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The Master of Technology in Artificial Intelligence and Data Science offers a specialized focus to empower students with advanced knowledge and skills crucial for success in the fields of AI and Data Science. The curriculum is meticulously designed to provide a comprehensive academic journey, going beyond theoretical concepts to ensure practical insights and hands-on experience in real-world scenarios.

The core courses lay a strong foundation, covering essential aspects such as the mathematical foundations of computer science, data structures, advanced algorithms, and software engineering methodologies. Complementing these are program-specific electives in AI and Data Science, allowing students to tailor their academic experience based on their career goals. Additionally, open electives offer flexibility and a well-rounded educational experience.

Duration

Two Years & Four Semesters

Why Choose
M. Tech. - AI and Data Science
at Alliance University?
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Dialectical & Interactive Pedagogy
Active engagement through interactive lectures.
AI & Data Science Research Frontier
Avenues for research-oriented projects on advancements in AI and Data Science.
Full-Stack Analytics & Tool Proficiency
Skill development in Apache Hadoop, Python / R programming, and Tableau / Power BI.
Professional Internship Integration
Internship integration for professional experience.
Global Scholarly & Professional Networking
Professional networking in esteemed societies such as CSI, IEEE, and ACM.

Course Category
Applied Probability and Statistics PC
Research Methodology and IPR PC
Advanced Data Structures and Algorithms PC
Distributed Databases PC
Bayesian Machine Learning PE
Fundamentals of Edge Computing PE
High Performance Scientific Computing PE
IoT Sensors & Microcontrollers PE

Course Category
Multicore Computing PC
Network Technologies PC
Reinforcement Learning PE
Edge Security PE
OpenMP PE
IoT Data Analytics PE
Elective - III (Industrial Certification) PC
Term Paper - I PC

Course Category
Generative AI PC
Elective - IV (Industrial Certification - II) PC
Ensembling with TensorFlow PE
TinyML PE
OpenCL PE
Industrial IoT PE
Term Paper - II PC

Course Category
Dissertation PC

Course Categories:

PC : Program Core || PE : Program Elective

The Industry Certifications component is strategically aligned with the Minor Pathways, enabling students to gain globally recognized credentials in their chosen domains of specialization. This integration ensures that students not only acquire academic knowledge but also develop industry-validated skills relevant to emerging technology sectors.

The certification framework is closely mapped to the three key minors—Immersive Game Design and Development, Data Engineering, and Data Analytics—providing students with targeted opportunities to build expertise using industry-standard tools and platforms.

Students pursuing the Immersive Game Design and Development minor are encouraged to undertake certifications related to game engines, 3D modeling, AR/VR development, and interactive media platforms. Example certifications include:

  • Unity Certified Associate/Professional

  • Unreal Engine Developer Certification

  • Blender Certification

  • AR/VR Developer Certifications (Meta, Microsoft Mixed Reality)


Students pursuing the Data Engineering minor can undertake certifications focused on big data technologies, cloud data platforms, ETL pipelines, and distributed data processing frameworks. Representative certifications include:

  • AWS Certified Data Engineer – Associate

  • Google Professional Data Engineer

  • Microsoft Azure Data Engineer Associate

  • Databricks Certified Data Engineer

  • Snowflake SnowPro Certification


Students specializing in the Data Analytics minor are guided toward certifications in data visualization, business intelligence, statistical analysis, and machine learning fundamentals. Example certifications include:

  • Google Data Analytics Professional Certificate

  • Microsoft Power BI Data Analyst Associate

  • IBM Data Analyst Professional Certificate

  • Tableau Desktop Specialist

  • SAS Certified Data Scientist


A key highlight of this framework is its flexible dual-pathway model:

  • Direct Certification Pathway – Students can complete globally recognized certifications aligned with their minor specialization and earn academic recognition with top grades

  • Academic Evaluation Pathway – Structured internal and semester-based assessments ensure equitable evaluation for students following the academic route


The Minor-Aligned Industry Certifications framework emphasizes:

  • Domain-specific skill validation aligned with chosen minor pathways

  • Hands-on learning using industry-relevant tools and platforms

  • Application-oriented knowledge in real-world scenarios

  • Enhanced employability through specialization-driven credentials

  • Continuous upskilling in emerging technologies


By integrating certifications within the Minor Pathways, the program ensures that graduates emerge as specialized, industry-ready professionals with validated expertise, capable of contributing effectively in areas such as immersive technologies, data engineering, and data-driven analytics.
Program Electives

The Program Electives component of the M.Tech Artificial Intelligence & Data Science (AIDS) curriculum provides students with the flexibility to explore advanced and application-oriented domains within AI and data science. It enables learners to deepen their expertise in specific areas of interest while aligning their academic pathway with career goals and emerging industry trends.

The Program Electives emphasize:

  • Domain-specific knowledge and specialization within AI and data science

  • Application of advanced analytical and computational techniques

  • Design and deployment of intelligent, data-driven solutions

  • Interdisciplinary learning across emerging technological areas

  • Industry relevance through practical case studies and project-based learning

By offering a diverse set of elective choices, this component empowers students to tailor their learning experience, enhance technical depth, and prepare for specialized roles in research, industry, and innovation-driven environments.

Program Elective List:

  • Predictive Analytics

  • Time Series Analysis and Forecasting

  • System Design for Robots and Drones

  • Human–Machine Interaction and Interface

  • Financial Data Analytics

  • Healthcare Data Analytics

  • Robotics System Integration

  • Business Intelligence and Analytics

  • Applied Social Network Analysis

PEO (Program Educational Objectives)

PEO 1.

To equip graduates with a strong foundation in computing principles and emerging technologies, enabling them to design, develop, and innovate scalable and intelligent solutions

PEO 2.

To develop graduates with leadership, problem-solving, and entrepreneurial skills to drive technological advancements and contribute to industry, research, and startup ecosystems

PEO 3.

To instill ethical responsibility, sustainability, and a commitment to using technology for addressing global and societal challenges.

PEO 4.

To develop AI-driven problem solvers who can extract insights from vast datasets and build predictive models

PSO (Program Specific Outcomes)

PSO1 :

To design, implement, and optimize intelligent, secure, and scalable computing solutions by integrating emerging technologies .

PSO2 :

To apply computational thinking and interdisciplinary knowledge to develop innovative, ethical, and sustainable technology solutions that address real-world societal and industrial challenges

PSO3 :

To design and implement AI and data analytics solutions that drive decision-making and innovation across industries

PO (Program Outcomes)

PO1. Research and Problem Solving:

An ability to independently carry out research /investigation and development work to solve practical problems

PO2. Technical Communication:

An ability to write and present a substantial technical report/document

PO3. Comprehensive Disciplinary Knowledge:

Students should be able to demonstrate a degree of mastery over the area as per the specialization of the program. The mastery should be at a level higher than the requirements in the appropriate bachelor program

PO4. Design/Development of Solutions:

Graduates can design and develop AI-powered solutions for real-world problems, considering constraints and ethical implications.

PO5. Modern Tool Usage:

Graduates are proficient in using modern AI and data science tools and libraries to handle large datasets and complex models, making them suitable for real-world applications.

PO6. Life Long Learning:

Graduates possess the ability to learn new things and adapt to the rapidly changing field of AI and data science

Program Core

The Program Core forms the foundation of the M.Tech Artificial Intelligence & Data Science (AIDS) curriculum, focusing on developing advanced analytical, computational, and research-oriented expertise in intelligent systems and data-driven technologies. It is carefully designed to enable students to model, analyze, and solve complex real-world problems using cutting-edge AI and data science methodologies aligned with current industry and research demands.

This component includes key subjects such as Applied Probability and Statistics, High Performance Computing for Big Data, Cognitive AI, Decision Support Systems, Virtual Reality, IoT Sustainable Solutions, and Research Methodology and IPR, among others. These courses are structured to provide a strong integration of mathematical foundations, algorithmic thinking, system-level understanding, and applied intelligence.

The Program Core emphasizes:

  • Advanced problem-solving and analytical thinking

  • Design and development of intelligent and scalable systems

  • Data-driven decision-making and predictive modeling

  • Integration of emerging technologies and interdisciplinary approaches

  • Research, innovation, and technical communication skills

With a balanced focus on theoretical depth, practical implementation, and research orientation, the Program Core prepares students for advanced roles in AI and data science, including research, industry applications, and technology innovation.

The Dissertation and Research Component is a central element of the M.Tech Artificial Intelligence & Data Science (AIDS) curriculum, providing students with a comprehensive research experience that emphasizes innovation, analytical rigor, and real-world problem-solving. This component enables students to undertake in-depth, research-driven work addressing complex challenges aligned with industry needs and societal impact.

Students actively engage in advanced research activities including problem formulation, extensive literature review, methodology design, data collection and analysis, model development, experimentation, evaluation, and validation. The work typically focuses on areas such as artificial intelligence, machine learning, big data analytics, intelligent systems, and emerging technologies, leading to the development of scalable solutions and novel contributions.

The research process is guided by faculty mentors and, where applicable, industry experts, with access to advanced computing infrastructure, datasets, cloud platforms, and specialized laboratories. Students are expected to produce high-quality outcomes including a detailed dissertation, technical artifacts, and mandatory publication of their research in reputed conferences or peer-reviewed journals.

The Dissertation and Research Component emphasizes:

  • Advanced research methodology and analytical problem-solving
  • Design and development of innovative AI and data-driven solutions
  • Experimental evaluation, validation, and optimization of models
  • Technical writing, scholarly communication, and dissemination of research
  • Outcomes such as publications, prototypes, patents, and impactful solutions

This structured research experience ensures that graduates develop strong research aptitude, technical depth, and innovation capabilities, preparing them for doctoral studies, R&D roles, and leadership positions in academia, industry, and technology-driven enterprises.

The Capstone Project represents a key integrative component of the M.Tech Artificial Intelligence & Data Science (AIDS) program, providing students with the opportunity to apply advanced knowledge and technical skills to solve complex, real-world problems. Typically undertaken in the later stages of the program, this experience enables students to work individually or in small teams, synthesizing concepts from core and elective courses into innovative and impactful solutions.

The Capstone Project is designed to foster:

  • Advanced analytical thinking and problem-solving

  • Innovation, design thinking, and research-driven development

  • Project planning, execution, and professional practices

  • Application of AI and data science techniques to real-world challenges

Students are required to develop robust models, scalable systems, or data-driven solutions using real-world datasets and contemporary tools. A mandatory outcome of the Capstone Project is the publication of research work in a recognized conference or peer-reviewed journal, ensuring that students gain experience in scholarly writing, validation, and dissemination of their work.

Strong emphasis is placed on originality, technical depth, and research contribution. The outcomes may include prototypes, high-quality technical reports, and publishable research aligned with industry and societal needs.

Serving as a critical, portfolio-defining experience, the Capstone Project significantly enhances students’ preparedness for advanced roles in industry, research, and academia, positioning them as competent professionals capable of contributing to innovation and knowledge creation in intelligent systems and data science.

The Course of Independent Study (CIS) is a distinctive 3-credit academic pathway that offers students a valuable opportunity to engage in research-oriented learning through a faculty-mentored project in place of one course within their curriculum. Designed to nurture intellectual curiosity, innovation, and critical thinking, the course enables students to immerse themselves in hands-on research through laboratories, field-based work, or Centres of Excellence. Under close faculty guidance, students identify research problems, pursue structured inquiry, and develop meaningful academic outcomes. Credits are earned through consistent progress, active participation in review milestones, successful completion of the project, and the preparation and submission of a research paper to a Scopus-indexed journal, conference, or other approved scholarly platform—positioning students for early exposure to high-quality research and scholarly contribution.

The Industry Internship Programme is a vital component of the M.Tech Artificial Intelligence & Data Science (AIDS) curriculum, designed to provide students with advanced industry exposure and hands-on experience in solving real-world, data-driven problems. Integrated within the academic framework, the internship enables students to apply advanced AI, machine learning, and data analytics concepts in professional environments, effectively bridging the gap between academic research and industry practices.

Typically undertaken during the later phase of the program, the internship offers opportunities to work with leading technology companies, startups, research labs, and innovation centers across domains such as artificial intelligence, data science, big data engineering, cloud computing, cybersecurity, intelligent systems, and automation. Students engage in live projects, research-driven development, and collaborative problem-solving, gaining insights into modern tools, frameworks, and deployment practices.

The programme emphasizes:

  • Application of advanced AI and data science techniques to real-world challenges
  • Development of professional, communication, and interdisciplinary teamwork skills
  • Exposure to industry-standard tools, platforms, and deployment environments
  • Hands-on experience with large-scale data systems and intelligent applications
  • Strengthening research aptitude and innovation through practical engagement

Guided by both academic mentors and industry supervisors, students are evaluated based on their technical contributions, problem-solving ability, innovation, and professional conduct. The internship may also lead to research outcomes, technical reports, or contributions aligned with conference or journal publications, reinforcing the research-oriented nature of the program.

The Industry Internship Programme plays a crucial role in preparing students for advanced careers in AI and data science, enabling them to transition effectively into roles in industry, research organizations, and innovation-driven enterprises as highly skilled and industry-ready professionals.

STUDY ABROAD OPTIONS

International Mobility

Experience global education through our international study opportunities designed to broaden academic perspectives and cultural understanding. These programmes enable students to study at partner universities abroad, gain international exposure, and develop the global competencies needed to succeed in an interconnected world.

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An opportunity that lets students begin their degree at Alliance University (1 or 2 years) and then transfer to a foreign university to complete and earn their degree internationally.

Explore the World: Study a semester abroad, earn transferable credits, and gain global insights while experiencing a new culture and expanding your skills.

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Alliance University welcomes students from across the world to study, collaborate, and thrive in a truly global learning ecosystem. We combine academic rigour with industry exposure, modern infrastructure with personalised support, and global perspectives with Indian values.

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Category Eligibility Criteria
General (X, XII, Undergraduate), B.E. / B.Tech. in Computer Science or Information Technology OR MCA with minimum 50% marks or equivalent CGPA
Reserved Categories 5% relaxation for SC / ST candidates

Program duration
Entry Level Program Duration
Entry Level Two Years / Four Semesters

ACCEPTED TEST SCORES
JEE Main
SAT
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JEE Main
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JEE Main
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Particulars Indian Nationals Foreign Nationals
Registration Fee (Fee for Learners Value Proposition Course Virtual) ₹25,000 $500
First Installment ₹1,75,000 $2,100
Second Installment ₹2,00,000 $2,550
Total program Fee ₹4,00,000 $5,150

 

Category Eligibility Scholarship
SC / ST 60% & above (X, XII, Undergraduate) + 70% & above National-Level Entrance Test 20% Tuition Fee Waiver
Differently-Abled 50% & above (X, XII, Undergraduate) 50% Tuition Fee Waiver
Defence & Paramilitary 60% & above (X, XII, Undergraduate)  + 70% & above Entrance Test 15% Tuition Fee Waiver
International-Level Sportsperson 50% & above (X & XII) 100% Tuition Fee Waiver
National-Level Sportsperson 50% & above (X & XII) 50% Tuition Fee Waiver
Domicile Students 60% & above (X & XII) + 70% & above Entrance Test 5% Tuition Fee Waiver
Policy Conditions Scholarships subject to approval and documentation. Limited seats.

 

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Steps Description
Step 1 Submit Online Application
Step 2 Pay Application Fee — ₹1000 (US$50 for foreign nationals)
Step 3 Appear for Entrance/Selection Process (as applicable)
Step 4 Personal Interview assessment
Step 5 Selection based on overall profile & performance
Start your application now

Living Spaces That Inspire Belonging

EXPLORE OUR HOSTELS

Comfort, safety, and community form the foundation of campus living. Our residential halls are thoughtfully designed to create a sense of belonging—offering a welcoming environment where students can study, unwind, and build lifelong friendships.

Separate hostels
for boys and girls

Student-friendly
common areas

Spacious rooms
(single, double, or triple occupancy)

Dedicated wardens
and support teams

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FACULTY

Everything You Need to Know

Is the M. Tech. in Artificial Intelligence and Data Science program industry-oriented?
Yes. The M. Tech. in Artificial Intelligence and Data Science program is designed to be highly industry-oriented, with a strong emphasis on practical skills, hands-on projects, and real-world applications. Students work with industry-relevant tools and technologies such as Python, R, and SQL while exploring advanced AI and machine learning concepts through research projects, internships, and industry collaborations.
What is the duration and structure of the M. Tech. in Artificial Intelligence and Data Science program?
The M. Tech. in Artificial Intelligence and Data Science program offered by the Alliance School of Advanced Computing is a two-year, full-time postgraduate degree program structured across four semesters.
What core subjects and advanced technologies are covered in the program?
The curriculum covers core computer science foundations such as Algorithms, Data Structures, and Mathematics, along with advanced domains including Machine Learning, Deep Learning, Big Data Analytics, Natural Language Processing, Computer Vision, Statistical Modelling, and real-world data engineering tools. The program also emphasises practical learning through laboratories and industry projects.
What career opportunities are available after completing the M. Tech. in Artificial Intelligence and Data Science program?
Graduates can pursue high-demand roles such as Machine Learning Engineer, Data Scientist, AI Engineer, Big Data Engineer, Data Architect, AI Research Scientist, and Analytics Consultant across industries including technology, healthcare, finance, consulting, and e-commerce.
What are the eligibility criteria for pursuing the M. Tech. in Artificial Intelligence and Data Science program?
Applicants must hold a B.E. / B. Tech. degree or MCA in Computer Science, Information Technology, or a related discipline with a minimum of 50% aggregate marks (45% for SC/ST candidates). Candidates should also possess valid scores in Karnataka-PGCET, AUET, or equivalent entrance examinations, along with clearing all academic backlogs.
Are students exposed to research opportunities during the program?
Yes. Students are actively involved in research-oriented learning through project assignments, innovation labs, industry collaborations, and hands-on exploration in areas such as Machine Learning, Deep Learning, and Big Data Analytics. The program also encourages research publications and advanced problem-solving.
How is the program integrated with Cloud, IoT, and Big Data technologies?
The program integrates Artificial Intelligence and Data Science with Cloud Computing, IoT, and Big Data technologies to create intelligent and scalable data-driven systems. Students learn how to process, analyse, and deploy data solutions across interconnected platforms and modern computing ecosystems.
What certifications or skill-building workshops are offered along with the program?
Students gain access to specialised electives in areas such as Deep Learning, Generative AI, Natural Language Processing, Computer Vision, Cloud Data Analytics, and Cyber Security. In addition, the University offers workshops on communication, aptitude, personality development, and research writing through the Career Advancement and Networking (CAN) cell and Coursera-based learning opportunities.
What is the global demand for AI and Data Science experts with an M. Tech. degree?
The global demand for Artificial Intelligence and Data Science professionals is exceptionally high across industries such as technology, healthcare, finance, manufacturing, and e-commerce. Countries including the United States, United Kingdom, Canada, Germany, and India continue to seek highly skilled AI and data science experts for advanced technical and research-oriented roles.
Is Alliance University’s M. Tech. in Artificial Intelligence and Data Science suitable for careers in Generative AI or real-time analytics?
Yes. The program is designed to equip students with advanced practical and analytical skills in emerging areas such as Generative AI, intelligent automation, and real-time analytics, preparing them for specialised careers in rapidly evolving AI-driven industries.
Does the program offer internships or projects with leading AI and data-driven companies?
Yes. The program includes internships, live industry projects, and mentorship opportunities facilitated through the Career Advancement and Networking (CAN) department. Students gain exposure to real-world applications through collaborations with organisations in technology, consulting, and analytics sectors.
What is the selection process for admission to the M. Tech. in Artificial Intelligence and Data Science program?
Applicants are required to submit an online application form. Shortlisted candidates must complete an online aptitude test followed by a personal interview as part of the admission process.
Are scholarships or financial aid available for students?
Yes. Alliance University offers merit-based scholarships and financial assistance for eligible M. Tech. in Artificial Intelligence and Data Science students. Scholarships are awarded based on academic performance and other eligibility criteria defined by the University.
How does the program prepare students for roles in AI engineering or data architecture?
The program builds strong foundations in Artificial Intelligence, Machine Learning, Big Data, and statistical modelling through specialised coursework, industry tools, and hands-on projects. This enables students to design intelligent systems, manage large-scale data architectures, and solve complex analytical challenges effectively.
What is the fee structure for the M. Tech. in Artificial Intelligence and Data Science program?
The program fee for the M. Tech. in Artificial Intelligence and Data Science at Alliance University is approximately Rs. 4 lakhs for the complete two-year duration, payable in instalments. Hostel fees and other applicable charges are additional.
What is the duration of the M. Tech. in Artificial Intelligence & Data Science program? +

The program spans two years across four semesters.

Who is eligible to apply? +

B.E. / B.Tech. with minimum 50% marks or equivalent in CGPA in Computer Science/Information Technology or MCA.

How is the admission process conducted? +

Selection is based on academic merit, entrance test performance, oral presentation, and personal interview.

Does the program include research exposure? +

Yes. Students undertake research-oriented projects and guided academic inquiry.

Are internships part of the program? +

Yes. Internship opportunities provide applied industry experience.

What skills will students develop? +

AI/ML modelling, data analytics, big data tools, programming in Python/R, and professional research capability.

What careers can graduates pursue? +

AI Engineer, Data Scientist, Research Scientist, Machine Learning Specialist, Analytics Consultant, Product Engineer, and PhD-track Researcher.

Are scholarships available? +

Yes. Category-based tuition fee waivers are available as per university policy.

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