02 / academics

LEARN THE
LANGUAGE.

A layered curriculum that moves from computational fundamentals to applied intelligence.

01 / degree pathways

ACADEMIC PROGRAMS.

Undergraduate · 4 Years

B.Tech in CSE (Data Science)

A four-year undergraduate engineering program combining computer science, mathematics, statistics and data-driven technologies to prepare students for careers in data science, analytics, artificial intelligence, machine learning and related fields.

Specialization · Elective

Honors & Minor Degrees

[HONORS PROGRAM] Advanced tracks in Autonomous Systems, Financial Technology, or Computational Biology for high-performing students.

02 / core curriculum

CORE SUBJECTS.

SUBJECT 01

Linear Algebra & Probability

Vector spaces, matrix decompositions, Bayesian probability, and stochastic processes.

SUBJECT 02

Data Structures & Algorithms

Graph algorithms, dynamic programming, space-time complexity analysis, and tree structures.

SUBJECT 03

Machine Learning Systems

Supervised & unsupervised learning, optimization algorithms, model evaluation, and validation.

SUBJECT 04

Deep Learning & Vision

Convolutional neural networks, transformer architectures, attention mechanisms, and generative models.

SUBJECT 05

Big Data & Cloud Systems

Distributed computing with PySpark, Hadoop, cloud data warehouses, and pipeline orchestration.

SUBJECT 06

Ethics & Responsible AI

Bias detection, algorithmic fairness, model explainability, privacy preservation, and data governance.

ACADEMICS / 03

INTERDISCIPLINARY
ELECTIVES.

GO BEYOND THE CORE.

Explore courses beyond the core Data Science curriculum and connect computational thinking with other engineering, technological and application domains.

DS-E01

Computing·Semester 6·3 Credits

Deep Learning & Natural Language Processing

Advanced neural architectures, transformer models, and semantic processing for multi-modal text intelligence.

DS-E02

Computing·Semester 6·3 Credits

Computer Vision & Pattern Recognition

Feature extraction, convolutional networks, object detection, and real-time video analytics.

DS-E03

Applications·Semester 7·3 Credits

Financial Analytics & Quantitative Trading

Algorithmic trading models, time-series econometric forecasting, risk analytics, and computational finance.

DS-E04

Science·Semester 7·3 Credits

Bioinformatics & Computational Genomics

Sequence alignment algorithms, genomic dataset processing, structural bioinformatics, and biological data mining.

DS-E05

Engineering·Semester 8·3 Credits

Autonomous Systems & Edge Robotics

Sensor fusion algorithms, SLAM, embedded AI hardware optimization, and autonomous control platforms.

DS-E06

Management·Semester 8·3 Credits

Technology Entrepreneurship & Product Analytics

Data-driven product growth strategies, tech venture creation, market telemetry analytics, and IP strategy.

04 / professional edge

CERTIFICATIONS & TRAINING.

Amazon Web Services

[AWS CERTIFIED DATA ANALYTICS]

Cloud data pipeline design, data lake architecture, and real-time analytics.

Google / Coursera

[TENSORFLOW DEVELOPER SPECIALIZATION]

Building, training, and deploying deep learning models in production environments.

Microsoft

[MICROSOFT AZURE AI ENGINEER]

Designing AI solutions with Cognitive Services, Azure Machine Learning, and OpenAI APIs.

05 / student support

TOOLS & RESOURCES.

Resource

Digital Library & Journals

Access to IEEE Xplore, ACM Digital Library, Springer journals, and curated dataset repositories.

Support

Faculty & Mentor Hours

Weekly designated office hours with faculty and peer mentors for research guidance and course support.

Infrastructure

GPU & Cloud Credits

[RESOURCE ACCESS] Compute allocation on cloud instances and high-performance GPU clusters for capstone projects.

LEARN THELANGUAGE.