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Bio2· Biotech and life sciences

AI in Food Science & Quality

You will use AI to speed up label checks, shelf-life reasoning and QC documentation for packaged foods, while keeping every compliance and safety decision with a qualified human and the current regulation text.

Choose a planRead the syllabus
Who it is for
MSc Food Science & Technology students and biotech students heading into quality, regulatory or product development work at food brands, including fast-growing D2C snack and staples brands.
AI core
9 units · 20 h
This course
6 modules · 12 lessons · 7.3 h
Live projects
2, on Professional and Career
01Roles it prepares you for
  • QC/QA Executive
  • Food Regulatory Assistant
  • Product Development Assistant (food)

The skills these roles ask for. Preparation, not a promise of a job.

02Tools you will use
  • ClaudeFree tier
  • ChatGPTFree tier
  • Google SheetsFree tier
  • NotebookLMFree tier
  • FSSAI FoSCoS public licence lookupFree tier

You never pay for a tool subscription. “Verified” means we checked the free access on the vendor’s own site this month. Tool names describe what you learn; no vendor endorses Launchpad.

03Syllabus

What you will learn, in order.

Lesson films are narrated with an AI voice, over visuals made with AI tools and checked by our team. Saarthi, the coach, is an AI. Mentors and reviewers are people.

Part 1 · The AI core, shared by every stream

00Set up your coach1 hLearn how the core works, write the learning-context document that tells every AI tool who you are, and set Saarthi up as a coach that makes you think instead of thinking for you.
  1. How this core works6 min
  2. Write your learning-context document8 min
  3. Seven roles for AI, and study modes7 min
01How LLMs work and fail2.5 hBuild a working mental model of a large language model: tokens, prediction, context windows and memory. Then learn its predictable failures (hallucination, sycophancy, stale knowledge, bad arithmetic) and reproduce them yourself.
  1. Tokens and next-word prediction7 min
  2. Context windows and memory7 min
  3. Hallucination, sycophancy and other failures8 min
  4. Lab: one prompt, three models, five failures8 min
02Description and context engineering3.5 hWrite briefs that get the right output the first time: role, task, context, examples and format. Then make them reusable with Claude and ChatGPT Projects, Gemini Gems, custom GPTs and NotebookLM, and learn to work with PDFs, spreadsheets and images.
  1. The brief: role, task, context, format8 min
  2. Examples and output formats7 min
  3. Projects in Claude and ChatGPT8 min
  4. Gems, custom GPTs and NotebookLM8 min
  5. Working with files: PDFs, spreadsheets, images8 min
03Verify everything2.5 hCheck AI output the way fact-checkers do: lateral reading, tracing citations and numbers to the original, using deep-research modes without trusting them blindly, and testing a prompt properly with a 10-case golden set.
  1. Lateral reading7 min
  2. Checking citations and numbers8 min
  3. Deep-research modes: use and limits7 min
  4. Your first eval: a 10-case golden set8 min
04Connectors and MCP2 hConnect AI to the places your work lives (Drive, Gmail, Sheets, business data) without writing code. Learn what an MCP server is, why a reviewed directory differs from unreviewed community servers, how to grant the least access that works, and how to keep browser extensions on a short leash.
  1. What connectors and MCP are8 min
  2. Trust, least privilege and the reviewed directory8 min
  3. Browser extensions and AI browsers7 min
  4. Lab: ask the seller-data MCP server, check every answer8 min
05Agents and automations3.5 hHand multi-step work to AI safely. Tell an agent from an automation, decide what to delegate, use browser and coding agents with care, and build an n8n workflow that uses AI with a human-approval step before anything leaves the system.
  1. Agents vs automations: what to delegate8 min
  2. Browser agents, safely7 min
  3. Automation basics with n8n and Zapier8 min
  4. Lab: build an automation with a human-approval step8 min
  5. Failure modes and your failure-mode note7 min
06AI for learning and careers1.5 hUse AI to learn faster without outsourcing the learning, write applications that still sound like you, and practise interviews out loud with Saarthi.
  1. Learning with AI, not instead of learning7 min
  2. Applications in your own voice7 min
  3. Mock interview with Saarthi8 min
07Diligence: law, ethics, integrity2.5 hThe rules that apply when you use AI in India: the DPDP Act 2023 and its 2025 Rules, academic integrity and disclosure, copyright (including where Indian law is still unsettled), and bias. You finish by writing your own AI-use policy.
  1. DPDP Act 2023: personal data and AI8 min
  2. Academic integrity and disclosure7 min
  3. Copyright and AI in India8 min
  4. Bias and fairness7 min
  5. Write your personal AI-use policy7 min
08Core capstone1 hPut all four Ds together on one anonymised marketplace settlement file: ask good questions, automate one step, verify every number against Saarthi's P&L engine, and defend your work live in five minutes.
  1. The capstone brief6 min
  2. Lab: ask, automate, verify8 min
  3. Prepare your 5-minute defence7 min

Part 2 · AI in Food Science & Quality

01The packaged-food label, element by element2 lessonsWhat the FSSAI labelling regulations require on a pack, how online listings must match the label, and how to check a label systematically.
  1. What must be on an Indian food label30 min
  2. Lab: audit five labels with an AI-assisted checklist40 min
02Nutrition panels and claims2 lessonsCalculating per-serve values and %RDA, and checking front-of-pack claims against the claims regulations.
  1. Claims: what 'high protein' actually requires30 min
  2. Lab: a claims calculator for a D2C range40 min
03Shelf-life science and stability data2 lessonsWhat limits shelf life, how real-time and accelerated studies work, and how to read stability data without over-claiming.
  1. What ends a product's shelf life30 min
  2. Lab: analyse a stability dataset45 min
04QC systems: HACCP, deviations and CAPA2 lessonsThe quality-system basics an AI assistant must respect, and how to use AI to draft documents without letting it make safety decisions.
  1. HACCP, deviations and CAPA in plain language30 min
  2. Lab: draft deviation records and a CAPA plan40 min
05Building a QC SOP assistant with refusal rules2 lessonsDesigning an assistant that answers only from approved SOPs, cites its source, and refuses or escalates safety decisions.
  1. Grounding, citations and when to refuse30 min
  2. Lab: build and red-team an SOP assistant45 min
06Complaints, traceability and the founder conversation2 lessonsHandling customer complaints and traceability with AI help, and explaining compliance decisions to a founder who wants a different answer.
  1. Complaint triage and traceability30 min
  2. Lab: triage 200 complaints and brief the founder45 min
04Live projects

Two briefs. Real-shaped work.

  1. Project 1

    Shelf-life and label-claim check for packaged-food D2C SKUs

    A synthetic D2C food brand plans to list 8 SKUs (for example, millet cookies, a chutney powder, a protein bar, a cold-pressed oil and roasted snack mixes) on its own site and quick-commerce apps. For each SKU, audit the label against the current FSSAI labelling regulations, check every front-of-pack and online claim against the current claims regulations with a transparent calculator, and analyse the provided stability data to recommend a defensible best-before period that also works with the reported e-commerce minimum remaining shelf life. Use AI to speed up checking and drafting, measure its errors, and keep every compliance conclusion traceable to a clause and a date. Present findings to the founder (Saarthi plays him), who wants longer dates and stronger claims.

    You hand in

    • Label audit checklist for 8 SKUs with clause citations and the date of the regulation text used
    • Claims calculator sheet with a Rules tab, boundary tests and results per claim
    • Stability analysis per SKU: charts, crossing points, limiting factor and Q10 justification
    • Shelf-life recommendation per SKU, including the e-commerce delivery check
    • Safe rewrites for every failing claim
    • AI error log with disagreement rate and error types
    • A 10-minute recorded founder briefing

    Data: Synthetic: label texts and HTML mock label artwork, lab nutrition reports, and stability readings at two temperatures for 8 SKUs of a fictional brand, plus a sandbox rule card into which you copy clauses from the official FSSAI text, with the date.. Reviewed by Saarthi against a published rubric, signed off by a mentor.

  2. Project 2

    QC SOP assistant with refusal rules

    Build a QC SOP assistant for a synthetic snack plant that answers shift staff questions only from the approved SOP set, cites SOP number, version and section for every answer, says honestly when the SOPs do not cover a question, and refuses and escalates every safety decision (batch release, allergen incidents, foreign bodies, contamination, limit changes, health questions) with a clear next step. Design the system prompt and the SOP version register, write a red-team test set of at least 40 questions, run it at least twice with fixes in between, and decide whether the assistant is fit to deploy. A do-not-deploy recommendation with clear reasons is an acceptable outcome.

    You hand in

    • System prompt with grounding, citation and refusal rules
    • SOP version register showing only approved versions loaded
    • Red-team test set of at least 40 questions with expected outcomes (at least 12 must-refuse)
    • Two or more scored test runs with changes documented between them
    • Release note with accuracy, not-covered honesty and refusal rates, limitations and owner
    • Deploy or do-not-deploy recommendation with reasons

    Data: Synthetic: an approved SOP set for a fictional snack plant (receiving, roasting, grinding, metal detection, packing, cleaning, allergen control, complaints), plus superseded versions as distractors, provided in the Saarthi sandbox.. Reviewed by Saarthi against a published rubric, signed off by a mentor.

05Practise out loud

In voice mock interviews and client calls, Saarthi plays: Anand, founder of a Mangaluru D2C millet-snacks brand selling on its own site and quick-commerce apps. He wants 'high protein' on every pack, a longer shelf life on the label, and an AI bot that answers his QC team's questions. He pushes back when you say no, so you must cite the rule and offer a safe alternative.

On plans that include mock interviews. You get written feedback after every call.

06Enrol

Pick a plan for AI in Food Science & Quality.

One payment. The access deadline for each plan is shown before you pay.

  • Foundation

    01

    Learn the AI your field now runs on.

    ₹2,999

    One payment. GST included.

    • Access for 120 days (about 4 months) from the day you pay
    • No 1:1 mentor sessions
    • The common AI core and your domain course
    • Saarthi, your AI coach, any hour
    • Hands-on labs on free tools
    • Verifiable certificate
    Enrol on Foundation

  • Professional

    02

    Prove it on real work.

    ₹7,999

    One payment. GST included.

    • Access for 180 days (about 6 months) from the day you pay
    • One 1:1 session with a mentor
    • Everything in Foundation
    • Two live projects, reviewed by Saarthi and a mentor
    • Public portfolio page of verified work
    • Voice mock interviews
    • One 1:1 coaching session
    Enrol on Professional

  • Career

    03

    Work alongside our team.

    ₹14,999

    One payment. GST included.

    • Access for 240 days (about 8 months) from the day you pay
    • Four 1:1 sessions with a mentor
    • One 1:1 call with an industry expert
    • Everything in Professional
    • Four-week supervised practicum with the Saarthi team
    • Four 1:1 coaching sessions with your mentor
    • An exclusive 1:1 call with an industry expert in your field
    • CV and LinkedIn review
    • Priority mentor replies
    Enrol on Career

Your access period starts the day you pay and is shown before you pay. One exam pause per enrolment, for up to 15 days. When access ends the course locks, and your portfolio page and certificate stay live. Full refund within 7 days, pro-rata after that, and an automatic refund for any practicum, 1:1 mentor or expert session we do not deliver. Refund policy