Taught from delivery, not slides
Every module comes out of AI programmes we are running right now — including the parts that did not work first time.
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AI Training Program
AI training taught by the people shipping it
Four tracks, from a two-day foundation for business users to a twelve-week programme for graduates — all built from live delivery work rather than generic curriculum.
Your documents, your data
Corporate sessions are run against your own document types and reports, so the examples are the ones your team will meet on Monday.
Small cohorts
Sessions are capped so that every participant gets time on the exercises and can bring their own problem to the room.
Tracks
Pick the one that matches your team
AI Foundations for Business Users
For operations, finance, HR and management staff who will use AI inside their day-to-day systems. What these models can and cannot do, how to write a prompt that returns a usable answer, and how to check output before acting on it.
Applied AI for Developers
For developers who will build AI features into enterprise applications. Working with model APIs, structured output, retrieval over your own documents, evaluation, and the engineering around reliability.
AI for Enterprise Automation
For teams planning an AI programme. How to pick the right first workflow, design a human-in-the-loop review step, keep an audit trail and structure milestones around demonstrable capability rather than calendar months.
Fresher Launchpad
A structured programme for recent graduates covering our full delivery stack — enterprise web development, SQL, and applied AI engineering — built around real project work rather than exercises.
Curriculum
What the hands-on track covers
Applied AI for Developers, module by module. Business and corporate tracks draw selected modules from the same material.
| Module | Focus | Outcome |
|---|---|---|
| 01 · Landscape | Model families, capabilities, cost and latency trade-offs, selecting a model per workflow | You can justify a model choice for a given task |
| 02 · Prompting | Instruction design, few-shot examples, output constraints, failure modes | You can get consistent output from an unreliable interface |
| 03 · Structured output | JSON schemas, validation, repair strategies, mapping to database tables | You can post AI output into a transactional system safely |
| 04 · Document AI | PDF and Excel ingestion, scanned documents, classification, field extraction, page references | You can build an extraction pipeline end to end |
| 05 · Retrieval / RAG | Chunking, embeddings, indexes, page-level citation, retrieval evaluation | You can answer questions over a large private document set |
| 06 · Comparison & rules | Requirement versus reference comparison, deviation logic, rule engines alongside models | You can build a validation workflow that an engineer trusts |
| 07 · Evaluation | Building an eval set, regression testing prompts, measuring drift | You can tell whether a change made things better |
| 08 · Productionising | Audit trails, human review screens, error handling, secrets, access control | You can ship an AI feature into an enterprise environment |
Formats
Delivered where it suits your team
- On-site corporate — at your office, using your own documents and reports as the working material
- Live online — instructor-led over video, same exercises, split across half-days if needed
- Campus programmes — delivered at engineering and technology institutions for final-year cohorts
- Fresher Launchpad — a full-time 12-week programme run from our Chennai office
Who it is for
Four audiences
- Business and operations teams adopting AI features inside their existing systems
- Software developers moving into AI engineering work
- Engineering and QA teams who will review AI-generated technical output
- Students and recent graduates preparing for applied AI roles
Outcomes
What participants leave with
A working artefact
Each hands-on track ends with a functioning pipeline the participant built and can take back to their team.
An evaluation habit
Participants leave able to measure whether an AI change helped — the skill that separates a demo from a product.
Governance instincts
Where a human review step belongs, what has to be logged, and which data should never reach a model.
Certificate of completion
Issued by Glob Data Analytics, listing the modules covered and the exercises completed.
Enquire
Plan a cohort
Tell us the track, the audience and roughly how many people. We will come back with a schedule, a syllabus tailored to your systems and a quote.
Training enquiriesinfo@globdataanalytics.in
Call us+91 00000 00000