Practitioner-led training in Data & AI implementation
Data Engineering, Data Science and AI Framework Implementation — for engineering colleges, university partnerships and enterprise teams. Taught by the same senior engineers who deliver our consulting work, not full-time trainers or recent graduates.
Not another Kaggle course
Most programs teach concepts on clean datasets. Graduates pass quizzes but stall at the first real production system. We build around three commitments.
Enterprise implementation, not theory
Every module is taught against the way data and AI actually ship in mid-market and enterprise companies — messy data, multi-team workflows, governance, cost pressure, change management. The goal is always the working system.
Industrial & automotive depth
Our founding team brings 17+ years of automotive and industrial data engineering. Connected vehicles, manufacturing telemetry and supply-chain analytics are the case studies and capstones — not generic e-commerce examples.
AI-framework-forward
The AI track is built around what enterprises deploy today: foundation models, RAG, LangChain, LlamaIndex, the Anthropic SDK, agent architectures, LLMOps, evaluation and governance — how to ship AI that passes enterprise security review.
One foundation, three specializations
A modular library: a shared Foundation tier, three specialization tracks, and an optional Enterprise Implementation tier for advanced learners.
Foundation
Brings learners from any CS/IT background to a working floor in modern data stacks: the modern data & AI landscape, Python, SQL and data modeling, cloud foundations, Git and CI/CD — plus the signature lecture, “How data flows in an automotive OEM” by founder Deepak K.
Data Engineering
Production pipelines, warehouses, lakehouses, orchestration, streaming, data quality, governance and performance.
Industrial telemetry pipeline
Data Science
Working statistics, ML fundamentals, feature engineering on enterprise data, evaluation rigor, time series, productionization, experimentation and responsible AI.
Predictive maintenance model for industrial equipment
AI Framework Implementation
Foundation models, prompt engineering and evaluation, RAG patterns, framework deep-dives, agent architectures, LLMOps, and enterprise AI security and governance.
Enterprise AI assistant (e.g. service-technician copilot)
Enterprise Implementation
Cross-cutting modules for senior learners and corporate engagements: architecture for mid-market vs enterprise scale, legacy migration patterns, team building, business case and ROI, vendor selection, and incident response.
For colleges
We are not selling a course. We offer an industry-academia partnership that helps your students enter the workforce with the skills the data and AI hiring market actually rewards.
| Format | Duration | Best for |
|---|---|---|
| Semester elective | 14 weeks | Final-year B.Tech / M.Tech / MCA students; counts toward credit |
| Workshop series | 8–10 sessions | Pre-final year or interest-based cohorts |
| Guest lectures / industry talks | 1–3 sessions | Department-wide or interdisciplinary audiences |
| Hackathon / capstone sponsorship | 2–4 weeks | Project-based engagement with our mentorship |
| Industry advisory | Ongoing | Curriculum review, internship pipeline, placement support |
- Curriculum, slides and hands-on lab content
- Senior-practitioner instructors
- Real enterprise project briefs as capstones
- Industry certificates of completion
- Top-performer pipeline into DataStackX roles
For enterprise teams
The same curriculum, delivered as paid corporate training and customized to your team's stack and use cases. Cohorts stay small — typically 10–15 — to protect the senior-led model.
| Format | Duration | Audience |
|---|---|---|
| Executive briefing | Half-day | CTO / CDO / VP Engineering — strategic decisions, not code |
| 3-day intensive | 3 days | A working team picks one track for focused upskilling |
| Multi-week program | 4–8 weeks | Foundation refresher + full track + team capstone on your real data |
| Embedded coaching | Custom | Part-time mentorship alongside an in-flight delivery project |
Portfolios and capability, not certificates alone
For every learner
- A working portfolio project on enterprise-shape data
- A DataStackX Academy certificate signed by the lead instructor
- A LinkedIn-ready project writeup
- Placement support and referrals (college cohorts)
For enterprise teams
- A documented team capability assessment — before and after
- Reusable templates, runbooks and eval harnesses
- Project starters built during the engagement
- A team that ships production data and AI, not slideware
Taught by people who ship
Senior instructors
A curated panel of practicing data engineers, ML engineers and AI implementation engineers from the DataStackX delivery network. Every instructor is shipping production work — not training full-time.
Bring enterprise-grade data & AI training to your people
Whether you run a CS department or an engineering team, let's design a cohort around your goals. A senior practitioner will walk you through the curriculum and formats.
Hyderabad, India · Delivering across India, US, UK & Canada