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B. Tech. in Computer Science and Engineering (Quantum Computing & Technologies)

Overview

The program is built on a simple premise: quantum computing cannot be meaningfully understood or engineered through theory and simulation alone. It therefore combines rigorous training in mathematics, physics, and computation with direct interaction with multi-qubit quantum hardware, enabling students to engage with the actual behaviour and limitations of quantum systems.

As students progress, they move from foundational concepts to qubit architectures, quantum algorithms, and error-prone implementations, alongside continuous engagement in structured research. This integration of theory, systems, and experimentation develops the ability to work on real quantum problems rather than only studying established models.

The program is designed to address a central constraint in the field: the shortage of engineers trained to work with quantum systems under real conditions. By integrating theory, hardware access, and sustained research, it prepares students to understand and build quantum systems as they exist in practice.

Duration

4 years (8 semesters), including elective projects, internships, and research components

Commence of the course


Course Duration

4 Years


Mode of Study

Eligibility


Passed 10+2 or equivalent from a recognized Board / Council with a minimum of 50% marks (45% for SC/ST) in Physics & Mathematics as compulsory subjects along with one of the Chemistry / Biotechnology / Biology / Technical Vocational Subjects.

Valid score in JEE (Main / Advanced), AUQET (Alliance University QUASAR Entrance Test) or Karnataka State-Level entrance examinations.


Key Features

Access to 8-qubit quantum systems for executing circuits and analyzing measurement outcomes.

Study of noise, decoherence, and error rates through observed behaviour in physical quantum systems.

Implementation of quantum algorithms under hardware constraints such as circuit depth and gate fidelity.

Coverage of quantum error correction methods in near-term, non-fault-tolerant architectures.

Introduction to post-quantum cryptographic approaches and their computational implications.

Exposure to hybrid quantum-classical workflows, including variational and optimisation techniques.

Structured research leading to technical documentation and publication-oriented outcomes.

Curriculum Architecture

Semester Stage Key Competencies
Semester 1-2 Foundation Calculus, linear algebra, probability, scientific computing, cognitive frameworks, data structures
Semester 3-4 Systems Core Electronic devices, systems, AI for mathematical embedded engineering, foundations quantum systems
Semester 5-6 Quantum Core Quantum mechanics, qubit models, algorithms, information theory, hardware architectures, PQC, error correction
Semester 7-8 Advanced and Capstone Quantum communications, decoherence, photonics, HPC, programme electives, Grand Capstone (12 credits)

Program Structure

Career Pathways and Graduate Outcomes

Industry Roles
  • Machine Learning Engineer
  • AI Product / Research Scientist
  • Data Scientist at top tech firms
  • MLOps / AI Infrastructure Engineer
  • Generative AI Developer and
  • Entrepreneur AI Safety and Ethics Researcher
Sectors and Applications
  • AI-native product companies (India and global)
  • Healthcare AI and biotech firms
  • Financial services and fintech
  • Autonomous systems companies
  • Government AI initiatives and think-tanks
  • Doctoral / research programs in AI

Contact for Admissions

ALLIANCE UNIVERSITY - QUANTUM AI SCHOOL FOR ADVANCED RESEARCH

SR. No. 2/1C, Near Infosys Drive Gate No.6, Electronic City Phase 1, Bangalore 560 100