Faculty Development Program
Train the people who train the next ten thousand engineers.
Hands-on AI faculty development programs (FDP) for universities and colleges — generative AI, RAG, and agentic systems, taught lab-first, online or on campus.
- FDP
- Universities
- Train the trainer
- On campus
- Online
What this is
Most AI faculty training stops at slides. Ours ends with every participant having built and broken a working system: a retrieval pipeline, an agent with tools, and an evaluation harness that catches regressions. Faculty leave with the teaching assets too — notebooks, lab guides, rubrics, and question banks they can run the following semester without us.
Who it is for
- Engineering colleges and technical universities
- Polytechnics and autonomous institutions
- University departments launching an AI or data science program
- Corporate L&D academies and internal universities
- Government skilling missions and state technical boards
Formats
Pick the shape that fits.
One-week FDP
30 hours · 5 days
Theory in the morning block, supervised lab in the afternoon. Ends with a working RAG service per participant.
Two-week FDP
60 hours · 10 days
Adds agents, evaluation, and deployment, plus a curriculum clinic where we map the content onto your syllabus.
Train-the-trainer intensive
3 days · small cohort
For the four or five faculty who will own the subject. Each of them teaches a module back to the room and gets critiqued.
Semester mentoring
12 weeks · fortnightly
Your faculty run the course; we hold fortnightly clinics on what broke, review assessments, and unblock labs.
Curriculum
What gets covered.
- 01
Tooling and Python for AI teaching
The environment the whole program runs on — Colab, uv, API keys, and a lab setup that survives a campus network.
- 02
LLM fundamentals without the hand-waving
Tokens, context windows, sampling, and cost — explained so faculty can answer the questions students actually ask.
- 03
Prompt and context engineering
Structured output, few-shot patterns, prompt injection as a security topic, and context as an engineering surface.
- 04
Embeddings, vector search, and RAG
A full retrieval pipeline built in the lab, then deliberately broken at each stage so the failure modes are visible.
- 05
Agents, tools, and MCP
The reasoning loop from scratch before any framework, then LangGraph and Model Context Protocol servers.
- 06
Evaluation and responsible AI
Retrieval metrics, task success, LLM-as-judge and its limits, plus bias, privacy, and disclosure in student work.
- 07
The teaching lab
How to sequence this for a semester: assessment design, project briefs, viva questions, and what to cut.
- 08
Research and publication clinic
Turning lab work into a paper — problem selection, baselines, reproducibility, and where to submit.
Outcomes
What changes afterwards
- Every participant ships a retrieval-augmented application and an agent that uses tools
- Faculty can set and grade AI assignments that cannot be completed by pasting a prompt
- A semester plan mapped onto your existing syllabus and credit structure
- An internal cohort able to run the next FDP without external help
- Lab infrastructure that works on your campus network and budget
Deliverables
What you keep
- Editable slide decks for every module
- Colab-ready notebooks and starter repositories
- Lab guides with expected output and common failure notes
- Assessment rubrics, question banks, and viva prompts
- Capstone project briefs at three difficulty levels
- Session recordings for internal reuse
- Participation certificates for every attendee
- A syllabus mapping document for your academic council
FAQ
Faculty Development Program — questions
Is the faculty development program aligned to AICTE or UGC requirements?
The curriculum is written against AICTE model curriculum outcomes for AI and data science, and we provide a syllabus mapping document your academic council can attach to its FDP proposal. We are not an approving body: certificates are issued by AI Anytime, and any AICTE, UGC, or ATAL sanction is applied for by your institution. We routinely supply the content annexures those applications ask for.
Can the FDP be delivered online?
Yes. All formats run online, on campus, or hybrid. Online cohorts use live sessions with breakout labs rather than recorded lectures — the lab time is the point, and it does not survive being pre-recorded. On-campus delivery works best for the one-week and two-week formats.
How many faculty can attend one batch?
Up to 60 for lecture-led modules. For lab modules we cap a supervised batch at 30 so every participant gets debugged personally; larger groups are split into parallel labs with an additional facilitator.
What prior knowledge do participants need?
Working Python and comfort with a terminal. No machine learning background is assumed — faculty from CSE, IT, ECE, and MCA departments all complete the program. We send a two-hour pre-work notebook that brings everyone to the same starting line.
What infrastructure does the college need to provide?
Laptops with a browser and internet. Everything runs on free Colab tiers or small local models where the network allows. If you want to run models on campus hardware, we will size a GPU configuration against your budget before the program.
Do participants receive certificates?
Every participant who completes the labs receives a certificate from AI Anytime naming the modules and contact hours. Institutions that need their own branding on the certificate can have it co-signed.
Do you keep the teaching material after the program?
You keep it. Slides, notebooks, rubrics, and recordings are licensed to your institution for internal teaching in perpetuity. The only restriction is reselling the material as a commercial course.
What does a faculty development program cost?
Pricing depends on format, cohort size, and whether delivery is on campus. Send us the format and headcount through the enquiry form and you will get a written quote, including travel where applicable, within two working days.
Also available
02
Online Courses on AI
Instructor-led delivery, course design, course development, or a full turnkey package — for AI programs in full stack AI, generative AI, agentic AI, and forward deployed engineering.
03
AI Masterclasses
Focused AI masterclasses for engineering teams, conferences, and cohorts — RAG in production, context engineering, agentic design patterns, evaluation, and AI security.
04
Workshops, Webinars and Seminars
Hands-on AI workshops, live webinars, campus seminars, and hackathon mentoring — from a 60-minute session to a two-day build.
Ready when
you are.
Send the audience, the headcount, and the window you are working with. You get scope and price in writing within two working days — no discovery call required first.
Enquire about faculty development