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B.Tech Computer Science and Engineering- Artificial Intelligence and Machine Learning
Program details
The B. Tech in Artificial Intelligence and Machine Learning program at UPES is a unique offering in collaboration with IBM, designed by a team of academic experts and industry professionals. Students are exposed to real-life applications of artificial intelligence and machine learning (AIML) from the beginning of their semesters, with a strong emphasis on probability and applied statistics. This allows students to think about AIML applications in both practical and theoretical ways, enabling them to optimize models and solutions.
The curriculum includes four projects, two of which are minor and two are major. In the major projects, students work on real-world problems and provide optimized solutions under the guidance of experienced mentors. Additionally, students are required to complete a three-month industry internship, where they work on real-world problems and have the opportunity to secure pre-placement offers. The faculty also involve bachelor's students in research work, providing opportunities to work on international and national projects of importance. Students are also encouraged to file patents independently or with the support of faculty members.
UPES also provides a platform for students to start their own businesses, and many students have successfully launched startups with good recognition. An excellent example is the first batch AIML student Mr. Nikunj Bansal, who worked with a faculty mentor on a prestigious international project and is a co-author of the work published in Scientific Reports, Nature Publishing Group. Overall, the B. Tech in Artificial Intelligence and Machine Learning program at UPES offers a comprehensive education that prepares students for successful careers in the field of artificial intelligence and machine learning.
Program Highlights
- The B. Tech in Artificial Intelligence and Machine Learning program emphasizes on the applications of AIML, followed by statistics, discrete mathematics, and probability to understand the core of artificial intelligence and machine learning.
- The program focuses on mathematical derivation of ML models and their implementation for real-time applications and labelled data.
- The students participate in research work with various faculties to learn about novel and actual usage of these concepts.
- The B. Tech in Artificial Intelligence and Machine Learning program includes four projects and one internship with strong problem definition, scrutinized by senior faculties.
- Specialized subjects taught include Introduction to Artificial Intelligence, Machine Learning, Neural Networks, Algorithm for Intelligent Systems and Robotics, Cognitive Analytics, Computational Linguistics and Natural Language Processing, Pattern Recognition and Anomaly Detection, and Application of machine learning in industries.
- The program prepares students with a strong foundation in AI and ML, as well as practical experience in applying these concepts to real-world problems.
Scope / Industry Trends
The future scope of B. Tech in Artificial Intelligence and Machine Learning is promising as enterprises that adopt AI engineering practices are expected to outperform their peers by at least 25% in terms of operationalizing AI models by 2026. AI is becoming an essential technology in various fields, including self-driven vehicles, digital disease diagnostics, and robot assistance. The demand for qualified artificial intelligence engineers has more than doubled in recent years, creating endless opportunities for those interested in research and development in AI. According to Gartner's study, there could be up to 2.3 million prospects for AI professionals by 2020, and the number of job vacancies in AI has doubled in the last three years. Machine learning developers, software technologists, and data scientists are the most in-demand roles in AI, according to a related study by Indeed.
Career Opportunities
A B. Tech in Artificial Intelligence and Machine Learning requires proficiency in programming languages like Python, R, or C++. The demand for AI engineers is rising, resulting in lucrative pay scales. To test and improve their skills, individuals can undertake personal projects. Despite the initial daunting requirements, the field of artificial intelligence has many areas to explore, and attaining the necessary skills and specializations may take time. The key to a successful career in artificial intelligence is a passion for learning and taking risks. Prospective individuals should not be discouraged by the initial challenges and instead focus on developing an interest in the field.
Graduates of the B. Tech in Artificial Intelligence and Machine Learning program can pursue several popular career paths, including:
- Data Scientist
- Machine Learning Engineer
- Research Scientist
- Business Intelligence Developer
- AI Data Analyst
- Big data engineering
- Robotics Scientist
- AI engineer
Placements
The adoption of new artificial intelligence and machine learning technologies is increasing rapidly, and it is expected to produce some of the most revolutionary inventions of this century, including self-driven vehicles, robot assistance, and digital disease diagnostics. As a result, the demand for qualified engineers in the field of AI has more than doubled in recent years, offering endless opportunities for professionals who want to lead research and development in AI. Pursuing a B. Tech in Artificial Intelligence and Machine Learning can lead to a highly rewarding career with a promising average CTC of Rs. 10.25 lakhs per annum and the potential for a highest CTC of Rs. 40 lakhs per annum. Companies like Accenture, Cognizant, Infosys, Samsung R&D, Jio Platforms Limited, Barclays India, 3 Pillar Global, PwC, Schneider Electric, and others have recruited graduates from this program. Therefore, AI & ML engineering can open up a vast number of career opportunities for the future.
Fee Structure
Click here for detailed Fee Structure.
Curriculum
Semester 1
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Linux Lab | 0 | 0 | 4 | 2 |
| Programming in C | 0 | 0 | 3 | 3 |
| Programming in C Lab | 0 | 0 | 4 | 2 |
| Problem Solving | 2 | 0 | 0 | 2 |
| Living Conversation | 2 | 0 | 0 | 2 |
| Advanced Engineering Mathematics – I | 3 | 1 | 0 | 4 |
| Environmental Sustainability and Climate Change - I | 2 | 0 | 0 | 2 |
| Physics for Computer Engineers | 4 | 0 | 0 | 4 |
| Physics for Computer Engineers Lab | 0 | 0 | 2 | 1 |
| TOTAL | 22 |
Semester 2
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Computer organization and Architecture | 3 | 0 | 0 | 3 |
| Data Structures and algorithms | 4 | 0 | 0 | 4 |
| Data Structures and algorithms Lab | 0 | 0 | 2 | 1 |
| Python programming | 2 | 0 | 0 | 2 |
| Python programming Lab | 0 | 0 | 4 | 2 |
| Digital Electronics | 3 | 0 | 0 | 3 |
| Critical Thinking and Writing | 2 | 0 | 0 | 2 |
| Advanced Engineering Mathematics – II | 3 | 1 | 0 | 4 |
| Environmental Sustainability and Climate Change - II | 2 | 0 | 0 | 2 |
| TOTAL | 23 |
Semester 3
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Database Management Systems | 3 | 0 | 0 | 3 |
| Database Management Systems Lab | 0 | 0 | 4 | 2 |
| Discrete Mathematical Structures | 3 | 0 | 0 | 3 |
| Object Oriented Programming | 3 | 0 | 0 | 3 |
| Object Oriented Programming Lab | 0 | 0 | 2 | 1 |
| Operating Systems | 3 | 0 | 0 | 3 |
| Software Engineering | 3 | 0 | 0 | 3 |
| Exploratory-1 | 0 | 0 | 0 | 3 |
| Design Thinking | 0 | 0 | 0 | 2 |
| TOTAL | 23 |
Semester 4
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Artificial Intelligence and Machine Learning | 2 | 0 | 0 | 2 |
| Artificial Intelligence and Machine Learning Lab | 0 | 0 | 2 | 1 |
| Data communication and Networks | 3 | 0 | 0 | 3 |
| Data communication and Networks Lab | 0 | 0 | 2 | 1 |
| Design and Analysis of Algorithms | 3 | 0 | 0 | 3 |
| Design and Analysis of Algorithms Lab | 0 | 0 | 2 | 1 |
| Exploratory-2 | 3 | 0 | 0 | 3 |
| Linear Algebra | 3 | 0 | 0 | 3 |
| PE-1 | 4 | 0 | 0 | 4 |
| PE-1 Lab | 0 | 0 | 2 | 1 |
| TOTAL | 22 |
Semester 5
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Cryptography and Network Security | 3 | 0 | 0 | 3 |
| Formal Languages and Automata Theory | 3 | 0 | 0 | 3 |
| Object Oriented Analysis and Design | 3 | 0 | 0 | 3 |
| Exploratory-3 | 3 | 0 | 0 | 3 |
| Start your Startup | 2 | 0 | 0 | 2 |
| Research Methodology in CS | 3 | 0 | 0 | 3 |
| Probability, Entropy, and MC Simulation | 3 | 0 | 0 | 3 |
| PE-2 | 4 | 0 | 0 | 4 |
| PE-2 Lab | 0 | 0 | 2 | 1 |
| TOTAL | 25 |
Semester 6
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Exploratory-4 | 3 | 0 | 0 | 3 |
| Leadership and Teamwork | 2 | 0 | 0 | 2 |
| Compiler Design | 3 | 0 | 0 | 3 |
| Statistics and Data Analysis | 3 | 0 | 0 | 3 |
| PE-3 | 4 | 0 | 0 | 4 |
| PE-3 Lab | 0 | 0 | 2 | 1 |
| Minor Project | 0 | 0 | 5 | 5 |
| TOTAL | 21 |
Semester 7
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Exploratory-5 | 3 | 0 | 0 | 3 |
| PE-4 | 4 | 0 | 0 | 4 |
| PE-4 Lab | 0 | 0 | 2 | 1 |
| PE-5 | 3 | 0 | 0 | 3 |
| PE-5 Lab | 0 | 0 | 2 | 1 |
| Capstone Project - Phase-1 | 0 | 0 | 5 | 5 |
| Summer Internship | 0 | 0 | 0 | 1 |
| TOTAL | 18 |
Semester 8
| Course | L | T | P | Credit |
|---|---|---|---|---|
| IT Ethical Practices | 3 | 0 | 0 | 3 |
| Capstone Project - Phase-2 | 0 | 0 | 5 | 5 |
| TOTAL | 8 |
Program Elective 24 Credits
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Applied Machine Learning | 4 | 0 | 0 | 4 |
| Applied Machine Learning Lab | 0 | 0 | 2 | 1 |
| Deep Learning | 4 | 0 | 0 | 4 |
| Deep Learning Lab | 0 | 0 | 2 | 1 |
| Pattern and Visual Recognition | 4 | 0 | 0 | 4 |
| Pattern and Visual Recognition Lab | 0 | 0 | 2 | 1 |
| Computational Linguistics and Natural Language Processing | 4 | 0 | 0 | 4 |
| Computational Linguistics and Natural Language Processing Lab | 0 | 0 | 2 | 1 |
| Algorithm for Intelligent Systems and Robotics | 3 | 0 | 0 | 3 |
| Algorithm for Intelligent Systems and Robotics Lab | 0 | 0 | 2 | 1 |
| TOTAL | 24 |
Eligibility
The minimum eligibility criteria for B. Tech in Artificial Intelligence and Machine Learning to be fulfilled by interested students is as follows: Minimum 50% marks in Class X and XII with 50% in PCM in Class XII.
Selection Criteria
The process of selection criteria for students interested in pursuing B. Tech in Artificial Intelligence and Machine Learning offered by UPES is based on the individual's performance in UPESEAT / JEE Mains / Board Merit / SAT / CUET.
Further Information
Enquiry Form
Frequently Asked Questions
Artificial Intelligence is an advanced technology that helps engineers build smart and responsive systems. Machine Learning technology further helps advanced systems to analyse and interpret data. Furthermore, data science help engineers and managers to use data to make informed business decisions.
Artificial Intelligence and Machine Learning developments predominantly use Python programming language. Furthermore, R, or C++, and JavaScript languages are also used for designing smart systems. B.Tech Artificial Intelligence and Machine Learning students at UPES Dehradun learn these programming languages as a part of their course curriculum.
Yes, a strong foundation in mathematics can help you understand Artificial Intelligence and Machine Learning concepts and models in greater depth. You should be comfortable with areas such as Linear Algebra, Calculus, and Statistics, as these form an important part of AI and ML. As per the B.Tech Artificial Intelligence and Machine Learning eligibility criteria, applicants should have at least 50% marks in PCM in Class XII, along with a minimum of 50% overall marks in both Class X and Class XII.
Yes. The B.Tech in Artificial Intelligence and Machine Learning program can introduce you to emerging areas such as Generative AI and Large Language Models (LLMs). These concepts help you understand how modern AI systems can generate text, images, code, and other types of content. Learning about Generative AI and LLMs can also help you build skills relevant to the growing range of AI applications across industries.
During BTech AI and ML program at UPES, students will learn several contemporary technologies along with industry-relevant programs and tools. Students enrolled in the program will work with technologies such ad Python, Machine Learning Frameworks, Generative AI and LLMs, Data Analysis Tools, Deep learning technologies, Cloud and AI platforms, and Databases and APIs.
If you are interested in building smart, responsive, and autonomous systems, B.Tech Artificial Intelligence and Machine Learning stream is for you. Furthermore, if you are planning to pursue a career in fast evolving sectors such as computer vision, robotics, or predictive analytics, you should choose BTech AI and ML specialization.
An AI Engineer focuses on building user-facing applications by integrating pre-trained AI models and APIs into products and services. A Machine Learning (ML) Engineer, on the other hand, works more closely with data to design, train, test, and optimise custom machine learning models. A B.Tech in Artificial Intelligence and Machine Learning program offer students promising career prospects in both AI and ML domains.
Yes, UPES Dehradun emphasises hands-on learning through industry projects and internships. As part of the program, you get opportunities to work on live projects and complete industry internships with relevant organisations, including AI-focused companies. This practical exposure helps you apply what you learn in the classroom to real-world AI applications while gaining valuable industry experience.
The B.Tech in Artificial Intelligence and Machine Learning program also covers the ethical and responsible use of AI. You learn about important areas such as AI bias, fairness, data privacy, transparency, and responsible decision-making. These concepts help you understand how AI systems can affect people and why they need to be designed and used carefully. The program also helps you recognise the limitations and risks of AI while developing solutions that are more trustworthy and responsible.
Graduates with a B.Tech Artificial Intelligence and Machine Learning degree can pursue careers in diverse industries including technology, finance, e-commerce, automotive, and healthcare. Some of the top roles that graduates can pursue include Data Scientist, Machine Learning Engineer, Research Scientist, Business Intelligence Developer, and AI Data Analyst.
After completing B.Tech Artificial Intelligence and Machine Learning program from UPES, graduate can pursue exciting career opportunities across diverse industries with roles such as Data Scientist, Machine Learning Engineer, Research Scientist, Business Intelligence Developer, and AI Data Analyst.
To enhance your career prospects and gain relevant technical skills in AI & ML systems, you can complete certificates such as Google Cloud Professional Machine Learning Engineer, AWS Certified Machine Learning Specialty, and Microsoft Certified: Azure AI Engineer. Additionally, to prepare students for skilled-focused industries, UPES offers AI Engineering & Deep Learning certification which is integrated into B.Tech Artificial Intelligence and Machine Learning program.
Yes, UPES B.Tech Artificial Intelligence and Machine Learning program is designed to prepare students for tech-driven and skill-focused industries. Over 33% of program curriculum is AI-embedded, and students can also earn AI Engineering & Deep Learning certification as a part of their course curriculum.