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B.Tech in CS, AI & Data Science

Build intelligent systems and shape the future of technology.
Apply for July 2026 Intake
Next Cohort
July 2026
Format
4 Years, Full time

The ATLAS uGDX B.Tech Experience

The B.Tech programs in ATLAS immerses you in technology from day one - through hands-on coding, real-world projects, and industry-integrated learning that build the skills to innovate and lead in the digital world.

Multidisciplinary
Tech Education
Learn AI/ML alongside electives in design and management, applying your skills through a semester-long internship.
Master classes by industry leaders
Learn directly from global technology experts, CTOs, and industry innovators.
NEP 2020
Integrated
Hundreds of hours of coding practice and training to master writing clean, scalable code.
Experiential &
Hands-on learning
Apply classroom concepts to live projects and real-world problem solving.
Curriculum co-created with industry
Study a curriculum designed with leading CTOs to stay aligned with industry needs.
Entrepreneurship hub
Get mentorship and support from Venture Labs to build and launch your own tech startup.
Urban campus experience
Thrive in a modern, high-tech learning environment with state-of-the-art infrastructure.
Career services
Apply classroom concepts to live projects and real-world problem solving.

Why Choose B.Tech in CS, AI & Data Science at ATLAS uGDX

AI & Machine Learning

A curriculum built around the data lifecycle - from collection and analysis to AI-driven prediction - equipping you to turn information into innovation.
01

AI & Machine Learning in Practice

Master modern tools and algorithms through hands-on labs and projects that simulate how real industries use data to automate, optimize, and scale.
02

Designed with
Industry Leaders

Apply design thinking to craft intuitive, user-centered digital products that solve complex problems.
03

Interdisciplinary Learning through ATLAS Electives

Work on live projects and challenges with leading companies, gaining practical exposure and problem-solving experience.
04

Global Exposure, Local Edge

Learn in Mumbai’s innovation ecosystem through observerships, global immersion programs, and ATLAS Venture Labs - where ideas become startups.
05

A Curriculum Designed for the Future

Built on the ‘Goal for Each Term’ (GET) philosophy, our curriculum ensures every semester has a clear, outcome-driven focus; continuously evolving with emerging technology trends and the learning needs of our students.
Year 1
Year 2
Year 3
Year 4

Semester 1

Foundations of Computing and Intelligent Systems
This semester builds a strong foundation in computing, mathematics, and scientific principles essential for artificial intelligence and machine learning. Students learn to program, analyze data, and understand robotics fundamentals while developing core digital communication.
Introduction to Computer Science & Programming 1
Provides a hands-on introduction to computational thinking and programming fundamentals.
Calculus 1
Introduces foundational mathematical concepts and techniques for modeling and problem-solving in AI and design.
Foundations of Statistics & Probability for AI & ML
Covers statistical reasoning and probabilistic methods essential for machine learning and AI applications.
Databases & SQL
Teaches principles of database design, querying, and management using SQL for data-driven projects.
Chemistry
Explores basic chemical principles and their applications in technology, materials, and interactive systems.
Fundamentals of CT, AI, ML, Robotics, and Data Science
Provides interdisciplinary exposure to computing, robotics, and machine learning frameworks driving intelligent automation.
Communication Skills for Digital World
Builds digital communication, presentation, and collaboration skills for effective engagement in tech-driven environments.
ATLAS Electives
Offers interdisciplinary elective courses that combine technology, design, and creative innovation.
Simulation/Computer Game Design (Pinnacle I)
Develops computational design skills through interactive simulations blending programming, logic, and visual storytelling.

Semester 2

Computational Structures and Applied Data Insights
This semester deepens programming, mathematics, and analytical reasoning for intelligent systems. Students enhance their understanding of algorithms, data modeling, and applied sciences while developing interdisciplinary perspectives that merge computation with human and physical sciences.
Introduction to Computer Science and Programming 2
Builds upon basic programming to develop efficient algorithms and modular code.
Mathematics for Computer Science
Focuses on discrete mathematics, logic, and proofs essential for computer algorithms and computation.
Calculus 2
Extends differential and integral calculus to multivariable systems and complex applications.
Physics
Covers mechanics, electromagnetism, and thermodynamics to strengthen scientific grounding in computational systems.
Statistical Modeling
Teaches how to construct and interpret statistical models to analyze real-world data patterns.
Indian Health Sciences
Examines traditional health knowledge systems and their relation to technology, ethics, and data innovation.
Expository Writing
Develops clarity and precision in technical writing, research presentation, and academic communication.
ATLAS Electives
Offers creative, cross-disciplinary courses blending design, computation, and innovation.
Data Analyst Project (Pinnacle II)
Applies data analytics and visualization skills in a practical, research-based computing project.

Semester 3

Foundations of Machine Learning and Computational Intelligence
Semester 3 focuses on developing strong analytical and computational foundations through machine learning, data science, and algorithmic thinking. Students explore structured and unstructured data systems while applying mathematical models to real-world problem-solving, shaping their ability to design intelligent, data-driven solutions.
Machine Learning Foundations
Provides the mathematical foundation for AI, computer graphics, and machine learning algorithms.
Computer Organization and Architecture
Explores processor design, memory hierarchy, and instruction execution essential for computational efficiency.
Linear Algebra
Provides the mathematical foundation for AI, computer graphics, and machine learning algorithms.
Data Structures and Algorithms
Develops problem-solving efficiency through algorithmic design and data optimization techniques.
Fundamentals of Data Science and Analytics
Explains data cleaning, visualization, and analysis methods to derive actionable insights.
Model Thinking
Applies mathematical and conceptual models to understand patterns in data and complex systems.
Foundational Literature of Indian Civilization
Examines Indian philosophical and scientific thought, connecting heritage with modern innovation.
ATLAS Electives
Offers creative, cross-disciplinary courses blending design, computation, and innovation.
Machine Learning: Astrophysics, Particles, Drug Design (Pinnacle III)
Applies machine learning to advanced scientific domains through real-world research projects.

Semester 4

Applied Intelligence and System Integration
Semester 4 integrates advanced machine learning with core concepts of software engineering, databases, and IoT to create scalable AI systems. Students gain hands-on experience in data mining, system design, and enterprise-grade applications, bridging technical development with practical business innovation.
Big Data Analyst
Explores deep neural networks, reinforcement learning, and optimization techniques for complex AI systems.
Database Design and Management
Covers relational models, normalization, and data integrity for efficient and secure information storage.
Operating Systems and Networks
Focuses on process management, memory systems, and network protocols essential for system-level computing.
Data Mining & Warehousing
Introduces data extraction, transformation, and analytics for large-scale decision-making frameworks.
Software Engineering Principles
Covers design methodologies, version control, and testing for robust, maintainable software systems.
Embedded System and IoT
Examines microcontrollers, sensors, and connectivity protocols for real-time intelligent devices.
Business Plan Writing
Develops entrepreneurial thinking through strategic, financial, and innovation-driven project planning.
ATLAS Electives
Encourages interdisciplinary engagement with human-centered, creative, or ethical perspectives in AI.
An Enterprise Grade AI Application: Recommendation Engines for OTT Platforms (Pinnacle IV)
Applies machine learning to personalize user experiences and enhance data-driven media recommendations.

Semester 5

Intelligent Systems and Innovation
This semester advances skills in AI-driven automation through reinforcement learning, computer vision, and NLP. Students apply cloud and data analytics to real-world systems while fostering entrepreneurial thinking and developing innovative projects such as self-driving technologies.
Reinforcement Learning and NLP
Master the art of making big-picture decisions. Learn how to evaluate competition, allocate resources, and plan for long-term business success in volatile environments.
Computer Vision and Deep Learning
Focuses on enabling machines to interpret and process visual information from the world.
Image Processing
Covers enhancement, transformation, and segmentation of digital images for computational applications.
Data Analytics and Visualization
Teaches methods to interpret, visualize, and communicate complex datasets through modern analytical tools.
Cloud Application Development
Explores cloud infrastructure, APIs, and deployment pipelines for scalable AI-based applications.
Entrepreneurship Development
Encourages innovation through idea validation, resource planning, and tech-based business creation.
Cultural and Intellectual Heritage of English
Introduces global communication, critical thinking, and cultural perspectives in academic and professional contexts.
Enterprise Grade Connected Device Application: Self-Driving Cars (Pinnacle V)
Applies AI, sensor fusion, and machine learning to develop autonomous and intelligent mobility systems.

Semester 6

Advanced Data Intelligence and Systems Security
This semester focuses on integrating large-scale data analysis with secure AI systems and predictive modeling. Students explore multi-modal learning and advanced forecasting while applying cross-disciplinary insights through internships and foundational studies in science and computation.
Big Data Analytics
Covers distributed computing frameworks, large-scale data handling, and predictive insight generation.
Secure Coding
Teaches best practices to write robust, vulnerability-free software applications.
Data Science for Generic AI
Focuses on building adaptable AI models through data-driven reasoning, generalization, and automation.
Time Series and Forecasting
Explores trend analysis and temporal data prediction using statistical and machine learning models.
Multi-Modal Learning (Text + Vision + Speech) Analysis
Integrates diverse sensory data types to train AI systems for richer contextual understanding.
Language of Science and Technology (English)
Strengthens scientific writing, communication, and presentation within technological and research contexts.
Introduction to Indian Mathematics & Astronomy
Examines classical mathematical logic and astronomical innovation from an Indian scientific heritage perspective.
Summer Internship
Provides practical exposure to AI development, data research, or tech innovation in professional settings.

Semester 7

Research and Ethical Innovation in AI
This semester deepens analytical and computational rigor through Bayesian inference, quantum computing, and advanced electives. Students refine their research skills while engaging with ethical and governance frameworks to ensure fairness and responsibility in AI-driven systems.
Advanced Statistical Inference & Bayesian Analysis
Focuses on probabilistic reasoning, Bayesian modeling, and uncertainty quantification for predictive AI systems.
Quantum Computing & Algorithms
Introduces quantum logic, superposition, and algorithmic frameworks for high-performance computational problem solving.
Core Elective 1
Allows focused study in a chosen AI or computer science specialization area.
Core Elective 2
Expands interdisciplinary expertise through advanced application-based or theoretical exploration.
Core Elective 3
Encourages independent inquiry into emerging fields or niche AI technologies.
Data Ethics, Fairness, and Governance in AI Systems
Examines AI accountability, bias mitigation, and regulatory frameworks for equitable digital systems.
Research Methodology
Develops systematic research design, data collection, and analytical skills for academic or industrial innovation.

Semester 8

Applied AI Innovation and Human-Centric Research
The final semester brings together computing, design, and innovation through an internship and capstone project, allowing students to apply theory, gain practical experience, and prepare for careers, research, or entrepreneurship.
Internship and Project and Dissertation (Product Based)
Applies AI and data science principles to develop, test, and deploy real-world product solutions.
Federated Learning and Distributed AI (MOOC)
Explores decentralized machine learning frameworks enabling collaborative intelligence while preserving data privacy.
Cognitive Systems and Human-AI Interaction (MOOC)
Studies intelligent systems that interpret, adapt, and respond to human behavior for seamless AI collaboration.

Program Outcomes

Engineer End-to-End Data Solutions
Develop scalable data pipelines and integrate AI models into robust software systems that power intelligent products.
Intelligent
Systems Design
Apply AI, machine learning, and deep learning to create adaptive, data-driven solutions.
Apply
Computational Thinking
Use structured problem-solving and algorithmic logic to turn complex data into clear, actionable insights.
Innovate Across Disciplines
Collaborate with designers, managers, and researchers to create technology that’s functional, human-centered, and impactful.
Champion Ethical
AI Practices
Design and deploy AI responsibly ensuring fairness, transparency, and accountability in every data-driven decision.
Research & Entrepreneurship
Translate ideas into prototypes, startups, or applied research that advance technology and serve real societal needs.

Ready to Build What’s Next?Let’s Get Started.

Get a glimpse - where future engineers and innovators areshaped through technology, industry, and inspiration.
Apply Now
Schedule a visit

Career Pathways

Explore diverse career pathways across AI, data science, and emerging technologies

Data Scientist
Data Analyst
Business Intelligence Developer
Quantitative Analyst
Machine Learning Engineer
Data Research Scientist
Policy Analyst
Supply Chain Analyst
AI/ML FocusedSoftware Developer
Big Data Engineer

Student Voices: Real Voices from the Program

Unlike traditional B.tech programs, uGDX prioritizes hand-on experiences and industry opportunities.
Ayush Gharat
Student, uGDX
At uGDX, I have started viewing the world in a different way.
Leisha Totani
Student, uGDX
Unlike many other B.Tech programs, we have an outcome defined for every semester.
Mohit Bhimrajka
Student, uGDX
Programming will become a second language to you. You'll understand it in a deeper sense.
Adarsh Mukherjee
2nd year student

Your guide to joining B.Tech in CS, AI & Data Science

01
Fill the online Application Form
Apply for July 2026 Intake
02
uGDX Challenge
03
Personal Interview
04
Result
Announcement
05
Complete
Enrolment
Eligibility
Indian Boards (ISC / CBSE / State Boards)
Minimum 50% in Class XII
Mathematics and Physics are mandatory

A-Levels (UK)
Minimum grades A/B/C in 2 subjects
Grade B or above in Mathematics.
Mathematics and Physics are mandatory

International Baccalaureate (IB)
Minimum of 24 points in 3 HL & 3 SL subjects
Mathematics and Physics are mandatory
Application Fee: ₹3,500
After selection, the enrolment fee of ₹50,000 to secure your seat is refundable!
Fee Structure
We believe in clarity. Here’s a simple year-on-year breakdown of our fees!
Fee Structure
Admissions Policy
Loans & Scholarships
That’s right – Funding just got easier! We partner with India’s top banks to support your journey to success. And, our ATLAS Scholarship is there to enable access to world-class education and lifelong growth.
Education Loans
ATLAS Scholarships
More questions?
Let our AI Assistant answer your queries

Questions? We can read your mind

Yes. AI & Data Science is one of the fastest-growing and in-demand fields in India and globally. Professionals skilled in AI, machine learning and data analytics are highly sought after across IT, fintech, healthcare and research industries.

AI & ML focuses on creating intelligent algorithms and predictive models, while AI & Data Science emphasises collecting, analysing and interpreting large datasets to drive insights and informed decisions. This program blends both applied problem-solving.

Applicants must have completed Class 12 or equivalent qualification with science or technical subjects from a recognised board. Program-specific requirements, such as minimum marks or aptitude assessment, may also apply.

Admission may require an entrance assessment, aptitude test or evaluation as per university guidelines. Candidates should check the official uGDX admissions portal for the latest accepted exams and requirements.

Students can apply online through the Atlas University portal. The process typically involves submitting academic records, completing the application and participating in assessments or interviews if required.

Core subjects include programming, AI and machine learning, data analytics, database management, cloud computing and cybersecurity fundamentals. The program also emphasises hands-on projects and applied learning.

Yes. Atlas University offers merit-based scholarships, need-based support and program-specific awards to eligible students. Details and eligibility criteria are available on the official admissions page.

Graduates can pursue careers as data scientists, AI engineers, machine learning specialists, business analysts or technology consultants across IT, finance, healthcare and research sectors.

Yes. This program provides theoretical knowledge, practical skills and industry exposure required to pursue roles as a Data Scientist or related analytics and AI positions.

Absolutely. Students gain hands-on experience through internships, live industry projects, masterclasses and professional visits, ensuring they graduate with practical skills and career readiness.