Advanced expertise in AI, machine learning, and deep learning
M.Tech Computer Science & Engineering(Artificial Intelligence)
The M.Tech in Computer Science & Engineering (Artificial Intelligence) programme is designed to build advanced expertise in AI, machine learning, deep learning, and intelligent computing systems. Students gain hands-on experience through real-world projects, research-driven learning, and industry-focused applications. The programme prepares graduates to develop smart technologies, solve complex computational problems, and lead innovation across emerging digital industries.
Industry-Focused M.Tech in Artificial Intelligence for Future Technology Leaders
The M.Tech in Computer Science & Engineering (Artificial Intelligence) programme offers advanced knowledge in AI technologies, intelligent systems, machine learning, and data-driven computing. Designed with an industry-oriented curriculum, the programme combines theoretical foundations with practical implementation through labs, research, and real-world projects.
Students develop the skills needed to innovate, automate, and lead in rapidly evolving technology sectors powered by artificial intelligence.
Advanced expertise in AI, machine learning, and deep learning
Research-driven learning with industry-focused applications
Hands-on projects, labs, and intelligent systems development
Specialized domains including NLP, computer vision, and generative AI
Strong industry integration through certifications and internships
Pathways to high-growth AI, data science, and research careers
Research-driven learning with industry-focused applications
Hands-on projects, labs, and intelligent systems development
Specialized domains including NLP, computer vision, and generative AI
Strong industry integration through certifications and internships
Pathways to high-growth AI, data science, and research careers
Explore Advanced Domains in Artificial Intelligence & Intelligent Computing
The programme offers specialized tracks designed to match emerging industry demands and future technology trends in Artificial Intelligence. Students can explore advanced domains such as Machine Learning, Deep Learning, Data Science, Computer Vision, Natural Language Processing, Robotics, and Intelligent Automation.
These specializations help learners build domain expertise, research capabilities, and industry-ready technical skills for high-growth AI careers:
Machine Learning & Deep Learning
Build and train intelligent models for prediction, classification, and advanced pattern recognition.
Data Science & Big Data Analytics
Analyse large-scale data to extract insights and drive data-informed decision systems.
Natural Language Processing (NLP)
Develop systems that understand, generate, and process human language at scale.
Computer Vision & Image Processing
Design vision systems for recognition, inspection, and intelligent visual analysis.
Robotics & Intelligent Automation
Apply AI to robotics, control, and intelligent automation across industrial systems.
AI in Cyber Security
Use AI techniques for threat detection, anomaly analysis, and secure intelligent systems.
Cloud Computing & AI Infrastructure
Deploy and scale AI workloads on modern cloud and high-performance infrastructures.
Internet of Things (IoT) & Smart Systems
Build connected intelligent systems that sense, analyse, and act in real time.
Generative AI & Large Language Models (LLMs)
Explore generative models, LLMs, and next-generation AI application development.
Business Intelligence & Predictive Analytics
Apply AI and analytics to forecasting, decision support, and enterprise intelligence.
Each pathway connects advanced AI foundations with research capability and industry-ready application skills.
Why Choose M.Tech CSE (Artificial Intelligence)?
Ideal for students seeking advanced expertise in AI, ML, and intelligent systems
Built for learners who want research-driven learning with real-world projects
Strong industry integration through certifications, workshops, and internships
Pathways into high-growth AI, data science, NLP, and research careers
Industry-Aligned AI Curriculum with Practical Learning & Research Excellence
The curriculum is designed to provide a strong foundation in Artificial Intelligence, advanced computing, and emerging digital technologies through a balanced blend of theory and practical learning. Students engage in hands-on labs, live projects, case studies, research work, and industry-oriented assignments to strengthen real-world problem-solving abilities. The learning experience emphasizes innovation, critical thinking, technical expertise, and collaborative development to prepare graduates for leadership roles in the evolving AI ecosystem.
Programming fundamentals, mathematical foundations for AI, data structures, and computational problem-solving.
Core Focus
- Programming Fundamentals
- Mathematical Foundations for AI
- Data Structures
- Computational Problem-Solving
Industry Exposure & Certifications
The programme offers strong industry integration through global certification platforms, internships, workshops, and experiential learning opportunities in collaboration with leading technology and skill-development organizations. Students gain access to industry-recognized certifications, real-world projects, and professional training programmes that enhance technical expertise and career readiness.
Certification & industry learning partners include Google Certifications, Red Hat Academy, SAP Certification Programs, Internshala Training, EduSkills Foundation, Coursera Learning Programs, Harvard Business Case Studies, LinkedIn Learning, NPTEL Certifications, NSE Academy, and KOSME Industry Programs.
These collaborations help students develop industry-relevant skills, global exposure, and professional competencies aligned with emerging technology trends.
Why This Matters
Google Certifications
Red Hat Academy
SAP Certification Programs
Internshala Training
EduSkills Foundation
Coursera Learning Programs
Harvard Business Case Studies
LinkedIn Learning
NPTEL Certifications
NSE Academy
KOSME Industry Programs
Explore certification opportunities and gain the skills, experience, and credentials that employers value.
Why This Matters
Enhanced employability across AI, data science, and intelligent systems roles
Practical exposure through labs, projects, and research-driven learning
Strong professional network through industry certifications and partnerships
Better understanding of real-world AI applications and intelligent systems
Globally recognized certifications to boost career prospects
Career Opportunities
Graduates of the M.Tech in Computer Science & Engineering (Artificial Intelligence) are well-prepared for high-demand careers in AI, data science, machine learning, and intelligent systems development. The programme equips students with advanced technical and research skills to work in leading IT companies, product-based firms, startups, and research organizations. They can contribute to innovation in automation, predictive analytics, and smart technologies across diverse industries. With strong industry alignment, graduates are ready to take on leadership, development, and research-oriented roles in the global tech ecosystem.
Potential Career Opportunities
Graduates of this programme may pursue roles such as:
- AI/ML Engineer
- Data Scientist
- Machine Learning Engineer
- Deep Learning Engineer
- Data Analyst
- Computer Vision Engineer
- Natural Language Processing (NLP) Engineer
- Robotics Engineer
- Cloud AI Engineer
- Research Scientist (AI & Computing)
Additionally, students can pursue research pathways, specialized certifications, and leadership roles across the global AI ecosystem.
Meet the Faculty
Our faculty members bring strong academic backgrounds, research expertise, and industry experience to guide students throughout their academic journey.
- Artificial Intelligence & ML
- Deep Learning
- Data Science
- Intelligent Systems
With a passionate team of faculty, modern infrastructure, and partnerships with industry, our department cultivates an engaging educational environment that combines academic rigor with practical experience.
At PCU, we prioritize hands-on learning, research-based teaching, and interdisciplinary projects that enable students to innovate and address real-world issues.
View Faculty Profiles
Engineering Labs & Innovation Facilities
The programme provides access to advanced labs and modern learning infrastructure designed to support practical AI and computing education. Students gain hands-on experience in AI & Machine Learning Labs, Data Science Labs, Cloud Computing environments, IoT & Robotics Labs, and High-Performance Computing facilities. Smart classrooms, industry-grade software tools, research centers, and collaborative project spaces create an innovation-driven learning ecosystem that enhances technical skills, experimentation, and real-world application development.
Computer Programming Labs — Practical learning in programming fundamentals, software development, problem-solving, and application design using modern computing tools.
IoT & Embedded Systems Labs — Hands-on experience in smart devices, sensor integration, automation systems, and connected technology applications.
Python Programming Labs — Industry-focused training in Python programming, AI applications, data analysis, machine learning, and intelligent software development.
Explore Campus Facilities
Admissions & Eligibility
Students interested in this programme must fulfill the prescribed academic eligibility criteria and complete the application process through the PCU Admissions Portal. Admissions are based on merit and valid entrance examination scores as per university guidelines. Eligible candidates are encouraged to apply early to secure admission in this future-focused engineering programme.
Applicants must fulfill the following requirements:
Educational Qualification: Candidates must have a B.E. / B.Tech. / M.Sc. in Computer Science, Information Technology, Artificial Intelligence, Data Science, Electronics, or a related discipline from a recognized university.
Minimum Marks Required: A minimum of 45% marks in the qualifying examination (or 40% for reserved category candidates).
Entrance Requirement: Admission is based on a valid GATE score or other national-level entrance examination or university entrance test.
Selection Process: Final admission is based on merit-based selection, considering entrance performance and academic background.
Frequently Asked Questions
Find answers to common questions related to the programme, curriculum, and admission process.
The programme is typically of 2 years, divided into four semesters with a mix of theory, practicals, and project work.
Take the Next Step Toward Your Future in Artificial Intelligence
Take the next step toward building a future in Artificial Intelligence with our M.Tech in Computer Science & Engineering (AI) programme. Gain advanced technical skills, hands-on experience, and industry-ready expertise to excel in high-growth technology careers. Join a learning environment designed to transform ideas into innovation and research into real-world impact. Apply now and become a part of the next generation of AI leaders and innovators.