, Nuvo AI (Meril Group)
Close to a decade across NLP, computer vision and Generative AI. Microsoft Azure ML Scholar. Works on production AI systems in medical devices and healthcare, and leads the agentic-AI and MCP modules.
GenAINLP / CVAgents & MCPLLMOps
BEFORE YOU ENROL
A clear picture of your next step.
Understand the starting point, learning format and portfolio before choosing your programme.
Do I need previous IT experience?
No. This pathway begins with coding and software-engineering foundations.
What will I build?
Python tools, an integration API, a deployed cloud service, retrieval and agent systems, and an end-to-end simulated client engagement.
How is it different from FDE for Professionals?
The professional pathway assumes engineering and AI fundamentals, then concentrates on advanced enterprise delivery in a proposed 16-week schedule.
Does this guarantee an FDE job?
No. Roles describe the capabilities you practise; hiring depends on your portfolio, interviews and employer requirements.
Read the full FDE for Freshers guide +
From foundations to client-facing AI delivery
FDE for Freshers follows the existing ground-up pathway: Python and the professional toolkit, data and APIs, production engineering and cloud, applied ML and GenAI, agents and MCP, consulting craft, and a complete client-simulation capstone.
Plan for approximately 30 weeks (6–7 months), with regular practice and project work. No prior work experience is required. You build, test and deploy services before taking on the client-facing parts of the role.
Not ready to commit? Read our complete Forward Deployed Engineer guide first — what the role involves day to day, what it pays in India, how to get there from where you are, and how it differs from data-science and ML-engineering careers.
CONTINUE EXPLORING
Forward Deployed Engineer Salary in India: Job-Posting Evidence and Offer Comparison
Two live employer disclosures show why one FDE salary band is misleading. Learn how to compare the role, pay basis and offer components.
Read the guide · 4 min ↗How to Become a Forward Deployed Engineer: A Roadmap Built Around Evidence
A learning sequence with observable outputs, failure tests and a portfolio walkthrough, for beginners and engineers moving into customer delivery.
Read the guide · 4 min ↗What Is a Forward Deployed Engineer? Responsibilities, Skills and Examples
What FDE work looks like, how responsibilities vary, and a practical way to inspect the engineering behind customer delivery.
Read the guide · 4 min ↗Is Forward Deployed Engineering a Good Career? Fit, Tradeoffs and Questions to Ask
A realistic way to evaluate the role, including the work you may enjoy, the pressures to investigate and the evidence to build before committing.
Read the guide · 4 min ↗YOUR NEXT STEP / FDE FOR FRESHERS
Start with curiosity.
Learn to ship.
Get the detailed syllabus and talk through your starting point, weekly schedule and the work you want to build.
6–7 monthsLive practitioner learningFees shared on a call
Compare all programmes →