Computer Science and Engineering (Artificial Intelligence) focuses on designing intelligent systems capable of learning, reasoning and solving real-world problems. The program combines core computer science with artificial intelligence, machine learning, data science, deep learning and intelligent automation to prepare students for the rapidly evolving AI industry.
How the degree evolves year by year
Students begin with mathematics, programming and computer science fundamentals before studying data structures, algorithms, machine learning, deep learning, computer vision, natural language processing and intelligent systems. Advanced electives, laboratories and projects prepare graduates for careers in AI, software development, research and data-driven industries.
What you'll study each semester
Build a strong mathematical foundation through calculus, linear algebra and analytical techniques used in computer science and artificial intelligence.
Study the principles of mechanics, electricity, magnetism, optics and modern physics that support computing and information technologies.
Understand engineering chemistry concepts including materials, semiconductors, corrosion and energy storage systems.
Learn engineering drawing principles and create technical drawings using computer-aided design tools.
Study the fundamentals of electrical circuits, electronic devices and basic electrical engineering concepts.
Develop problem-solving skills and learn Python programming for algorithm design and computational thinking.
Gain practical experience with electrical circuits, electronic components and basic engineering workshop practices.
Develop awareness of physical fitness, mental well-being and healthy lifestyle practices.
Develop communication, teamwork, leadership and professional skills essential for engineering careers.
Study advanced mathematical concepts including differential equations, probability and numerical methods for computing applications.
Explore advanced physics concepts relevant to computing, electronics and modern information systems.
Learn engineering chemistry concepts related to materials, nanotechnology and electronic applications.
Understand computer hardware fundamentals, operating systems, networking basics and introductory web design concepts.
Learn structured programming, problem solving and software development using the C programming language.
Understand entrepreneurship, innovation, intellectual property rights and business fundamentals for engineers.
Promote physical fitness, mental health and overall well-being through healthy lifestyle practices.
Strengthen communication, interpersonal skills, teamwork and professional ethics.
Gain hands-on experience with operating systems, productivity software, networking and essential IT tools.
Study logic, sets, relations, graphs and combinatorics that form the mathematical foundation of computer science and artificial intelligence.
Study advanced mathematical concepts including probability, statistics and numerical methods used in computer science and artificial intelligence.
Learn automata theory, formal languages, computability and computational complexity that form the foundation of computer science.
Study efficient data organization, algorithm design and problem-solving techniques for software and AI applications.
Learn object-oriented programming concepts including classes, inheritance, polymorphism and software design principles.
Understand digital logic circuits, Boolean algebra and electronic systems used in modern computing devices.
Learn engineering economics, project costing and financial decision-making for engineering projects.
Develop professional ethics and understand sustainable engineering practices in technology and society.
Implement and analyze data structures and algorithms through practical programming exercises.
Develop Python programming skills for software development, data analysis and artificial intelligence applications.
Study advanced mathematical methods used in artificial intelligence, machine learning and data science.
Learn database design, SQL, normalization and database management techniques for modern applications.
Understand process management, memory management, file systems and operating system design principles.
Study computer hardware organization, processor architecture and system performance optimization.
Understand engineering economics, financial analysis and project management principles.
Learn ethical engineering practices, professional responsibility and sustainable technology development.
Perform practical experiments on process scheduling, memory management and operating system concepts.
Gain hands-on experience in database creation, SQL programming and database application development.
Choose any ONE Professional Elective offered by the department to specialize in areas such as Software Engineering, Pattern Recognition, Functional Programming, Nature Inspired Computing, Soft Computing or Algorithm Design.
Learn the fundamentals of computer communication, network architecture, protocols and data transmission techniques used in modern computer systems.
Understand the basic concepts of artificial intelligence including intelligent agents, problem solving, knowledge representation and AI applications.
Study machine learning algorithms, models and techniques that enable computers to learn from data and make predictions.
Learn advanced graph theory concepts and algorithms used for solving complex problems in computer science and artificial intelligence.
Gain practical experience in implementing artificial intelligence algorithms and solving problems using programming techniques.
Perform practical experiments on machine learning algorithms, data analysis methods and model development techniques.
Choose any ONE Professional Elective offered by the department to specialize in areas such as Software Engineering, Pattern Recognition, Functional Programming, Nature Inspired Computing, Soft Computing or Algorithm Design.
Study intelligent agents, their architecture and applications in developing autonomous AI-based systems.
Learn robotics concepts, automation systems, robot programming and intelligent control techniques used in modern applications.
Learn deep learning concepts, neural network architectures and techniques used in advanced artificial intelligence applications.
Gain practical experience in robotics concepts, robot programming, automation techniques and intelligent control systems.
Choose any ONE Professional Elective offered by the department to specialize in areas such as Software Engineering, Pattern Recognition, Functional Programming, Nature Inspired Computing, Soft Computing or Algorithm Design.
Choose any ONE Open Elective from the university's approved interdisciplinary courses to broaden your knowledge in areas such as Intelligent Transportation Systems, Environmental Safety, Watershed Management or Engineering Finance.
Choose any ONE Professional Elective offered by the department to specialize in areas such as Software Engineering, Pattern Recognition, Functional Programming, Nature Inspired Computing, Soft Computing or Algorithm Design.
Choose any ONE Open Elective from the university's approved interdisciplinary courses to broaden your knowledge in areas such as Intelligent Transportation Systems, Environmental Safety, Watershed Management or Engineering Finance.
Choose any ONE Professional Elective offered by the department to specialize in areas such as Software Engineering, Pattern Recognition, Functional Programming, Nature Inspired Computing, Soft Computing or Algorithm Design.
Choose any ONE Open Elective from the university's approved interdisciplinary courses to broaden your knowledge beyond Civil Engineering.
What you can do after completing this course
Where graduates typically go
Develop intelligent systems using artificial intelligence, machine learning and deep learning technologies.
Build, train and deploy machine learning models for real-world applications.
Analyze large datasets to extract insights and develop predictive models for business and research.
Design, develop and maintain software applications for web, mobile and enterprise platforms.
Develop AI systems for image processing, object detection, facial recognition and autonomous technologies.
Build intelligent applications such as chatbots, virtual assistants and language translation systems.
Research and develop advanced artificial intelligence algorithms and intelligent computing solutions.
Deploy, manage and scale AI applications using cloud computing platforms and modern AI services.
Where you can go next
Specialize in advanced AI topics including intelligent systems, deep learning and autonomous technologies.
Gain advanced knowledge in software engineering, algorithms, distributed systems and advanced computing.
Pursue higher education in Artificial Intelligence, Machine Learning, Data Science or Computer Science at leading international universities.
Combine technical expertise with business and management skills for leadership and technology management roles.
Qualify through GATE for M.Tech admissions, research opportunities and selected Public Sector Undertaking (PSU) careers.
Conduct advanced research in Artificial Intelligence, Machine Learning, Robotics, Computer Vision or Natural Language Processing.
Enhance expertise through professional certifications in AI, Cloud Computing, Data Science, Cybersecurity and Generative AI.
Things students often get wrong about this course
AI assists developers by automating repetitive tasks, but skilled programmers are still essential for designing, developing and maintaining intelligent systems.
The program covers core Computer Science subjects along with AI, including programming, algorithms, databases, operating systems, networking and software engineering.
Basic mathematical knowledge is important, and the required concepts are taught throughout the course as students progress.
AI professionals are in high demand across industries including healthcare, finance, manufacturing, cybersecurity, education and autonomous systems.
AI Engineers develop intelligent software, recommendation systems, chatbots, computer vision applications, predictive models and many other AI-powered solutions beyond robotics.
Answers to common questions students ask