Artificial Intelligence and Data Science is a four-year B.Tech program that combines computer science, mathematics, and data analytics to develop intelligent systems. Students gain practical skills in programming, machine learning, deep learning, and data-driven decision-making while solving real-world problems across various industries.
How the degree evolves year by year
Year 1: Engineering fundamentals, mathematics, programming, and basic computing concepts. Year 2: Core computer science, software development, and system fundamentals. Year 3: Artificial Intelligence, Machine Learning, and Data Science specialization. Year 4: Projects, internships, research, and industry-focused learning.
What you'll study each semester
Build a strong foundation in calculus, linear algebra, and analytical methods essential for computer science, artificial intelligence, and data-driven problem solving.
Learn the principles of physics that support computing hardware, electronic systems, communication technologies, and modern information science.
Study engineering chemistry concepts including semiconductors, advanced materials, batteries, corrosion, and energy systems used in computing technologies.
Develop technical drawing and visualization skills using engineering graphics and CAD tools for engineering design and problem solving.
Understand the fundamentals of electrical circuits, electronic devices, and engineering systems that power modern computing technologies.
Learn Python programming while developing algorithmic thinking, logical reasoning, and computational problem-solving skills for AI and software development.
Gain practical experience with electrical circuits, electronic components, measuring instruments, and essential engineering workshop practices.
Promote physical fitness, mental well-being, healthy habits, and personal development for a balanced academic and professional life.
Develop communication, teamwork, leadership, critical thinking, and professional skills essential for successful engineering careers.
Expand your mathematical knowledge through advanced calculus, probability, and statistical techniques used in artificial intelligence and data science.
Strengthen your understanding of physics concepts and their applications in computing systems, electronics, and modern information technologies.
Explore engineering chemistry topics including advanced materials, electrochemistry, semiconductors, and sustainable technologies.
Learn computer hardware fundamentals, operating systems, networking basics, and introductory web design concepts.
Develop structured programming skills using C while learning algorithms, data handling, and efficient problem-solving techniques.
Understand entrepreneurship, innovation, startups, intellectual property rights, and business opportunities in technology.
Develop healthy lifestyle habits while improving physical fitness, mental health, and personal well-being.
Enhance communication, leadership, teamwork, and professional skills required in engineering and technology careers.
Gain practical experience with computer systems, networking, software tools, and essential IT applications.
Learn mathematical concepts including logic, sets, relations, combinatorics, and graph theory used in computer science.
Study discrete structures that form the mathematical foundation for algorithms, programming, cryptography, and artificial intelligence.
Develop advanced mathematical techniques used in artificial intelligence, machine learning, data analysis, and computational problem solving.
Learn the core concepts of artificial intelligence including intelligent agents, search algorithms, knowledge representation, and reasoning.
Master efficient data organization, algorithms, and problem-solving techniques for building high-performance software applications.
Explore data collection, analysis, visualization, and statistical techniques used to extract meaningful insights from data.
Study digital circuits, logic gates, Boolean algebra, and electronic systems that form the foundation of computing hardware.
Understand economic principles, financial decision-making, and resource management relevant to engineering and technology industries.
Learn professional ethics, social responsibility, and sustainable engineering practices for responsible technology development.
Implement and analyze data structures and algorithms through practical programming exercises and real-world problem solving.
Apply Python programming and statistical techniques to analyze datasets and develop data-driven solutions.
Study advanced mathematical concepts that support machine learning, artificial intelligence, optimization, and data science applications.
Learn database design, SQL, normalization, transactions, and data management techniques for modern applications.
Understand process management, memory management, scheduling, file systems, and operating system architecture.
Explore computer hardware architecture, processors, memory organization, instruction execution, and system performance.
Learn software development methodologies, project management, testing, maintenance, and quality assurance practices.
Understand ethical AI, data privacy, responsible data handling, and legal considerations in data science.
Choose a specialized subject to deepen your knowledge in artificial intelligence, data science, and emerging computing technologies.
Study economic concepts, cost analysis, and decision-making techniques relevant to engineering projects and businesses.
Develop ethical decision-making skills and understand sustainable engineering practices for modern technology solutions.
Build practical skills in artificial intelligence and data science through programming, experimentation, and real-world datasets.
Practice database design, SQL programming, query optimization, and database application development.
Develop practical expertise through laboratory exercises related to your chosen department elective, where applicable.
Learn network architectures, communication protocols, routing, switching, and secure data transmission in modern computer networks.
Study intelligent robotic systems, sensors, automation, and AI techniques used in autonomous machines.
Learn machine learning algorithms, predictive modeling, and data-driven techniques for building intelligent applications.
Explore big data technologies, distributed computing, and analytics techniques for processing large-scale datasets.
Choose a specialized subject to deepen your knowledge in artificial intelligence, data science, and advanced computing technologies.
Gain practical experience in robotics, intelligent systems, sensors, and automation through laboratory experiments.
Apply data analytics techniques using real-world datasets through hands-on programming and visualization exercises.
Learn deep neural networks, computer vision, and advanced AI models for solving complex real-world problems.
Study IoT architecture, smart devices, sensors, cloud integration, and intelligent connected systems.
Learn techniques for extracting valuable insights from large datasets using data warehouses and mining algorithms.
Select an advanced elective to specialize in emerging areas of artificial intelligence and data science.
Choose a subject from another department to broaden interdisciplinary knowledge and technical skills.
Implement deep learning models using modern AI frameworks for image, text, and predictive analytics applications.
Apply theoretical knowledge to solve real-world problems through project-based learning and collaborative development.
Learn mathematical techniques to design, verify, and develop reliable, secure, and error-free software systems.
Develop modern web applications using frontend and backend technologies, databases, and web frameworks.
Choose an advanced specialization in Artificial Intelligence, Data Science, or emerging computing technologies based on your interests.
Select a subject from another department to broaden interdisciplinary knowledge and technical expertise.
Begin your major project by identifying a problem, reviewing literature, and developing the initial solution design.
Present and discuss recent technologies, research papers, or innovations to strengthen technical communication skills.
Learn architectural design patterns, scalable software systems, and enterprise application development principles.
Choose an advanced elective to specialize in cutting-edge areas of Artificial Intelligence and Computer Science.
Explore a subject from another discipline to expand your technical and interdisciplinary knowledge.
Design, develop, and implement a complete software solution to solve a real-world engineering problem.
Demonstrate your overall technical knowledge, project experience, and problem-solving abilities through a final evaluation.
What you can do after completing this course
Where graduates typically go
Design, develop, and deploy intelligent systems that can learn, reason, and automate complex tasks using artificial intelligence and machine learning technologies.
Collect, analyze, and interpret large datasets to uncover valuable insights that help organizations make informed decisions and solve real-world business problems.
Build, train, and optimize machine learning models for applications such as recommendation systems, predictive analytics, fraud detection, and intelligent automation.
Analyze and visualize data to identify trends, create reports, and provide actionable insights that support business growth and decision-making.
Develop dashboards and reporting solutions that transform raw data into meaningful business insights, helping organizations monitor performance and plan strategies.
Develop AI-powered systems that process and interpret images and videos for applications such as autonomous vehicles, medical imaging, and facial recognition.
Create intelligent applications that understand, process, and generate human language, enabling technologies like chatbots, virtual assistants, and language translation.
Design and manage scalable data pipelines and big data platforms that efficiently process, store, and analyze massive volumes of structured and unstructured data.
Where you can go next
Specialize in advanced AI concepts such as intelligent systems, deep learning, robotics, and AI-driven applications for research and industry.
Gain expertise in big data analytics, machine learning, statistical modeling, and data-driven decision-making for solving complex real-world problems.
Develop advanced knowledge of machine learning algorithms, predictive modeling, and AI systems used across various industries.
Combine technical knowledge with business management skills to lead data-driven projects, analytics teams, and strategic business initiatives.
Pursue advanced education at leading international universities with a focus on AI research, innovation, and cutting-edge data science technologies.
Enhance your skills through industry-recognized certifications in AI, machine learning, cloud computing, data analytics, and big data from leading technology providers.
Conduct advanced research in artificial intelligence, machine learning, and data science while contributing to technological innovations and academic development.
Things students often get wrong about this course
The course involves programming, but it also focuses on mathematics, statistics, problem-solving, data analysis, machine learning, and developing intelligent solutions.
A basic understanding of mathematics is helpful, and the required concepts are taught throughout the course with practical applications.
AI is designed to assist humans by improving efficiency and creating new opportunities. Professionals who understand AI technologies will be highly valuable in the future.
AI and data science skills are required across many industries including healthcare, finance, manufacturing, education, retail, and research.
Practical skills, projects, internships, programming experience, and continuous learning are important for building a successful career in AI and Data Science.
Graduates can explore various career paths including AI engineering, machine learning, software development, data analytics, cloud AI, and research.
Artificial Intelligence and Data Science are rapidly growing fields that are becoming essential technologies across industries and will continue to evolve in the future.
Answers to common questions students ask