Strong foundation in programming, data structures, and algorithms
B.Tech Computer Science & Engineering(Artificial Intelligence & Machine Learning)
Programme Overview
The B.Tech in Computer Science & Engineering (Artificial Intelligence & Machine Learning) is designed to equip students with a strong foundation in core computing principles along with advanced knowledge in AI and ML technologies. The programme focuses on developing intelligent systems capable of solving real-world problems through data-driven decision-making.
Students gain hands-on experience in key areas such as machine learning, deep learning, data science, computer vision, and natural language processing. The curriculum integrates theoretical concepts with practical applications through lab work, industry projects, and internships.
With a strong emphasis on innovation and emerging technologies, the programme prepares students to build scalable AI solutions, work with large datasets, and contribute to cutting-edge advancements in technology. Learners are also encouraged to develop critical thinking, problem-solving abilities, and research-oriented skills.
Strong foundation in programming, data structures, and algorithms
Specialized courses in Artificial Intelligence & Machine Learning
Hands-on learning through projects, labs, and internships
Exposure to real-world problem solving using data
Focus on emerging technologies like Deep Learning, NLP, and Computer Vision
Opportunities for research, innovation, and industry collaboration
Specialized courses in Artificial Intelligence & Machine Learning
Hands-on learning through projects, labs, and internships
Exposure to real-world problem solving using data
Focus on emerging technologies like Deep Learning, NLP, and Computer Vision
Opportunities for research, innovation, and industry collaboration
Specializations Offered
Students can choose specialized pathways that align with their career interests, industry trends, and emerging technological domains. Each track is designed to provide in-depth knowledge, practical exposure, and industry-relevant skills.
Focus on designing intelligent systems, developing machine learning models, and building AI-driven applications:
Machine Learning Algorithms
Supervised and unsupervised learning techniques for data-driven decision-making.
Deep Learning & Neural Networks
Build and train neural networks for complex pattern recognition and prediction.
Natural Language Processing (NLP)
Process and understand human language for intelligent text and speech applications.
Computer Vision
Develop systems that interpret visual data for real-world AI applications.
Reinforcement Learning
Train intelligent agents to make decisions through rewards and real-world feedback.
AI Model Deployment & Optimization
Deploy, optimize, and scale AI models for production environments.
Students gain expertise in deep learning, neural networks, computer vision, natural language processing, and reinforcement learning—preparing them for careers in AI-driven industries.
Why Choose AI & ML?
Ideal for students interested in AI, data science, and automation
Built for learners who enjoy problem-solving and logical thinking
Pathways into future technologies and innovation-driven industries
Enhance employability with job-ready AI and ML skills
Curriculum & Learning Experience
The curriculum is thoughtfully designed to blend strong foundational knowledge with advanced concepts in Artificial Intelligence and Machine Learning. It emphasizes both theoretical understanding and practical implementation through hands-on labs, projects, and industry exposure, ensuring students are well-prepared for real-world challenges.
Year 1 – Foundations
Programming basics, engineering mathematics, digital logic.
Year 2 – Core Computing
Data structures, operating systems, database systems.
Year 3 – Advanced Learning
Machine learning, cloud computing, specialized electives.
Year 4 – Industry Integration
Capstone project and internships.
Course Code
UBTFY101
Course Name
Linear Algebra & Differential Calculus
Course Code
UBTFY103I/UBTFY104I
Course Name
Engineering Physics / Engineering Chemistry
Course Code
UBTFY104I/UBTFY106I
Course Name
Basic Electronics Engineering / Basic Electrical Engineering
Course Code
UBTFY107I/UBTFY113I
Course Name
Engineering Graphics & Design / Web Programming
Course Code
UBTFY114
Course Name
Procedural Programming
Course Code
UBTFY110I/UBTFY115I
Course Name
IT Workshop / Fab Workshop
Course Code
UEG101
Course Name
Applied Communication
Course Code
ACUHV101I/ACIKSET101I
Course Name
UHV-1: Professional Ethics / IKS: Indian Science, Engineering & Technology
Course Code
UBTFY101
Course Name
Linear Algebra & Differential Calculus
Course Code
UBTFY103I/UBTFY104I
Course Name
Engineering Physics / Engineering Chemistry
Course Code
UBTFY104I/UBTFY106I
Course Name
Basic Electronics Engineering / Basic Electrical Engineering
Course Code
UBTFY107I/UBTFY113I
Course Name
Engineering Graphics & Design / Web Programming
Course Code
UBTFY114
Course Name
Procedural Programming
Course Code
UBTFY110I/UBTFY115I
Course Name
IT Workshop / Fab Workshop
Course Code
UEG101
Course Name
Applied Communication
Course Code
ACUHV101I/ACIKSET101I
Course Name
UHV-1: Professional Ethics / IKS: Indian Science, Engineering & Technology
Learning Experience
Hands-on Approach
- Practical lab sessions for every major subject
- Real-world datasets and problem-solving
- Mini and major project-based learning
Industry Exposure
- Internships with industry partners
- Guest lectures by experts
- Workshops on latest tools & technologies
Skill Development
- Coding, analytical, and problem-solving skills
- Teamwork and project management
- Innovation and research orientation
Industry Exposure & Certifications
PCU integrates industry-recognized certifications and real-world projects into the curriculum to help students develop job-ready skills.
Certification opportunities may include training programmes from platforms such as Red Hat and Coursera.
Students also benefit from internships, industry workshops, and expert sessions conducted by professionals.
Why This Matters
Certification programmes from platforms like Red Hat and Coursera
Courses in AI, Machine Learning, Cloud Computing, and Data Science
Industry-aligned training modules integrated into the curriculum
Opportunities to gain hands-on experience with real-world tools
Internships, industry workshops, and expert sessions by professionals
Apply Now and gain the skills, experience, and certifications that employers value.
Why This Matters
Enhanced employability and industry readiness
Practical exposure beyond classroom learning
Strong professional network and mentorship opportunities
Better understanding of real-world applications of AI & ML
Globally recognized certifications to boost career prospects
Career Outcomes
The CSE (Artificial Intelligence & Machine Learning) programme is designed to align with current industry demands by integrating certification-based learning, real-world projects, and continuous industry interaction. Students are equipped with job-ready skills through practical exposure to tools, technologies, and professional practices followed in the industry.
Students are encouraged to earn globally recognized certifications to enhance their technical expertise and employability.
- Certification programmes from platforms like Red Hat and Coursera
- Courses in AI, Machine Learning, Cloud Computing, and Data Science
- Industry-aligned training modules integrated into the curriculum
- Opportunities to gain hands-on experience with real-world tools
Benefits to Students
- Enhanced employability and industry readiness
- Practical exposure beyond classroom learning
- Strong professional network and mentorship opportunities
- Better understanding of real-world applications of AI & ML
View Placement Highlights
Faculty & Academic Mentors
The Department of Computer Science & Engineering (Artificial Intelligence & Machine Learning) is supported by a team of highly qualified and experienced faculty members. Our educators are dedicated to delivering quality education, mentoring students, and contributing to research and innovation in emerging technologies.
- Artificial Intelligence & Machine Learning
- Data Science
- Blockchain
- Cybersecurity
- Cloud Computing
- Deep Learning & Computer Vision
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
AI & ML Labs & Innovation Facilities
Students gain hands-on experience through state-of-the-art laboratories and innovation spaces designed to support experimentation, research, and collaborative learning. The department provides a technology-driven environment where students can apply theoretical concepts to real-world problems.
AI & ML Lab for machine learning, deep learning, NLP, and computer vision
Advanced Computing Lab for programming, cloud, and big data analytics
Innovation & Project Studio for mini/major projects and hackathons
Support for startup initiatives, research, and team-based problem solving
Industry tools including Python, TensorFlow, AWS, and simulation platforms
Explore Campus Facilities
Admissions & Eligibility
Students aspiring to pursue the B.Tech in Computer Science & Engineering (Artificial Intelligence & Machine Learning) must meet the academic eligibility criteria and complete the admission process through the official university admissions portal. The process is designed to be simple, transparent, and student-friendly.
Applicants must fulfill the following requirements:
Completion of 10+2 (Higher Secondary Education) or equivalent
Mandatory subjects: Physics and Mathematics
Minimum qualifying marks as per university/regulatory guidelines
Valid score in relevant entrance examination (if applicable as per university norms)
Frequently Asked Questions
Find answers to common questions about the B.Tech Computer Science & Engineering (Artificial Intelligence & Machine Learning) programme, including admissions, curriculum, career opportunities, and student life.
The programme duration is 4 years (8 semesters), designed to provide both foundational and advanced knowledge in computer science and AI technologies.
Start Your AI & ML Engineering Journey at PCU
Take the first step towards a successful career in Artificial Intelligence and Machine Learning. Join a dynamic and future-focused learning environment that empowers you with technical expertise, practical skills, and industry exposure to become a technology leader of tomorrow.