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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 third semester, 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 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 the 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, Algorithms 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.
Duration of Program
4 years (8 Semesters)
Seats
1180*
Co-Delivered Courses by Partner Industries
DESIGN YOUR OWN DEGREE
UPES’ curriculum framework is holistic in its overall structure and yet focuses on the individual need of the student to discover, experience, explore and challenge. Along with the core subject, students have the option to choose from subject-focused specialisations. They are also allowed to choose minor/exploratory subject from other schools at UPES that are: School of Engineering, School of Computer Science, School of Law, School of Business, School of Health Sciences, School of Design, School of Modern Media, and School of Liberal Studies.
Further, based on the multifaceted needs of the global workplace and evolving lifestyles, the curriculum offers Signature and Life-Skills courses through School for Life. To round off this learning experience, students are required to do mandatory internships in the social sector, government/public sector, and industry. The combinations available for students to pick and choose from are endless, ensuring both depth and width of knowledge.
Details
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.
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
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.
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.
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
Click here to download the curriculum
SEMESTER I
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| MATH 1036 | Engineering Mathematics | 3 | 3 | 0 | 0 |
| *PHYS 1023 / SLLS 0103 | Engineering Physics/Leadership and Teamwork | 3/2 | 3/2 | 0 | 0 |
| CSEG 1010 | Principles of Programming Languages | 4 | 4 | 0 | 0 |
| CSIB 1001 | Introduction to IT Industry Verticals | 2 | 2 | 0 | 0 |
| SLLS 0101 | Living Conversations | 2 | 3 | 0 | 0 |
| SLLS 0102 | Learning how to Learn | 2 | 2 | 0 | 0 |
| HUMN 1010 | Induction Program | 0 | 0 | 0 | 0 |
| CSEG 1110 | Principles of Programming Languages Lab | 1 | 0 | 0 | 2 |
| *PHYS 1123 | Engineering Physics Lab | 1 | 0 | 0 | 2 |
| TOTAL | 16/18 |
SEMESTER II
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| CSEG 1011 | Data Structures | 3 | 3 | 0 | 0 |
| CSEG 1013 | Operating Systems | 3 | 3 | 0 | 0 |
| CSEG 1012 | Discrete Mathematics | 3 | 3 | 0 | 0 |
| CSEG 1014 | Computer System Architecture | 3 | 3 | 0 | 0 |
| CSIB 1002 | Python Programming | 3 | 3 | 0 | 0 |
| SLLS 0202 | Working with Data | 2 | 3 | 0 | 0 |
| *PHYS 1023 / SLLS 0103 | Engineering Physics/Leadership and Teamwork | 3/2 | 2 | 0 | 0 |
| CSEG 1111 | Data Structures Lab | 1 | 0 | 0 | 2 |
| CSEG 1113 | Operating Systems Lab | 1 | 0 | 0 | 2 |
| *PHYS 1123 | Engineering Physics Lab | 1 | 0 | 0 | 2 |
| CSIB 1102 | Python Programming Lab | 1 | 0 | 0 | 2 |
| TOTAL | 22/24 |
SEMESTER III
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| CSEG 2021 | Object-Oriented Programming | 3 | 3 | 0 | 0 |
| CSEG 2021 | Design and Analysis of Algorithm | 3 | 3 | 0 | 0 |
| CSEG 2008 | Software Engineering & Project management | 3 | 3 | 0 | 0 |
| CSBL 2004 | Introduction to Blockchain | 2 | 2 | 0 | 0 |
| CSSF 2005 | IT Application & Data Security | 3 | 3 | 0 | 0 |
| SLSG 0201 | Ethical Leadership in 21st Century (Human Values and Ethics) | 3 | 3 | 0 | 0 |
| SLLS 0201 | Design Thinking | 2 | 2 | 0 | 0 |
| Exploratory Elective 1 | 3 | 3 | 0 | 0 | |
| Core Electives-1 | 4 | 4 | 0 | 0 | |
| CSEG 2120 | Object-Oriented Programming Lab | 1 | 1 | 0 | 0 |
| SLLS 2001 | Social Internship | 0 | 0 | 0 | 0 |
| CSSF 2105 | IT Application & Data Security Lab | 1 | 1 | 0 | 0 |
| CSBL 2001 | Dynamic Paradigm in Blockchain Technology 1 | 0 | 0 | 0 | 0 |
| TOTAL | 24 | 28 | |||
| Core Electives-1 | 4 | ||||
| CSEG 2035P | Formal Languages and Automata Theory | ||||
| CSEG 2036P | Probability & Statistics for Engineers |
SEMESTER IV
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| CSEG 2005 | Advanced Database Management Systems | 3 | 3 | 0 | 0 |
| CSEG 2009 | Data Communication and Computer Networks | 3 | 3 | 0 | 0 |
| CSEG 2030 | Computer Graphics | 3 | 3 | 0 | 0 |
| CSBL 2002 | CryptoCurrency | 3 | 3 | 0 | 0 |
| SLSG 0203 | Critical thinking and writing | 3 | 3 | 0 | 0 |
| SLSG 0202 | Environment and Sustainability - Himalaya Fellowship | 3 | 3 | 0 | 0 |
| Exploratory Elective 2 | 3 | 3 | 0 | 0 | |
| Core Electives-2 | 4 | 4 | 0 | 0 | |
| CSEG 2105 | Advanced Database Management Systems Lab | 1 | 1 | 0 | 0 |
| CSEG 2109 | Data Communication and Computer Networks Lab | 1 | 1 | 0 | 0 |
| CSEG 2130 | Computer Graphics Lab | 1 | 1 | 0 | 0 |
| CSBL 2102 | CryptoCurrency Lab | 1 | 1 | 0 | 0 |
| CSBL 2003 | Dynamic Paradigm in Blockchain Technology 2 | 0 | 0 | 0 | 0 |
| TOTAL | 25 | 29 | |||
| Core Electives-2 | 4 | ||||
| CSEG 2037P | Modelling and Simulation | ||||
| CSEG 2038P | Human-Computer Interface |
SEMESTER V
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| ECEG 3052 | Micro Processor & Embedded Systems | 3 | 3 | 0 | 0 |
| CSEG 3015 | Compiler Design | 3 | 3 | 0 | 0 |
| CSBL 3002 | Industry Use Cases using Blockchain | 3 | 3 | 0 | 0 |
| CSBL 3009 | Blockchain Components and Architecture | 2 | 2 | 0 | 0 |
| Program Elective I | 2 | 2 | 0 | 0 | |
| SLSG 0301 | Starting your Startup | 3 | 3 | 0 | 0 |
| Exploratory Elective 3 | 3 | 3 | 0 | 0 | |
| SLLS 0301 | Persuasive Presence | 2 | 2 | 0 | 0 |
| PROJ 3103 | Minor Project-I | 2 | 2 | 0 | 0 |
| Core Electives-3 | 3 | 3 | 0 | 0 | |
| ECEG 3152 | Micro Processor & Embedded Systems Lab | 1 | 1 | 0 | 0 |
| CSBL 3102 | Industry Use Cases using Blockchain Lab | 1 | 1 | 0 | 0 |
| CSBL 3109 | Blockchain Components and Architecture Lab | 1 | 1 | 0 | 0 |
| CSBL 3004 | Dynamic Paradigm in BlockChain Technology 3 | 0 | 0 | 0 | 0 |
| SIIB 3104 | Internship in Government Setup/Startup | 0 | 0 | 0 | 0 |
| TOTAL | 26 | 29 | |||
| Core Electives-3 | 3 | ||||
| CSEG 3040P | Cryptography and Network Security | ||||
| CSEG 3041P | Image Processing & Pattern Analysis |
SEMESTER VI
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| CSBL 3005 | Public Blockchain- Ethereum | 3 | 3 | 0 | 0 |
| CSBL 3006 | Blockchain Applications for Cognitive | 3 | 3 | 0 | 0 |
| CSBL 3010 | Blockchain for Public Sector | 2 | 2 | 0 | 0 |
| CSBL 3011 | Emerging areas in Blockchain | 2 | 2 | 0 | 0 |
| Program Elective II | 3 | 3 | 0 | 0 | |
| SLSG 0305 | Managing Relationship and Being Happy | 3 | 3 | 0 | 0 |
| Exploratory Elective 4 | 3 | 3 | 0 | 0 | |
| PROJ 3105 | Minor Project-II | 2 | 2 | 0 | 0 |
| Core Electives-4 | 3 | 3 | 0 | 0 | |
| CSBL 3106 | Blockchain Applications for Cognitive Lab | 1 | 1 | 0 | 0 |
| CSBL 3105 | Public Blockchain- Ethereum Lab | 1 | 1 | 0 | 0 |
| CSBL 3110 | Blockchain for Public Sector - Lab | 1 | 1 | 0 | 0 |
| CSBL 3008 | Dynamic Paradigm in Blockchain Technology 4 | 0 | 0 | 0 | 0 |
| TOTAL | 24 | 27 | |||
| Core Electives-4 | 3 | ||||
| CSEG 3042P | Digital Signal Processing | ||||
| CSEG 3043P | Natural Language Processing |
SEMESTER VII
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| Program Elective III | 3 | 3 | 0 | 0 | |
| PROJ 4101 | Major Project I | 4 | 4 | 0 | 0 |
| SLSG 0404 | Finding your Purpose in Life | 3 | 3 | 0 | 0 |
| Exploratory Elective 5 | 3 | 3 | 0 | 0 | |
| SIIB 4102 | Summer Internship | 1 | 1 | 0 | 0 |
| Core Electives-5 | 3 | 3 | 0 | 0 | |
| TOTAL | 14 | 17 | |||
| Core Electives-5 | 3 | ||||
| CSEG 4012P | Enterprise Resource Planning | ||||
| CSEG 4013P | Software Version Control |
SEMESTER VIII
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| Program Elective IV | 3 | 3 | 0 | 0 | |
| PROJ 4112 | Major Project II | 4 | 4 | 0 | 0 |
| Core Electives-6 | 3 | 3 | 0 | 0 | |
| TOTAL | 7 | 10 | |||
| Core Electives-6 | 3 | ||||
| CSEG 4014P | Software Reliability & Testing | ||||
| CSEG 4015P | Software Quality Assurance |
Total of B.Tech (Hons.) Computer Science Engineering with specialization in Artificial Intelligence and Machine Learning is 160/180.
Details
Future 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
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.
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
Curriculum
Click here to download the curriculum
SEMESTER I
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| MATH 1036 | Engineering Mathematics | 3 | 3 | 0 | 0 |
| *PHYS 1023 / SLLS 0103 | Engineering Physics/Leadership and Teamwork | 3/2 | 3/2 | 0 | 0 |
| CSEG 1010 | Principles of Programming Languages | 4 | 4 | 0 | 0 |
| CSIB 1001 | Introduction to IT Industry Verticals | 2 | 2 | 0 | 0 |
| SLLS 0101 | Living Conversations | 2 | 3 | 0 | 0 |
| SLLS 0102 | Learning how to Learn | 2 | 2 | 0 | 0 |
| HUMN 1010 | Induction Program | 0 | 0 | 0 | 0 |
| CSEG 1110 | Principles of Programming Languages Lab | 1 | 0 | 0 | 2 |
| *PHYS 1123 | Engineering Physics Lab | 1 | 0 | 0 | 2 |
| TOTAL | 16/18 |
SEMESTER II
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| CSEG 1011 | Data Structures | 3 | 3 | 0 | 0 |
| CSEG 1013 | Operating Systems | 3 | 3 | 0 | 0 |
| CSEG 1012 | Discrete Mathematics | 3 | 3 | 0 | 0 |
| CSEG 1014 | Computer System Architecture | 3 | 3 | 0 | 0 |
| CSIB 1002 | Python Programming | 3 | 3 | 0 | 0 |
| SLLS 0202 | Working with Data | 2 | 3 | 0 | 0 |
| *PHYS 1023 / SLLS 0103 | Engineering Physics/Leadership and Teamwork | 3/2 | 2 | 0 | 0 |
| CSEG 1111 | Data Structures Lab | 1 | 0 | 0 | 2 |
| CSEG 1113 | Operating Systems Lab | 1 | 0 | 0 | 2 |
| *PHYS 1123 | Engineering Physics Lab | 1 | 0 | 0 | 2 |
| CSIB 1102 | Python Programming Lab | 1 | 0 | 0 | 2 |
| TOTAL | 22/24 |
SEMESTER III
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| CSEG 2021 | Object-Oriented Programming | 3 | 3 | 0 | 0 |
| CSEG 2021 | Design and Analysis of Algorithm | 3 | 3 | 0 | 0 |
| CSEG 2008 | Software Engineering & Project management | 3 | 3 | 0 | 0 |
| CSBL 2004 | Introduction to Blockchain | 2 | 2 | 0 | 0 |
| CSSF 2005 | IT Application & Data Security | 3 | 3 | 0 | 0 |
| SLSG 0201 | Ethical Leadership in 21st Century (Human Values and Ethics) | 3 | 3 | 0 | 0 |
| SLLS 0201 | Design Thinking | 2 | 2 | 0 | 0 |
| Exploratory Elective 1 | 3 | 3 | 0 | 0 | |
| Core Electives-1 | 4 | 4 | 0 | 0 | |
| CSEG 2120 | Object-Oriented Programming Lab | 1 | 1 | 0 | 0 |
| SLLS 2001 | Social Internship | 0 | 0 | 0 | 0 |
| CSSF 2105 | IT Application & Data Security Lab | 1 | 1 | 0 | 0 |
| CSBL 2001 | Dynamic Paradigm in Blockchain Technology 1 | 0 | 0 | 0 | 0 |
| TOTAL | 24 | 28 | |||
| Core Electives-1 | 4 | ||||
| CSEG 2035P | Formal Languages and Automata Theory | ||||
| CSEG 2036P | Probability & Statistics for Engineers |
SEMESTER IV
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| CSEG 2005 | Advanced Database Management Systems | 3 | 3 | 0 | 0 |
| CSEG 2009 | Data Communication and Computer Networks | 3 | 3 | 0 | 0 |
| CSEG 2030 | Computer Graphics | 3 | 3 | 0 | 0 |
| CSBL 2002 | CryptoCurrency | 3 | 3 | 0 | 0 |
| SLSG 0203 | Critical thinking and writing | 3 | 3 | 0 | 0 |
| SLSG 0202 | Environment and Sustainability - Himalaya Fellowship | 3 | 3 | 0 | 0 |
| Exploratory Elective 2 | 3 | 3 | 0 | 0 | |
| Core Electives-2 | 4 | 4 | 0 | 0 | |
| CSEG 2105 | Advanced Database Management Systems Lab | 1 | 1 | 0 | 0 |
| CSEG 2109 | Data Communication and Computer Networks Lab | 1 | 1 | 0 | 0 |
| CSEG 2130 | Computer Graphics Lab | 1 | 1 | 0 | 0 |
| CSBL 2102 | CryptoCurrency Lab | 1 | 1 | 0 | 0 |
| CSBL 2003 | Dynamic Paradigm in Blockchain Technology 2 | 0 | 0 | 0 | 0 |
| TOTAL | 25 | 29 | |||
| Core Electives-2 | 4 | ||||
| CSEG 2037P | Modelling and Simulation | ||||
| CSEG 2038P | Human-Computer Interface |
SEMESTER V
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| ECEG 3052 | Micro Processor & Embedded Systems | 3 | 3 | 0 | 0 |
| CSEG 3015 | Compiler Design | 3 | 3 | 0 | 0 |
| CSBL 3002 | Industry Use Cases using Blockchain | 3 | 3 | 0 | 0 |
| CSBL 3009 | Blockchain Components and Architecture | 2 | 2 | 0 | 0 |
| Program Elective I | 2 | 2 | 0 | 0 | |
| SLSG 0301 | Starting your Startup | 3 | 3 | 0 | 0 |
| Exploratory Elective 3 | 3 | 3 | 0 | 0 | |
| SLLS 0301 | Persuasive Presence | 2 | 2 | 0 | 0 |
| PROJ 3103 | Minor Project-I | 2 | 2 | 0 | 0 |
| Core Electives-3 | 3 | 3 | 0 | 0 | |
| ECEG 3152 | Micro Processor & Embedded Systems Lab | 1 | 1 | 0 | 0 |
| CSBL 3102 | Industry Use Cases using Blockchain Lab | 1 | 1 | 0 | 0 |
| CSBL 3109 | Blockchain Components and Architecture Lab | 1 | 1 | 0 | 0 |
| CSBL 3004 | Dynamic Paradigm in BlockChain Technology 3 | 0 | 0 | 0 | 0 |
| SIIB 3104 | Internship in Government Setup/Startup | 0 | 0 | 0 | 0 |
| TOTAL | 26 | 29 | |||
| Core Electives-3 | 3 | ||||
| CSEG 3040P | Cryptography and Network Security | ||||
| CSEG 3041P | Image Processing & Pattern Analysis |
SEMESTER VI
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| CSBL 3005 | Public Blockchain- Ethereum | 3 | 3 | 0 | 0 |
| CSBL 3006 | Blockchain Applications for Cognitive | 3 | 3 | 0 | 0 |
| CSBL 3010 | Blockchain for Public Sector | 2 | 2 | 0 | 0 |
| CSBL 3011 | Emerging areas in Blockchain | 2 | 2 | 0 | 0 |
| Program Elective II | 3 | 3 | 0 | 0 | |
| SLSG 0305 | Managing Relationship and Being Happy | 3 | 3 | 0 | 0 |
| Exploratory Elective 4 | 3 | 3 | 0 | 0 | |
| PROJ 3105 | Minor Project-II | 2 | 2 | 0 | 0 |
| Core Electives-4 | 3 | 3 | 0 | 0 | |
| CSBL 3106 | Blockchain Applications for Cognitive Lab | 1 | 1 | 0 | 0 |
| CSBL 3105 | Public Blockchain- Ethereum Lab | 1 | 1 | 0 | 0 |
| CSBL 3110 | Blockchain for Public Sector - Lab | 1 | 1 | 0 | 0 |
| CSBL 3008 | Dynamic Paradigm in Blockchain Technology 4 | 0 | 0 | 0 | 0 |
| TOTAL | 24 | 27 | |||
| Core Electives-4 | 3 | ||||
| CSEG 3042P | Digital Signal Processing | ||||
| CSEG 3043P | Natural Language Processing |
SEMESTER VII
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| Program Elective III | 3 | 3 | 0 | 0 | |
| PROJ 4101 | Major Project I | 4 | 4 | 0 | 0 |
| SLSG 0404 | Finding your Purpose in Life | 3 | 3 | 0 | 0 |
| Exploratory Elective 5 | 3 | 3 | 0 | 0 | |
| SIIB 4102 | Summer Internship | 1 | 1 | 0 | 0 |
| Core Electives-5 | 3 | 3 | 0 | 0 | |
| TOTAL | 14 | 17 | |||
| Core Electives-5 | 3 | ||||
| CSEG 4012P | Enterprise Resource Planning | ||||
| CSEG 4013P | Software Version Control |
SEMESTER VIII
| Subject Code | Subject | Credits | L | T | P |
|---|---|---|---|---|---|
| Program Elective IV | 3 | 3 | 0 | 0 | |
| PROJ 4112 | Major Project II | 4 | 4 | 0 | 0 |
| Core Electives-6 | 3 | 3 | 0 | 0 | |
| TOTAL | 7 | 10 | |||
| Core Electives-6 | 3 | ||||
| CSEG 4014P | Software Reliability & Testing | ||||
| CSEG 4015P | Software Quality Assurance |
Total of B.Tech (Hons.) Computer Science Engineering with specialization in Artificial Intelligence and Machine Learning is 160/180.
Non Examination Pathway
| JEE Main, SAT & Board Merit | |
|---|---|
|
(1) Minimum 50% marks at Higher& Senior Secondary level (10th&12th) and minimum 50% aggregate in PCM (Physics, Chemistry & Mathematics) at Senior Secondary level (12th class). & (2) JEE Main cut-off Rank to be announced (on UPES website) after the declaration of JEE Main 2023 results) Or (3) SAT Cut off - 50 percentiles and above Or (4). Minimum 80% Marks at Higher & Senior Secondary Level and Minimum 80% aggregate in PCM (Physics, Chemistry and Math’s) at Senior Secondary Level |
Through Merit Rank / Cut-off Score |
# Upto 20% seats shall be filled through non-exam category (10% through JEE Mains and 10% through Board Merit). In case of seats following vacant in this category; UPES has the right to fill these through UPES Examination. University also reserves the right to conduct further CBT / Pen Paper / Online test for admission.
