Undergraduate · 4 Years · Full-Time

B.Tech in Digital Transformation, AI & Leadership

Not just engineers — AI architects of organisations. A B.Tech that builds technical depth and leadership breadth from Year 1.

A 4-year, 8-semester engineering programme that combines computer science and AI foundations with business strategy, product thinking, and responsible technology leadership. Graduates leave with Python, ML, cloud, and generative AI proficiency — alongside skills in digital strategy, product management, AI governance, and entrepreneurship. A mandatory Year-3 industry internship and a Year-4 Capstone put every graduate into the workforce with real-world experience and a portfolio of work.

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  • AI + Leadership integrated from Year 1
  • Generative AI & LLMs as a core Year-3 course
  • 6 labs across 8 semesters + Year-4 Capstone

Why this programme is different

Four things separate this B.Tech from a conventional engineering degree.

1

Technical Depth Meets Leadership Breadth

Not a traditional B.Tech with a management elective. AI engineering (ML, deep learning, LLMs, cloud, DevOps) is integrated with leadership, strategy, product thinking, and AI governance from Year 1 through Year 4. Graduates can build systems and lead teams.

2

Generative AI & LLMs From Year 3

Generative AI & Large Language Models (BDT501) is a dedicated core subject in Semester V — one of very few undergraduate engineering programmes globally to include a full course on LLMs, prompt engineering, RAG architectures, and real-world GenAI deployment at the undergraduate level.

3

Six Labs Across Eight Semesters

Digital Futures Labs (I & II), Innovation Labs (I & II), AI Engineering Labs (I & II), and the Year 4 Capstone keep students hands-on with real tools and real briefs throughout the entire programme. Labs are graded, credit-bearing, and industry-connected.

4

Industry Internship + Capstone in Final Years

An Industry Internship in Semester VII places students in real organisations, followed by a Capstone Project / B.Tech Thesis in Semester VIII evaluated by an expert industry panel. Every graduate leaves with a professional portfolio, not just a transcript.

Year-by-year journey

Eight semesters. 152 credits. Six labs. One industry internship and one capstone thesis.

Year 1 — Digital Foundations

Semester I — Computing & Digital Foundations

Build the technical and conceptual base — computing principles, mathematics for AI, Python programming, and a first look at digital transformation. Digital Futures Lab I provides hands-on exploration of real digital tools.

CodeCourse
BDT101Foundations of Computing & Digital Systems
BDT102Mathematics for AI & Data Science
BDT103Introduction to Digital Transformation
BDT104Programming Fundamentals (Python)
BDT105Communication & Professional Skills – I
BDT106Digital Futures Lab – I
Year 1 — Digital Foundations

Semester II — Data, Algorithms & Introduction to AI

Progress into data structures, statistical thinking, OOP, and a formal introduction to AI and machine learning concepts. Digital Futures Lab II introduces students to AI tools in practical contexts.

CodeCourse
BDT201Data Structures & Algorithms
BDT202Statistics & Probability for AI
BDT203Business Fundamentals for Engineers
BDT204Object-Oriented Programming (Java/Python)
BDT205Introduction to AI & Machine Learning
BDT206Digital Futures Lab – II
Year 2 — Core AI & Engineering

Semester III — Machine Learning, Databases & Digital Strategy

ML theory meets practice — supervised and unsupervised learning, database systems, cloud storage, web development, and an AI ethics foundation. Innovation Lab I provides a real industry brief.

CodeCourse
BDT301Machine Learning – I: Supervised & Unsupervised
BDT302Database Systems & Cloud Storage
BDT303Digital Business Strategy
BDT304Web & Application Development
BDT305AI Ethics & Society
BDT306Innovation Lab – I
Year 2 — Core AI & Engineering

Semester IV — Deep Learning, Cloud, DevOps & Product Thinking

Neural networks, cloud computing, DevOps pipelines, big data platforms, and responsible AI governance — all while developing product thinking and innovation skills in Innovation Lab II.

CodeCourse
BDT401Machine Learning – II: Deep Learning & Neural Nets
BDT402Cloud Computing & DevOps
BDT403Product Thinking & Digital Innovation
BDT404Data Engineering & Big Data Platforms
BDT405Responsible AI & Governance
BDT406Innovation Lab – II
Year 3 — Advanced AI & Industry Practice

Semester V — Generative AI, Product Management & Specialisation

Dedicated LLM and GenAI engineering course, AI product management, cybersecurity in AI systems, digital transformation strategy, and the first specialisation elective. AI Engineering Lab I is a live product build exercise.

CodeCourse
BDT501Generative AI & Large Language Models
BDT502AI Product Management
BDT503Cybersecurity & Privacy in AI Systems
BDT504Digital Transformation Strategy
BDT505Elective I (Specialisation Track)
BDT506AI Engineering Lab – I
Year 3 — Advanced AI & Industry Practice

Semester VI — AI Systems, Leadership & Deep Specialisation

AI systems architecture, technology leadership, entrepreneurship, and two more specialisation electives. AI Engineering Lab II delivers an advanced, industry-connected engineering project.

CodeCourse
BDT601AI Systems Design & Architecture
BDT602Leadership in Technology Organisations
BDT603Entrepreneurship & AI Ventures
BDT604Elective II (Specialisation Track)
BDT605Elective III (Specialisation Track)
BDT606AI Engineering Lab – II
Year 4 — Specialisation, Internship & Capstone

Semester VII — Industry Internship & Research Foundations

A full-semester, 240-hour industry internship sits at the core of this semester. Research methods, sustainability, and executive communication modules run alongside it to prepare students for the Capstone.

CodeCourse
BDT701Industry Internship
BDT702Research Methods & Technical Writing
BDT703Sustainability & ESG in Technology
BDT704Communication & Executive Presence
Year 4 — Specialisation, Internship & Capstone

Semester VIII — Capstone Project, AI Showcase & Pitch Day

The final semester is entirely applied. The Capstone Project / B.Tech Thesis (10 credits) is evaluated by an industry-academic panel. The AI Product Showcase and Entrepreneurship Pitch Day complete the graduating portfolio.

CodeCourse
BDT801Capstone Project / B.Tech Thesis
BDT802AI Product Showcase
BDT803Entrepreneurship Lab & Pitch Day
Programme total — 4 years · 8 semesters · 152 credits

Tools & platforms you'll master

The same stack used by production AI teams — from Python and cloud to Hugging Face, LangChain, and modern experiment tracking.

Python (core)

Y1–Y4

Primary programming language — ML, data science, scripting

Jupyter Notebook

Y1–Y4

Interactive coding, ML experiments, data analysis

Git & GitHub

Y1–Y4

Version control, collaboration, portfolio hosting

scikit-learn

Y2–Y4

Classical ML — classification, regression, clustering

TensorFlow / PyTorch

Y2–Y4

Deep learning frameworks for neural network training

Hugging Face

Y3–Y4

Pre-trained LLMs, transformers, GenAI experimentation

OpenAI / Claude API

Y3–Y4

Generative AI integration and LLM application development

AWS / GCP / Azure

Y2–Y4

Cloud computing, model hosting, DevOps pipelines

Docker & Kubernetes

Y3–Y4

Containerisation and deployment of AI applications

Power BI / Tableau

Y1–Y3

Data visualisation, business dashboards, analytics

PostgreSQL / MongoDB

Y2–Y3

Relational and NoSQL databases, cloud storage

Spark / Databricks

Y2

Big data processing and distributed computing

ChatGPT / Claude / Gemini

Y1–Y4

AI assistants — productivity, coding, research

Notion / Miro / Figma

Y2–Y4

Product management, design thinking, wireframing

Langchain / LlamaIndex

Y3–Y4

RAG systems and LLM application frameworks

MLflow / Weights & Biases

Y3–Y4

ML experiment tracking and model management

Where graduates go

Eight career destinations for Futred DTAIL graduates — from AI engineering and product to research and entrepreneurship.

AI / ML Engineer

Build, train, and deploy machine learning and deep learning models at technology companies, AI labs, and enterprise data teams.

Generative AI Developer / LLM Engineer

Specialise in GenAI application development, RAG systems, fine-tuning, and LLM-powered product features.

AI Product Manager

Manage the product lifecycle of AI-powered products from concept through deployment, at technology companies and AI-native startups.

Digital Transformation Analyst / Consultant

Advise organisations on technology adoption, digital strategy, and AI integration at consulting firms and in-house.

Cloud & DevOps Engineer (AI Focus)

Build the infrastructure and pipelines that power AI systems at scale, in cloud-first and enterprise environments.

Responsible AI & Governance Specialist

Advise on AI ethics, regulatory compliance, bias auditing, and AI policy at technology companies, regulators, and advisory firms.

Technology Entrepreneur / AI Startup Founder

Build AI-native startups with a strong technical foundation and product, strategy, and fundraising skills.

Research Engineer / AI PhD Track

Pursue graduate research in machine learning, computer vision, NLP, or AI systems, with strong foundational preparation from the programme.

Frequently asked

What is the eligibility for this B.Tech programme?+

Students must have completed 10+2 (or equivalent) with Physics, Chemistry, and Mathematics from a recognised board. Admission is through the relevant national or state-level engineering entrance examination (JEE, state CET, or university entrance), subject to the affiliated university's criteria. No prior programming or AI knowledge is required — the programme builds from first principles.

Is this a recognised B.Tech degree or a corporate certificate?+

This is a full B.Tech — Bachelor of Technology — undergraduate engineering degree recognised under the AICTE and UGC framework, awarded by the affiliated university. It is a four-year, full-time programme, not a certificate or diploma. Graduates receive a university-issued degree equivalent to any other B.Tech in India.

Do I need to know coding or AI before I join?+

No prior coding or AI knowledge is required. The programme is designed to take students from zero to production-ready AI engineering across four years. Semester I starts with computing fundamentals and Python programming basics. By Semester V, students are building generative AI applications and deploying ML systems on cloud platforms.

What is the Industry Internship and how is it arranged?+

The Industry Internship (BDT701) is an 8-credit, 240-hour structured placement in Semester VII with a verified industry partner in the AI, technology, or digital transformation space. Futred coordinates placements aligned to each student's specialisation track and career interests. The internship is graded on outcomes, supervisor evaluation, and a final presentation — it is not left to students to arrange independently.

What careers can graduates pursue after this B.Tech?+

Graduates are positioned for roles as AI/ML Engineers, Generative AI Developers, AI Product Managers, Cloud/DevOps Engineers, Digital Transformation Analysts, and Responsible AI Specialists — across technology companies, AI startups, consulting firms, and enterprise digital teams. The programme also prepares students for AI-focused M.Tech, MS, or PhD research paths, or for launching their own AI ventures via the Entrepreneurship Lab in Year 4.

Ready to become an AI engineer who leads — not just codes?

Join the next cohort of the B.Tech in Digital Transformation, AI & Leadership at Futred Business School. Applications are open for the upcoming academic year. Seats are limited — apply early to secure your place and receive the programme brochure.

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