Infrastructure Development Banner

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.

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

CourseLTPCredit
Linux Lab0042
Programming in C0033
Programming in C Lab0042
Problem Solving2002
Living Conversation2002
Advanced Engineering 
Mathematics – I
3104
Environmental Sustainability and 
Climate Change - I
2002
Physics for Computer Engineers4004
Physics for Computer Engineers 
Lab
0021
TOTAL   22
,

Semester 2

CourseLTPCredit
Computer organization and Architecture3003
Data Structures and algorithms4004
Data Structures and algorithms Lab0021
Python programming2002
Python programming Lab0042
Digital Electronics3003
Critical Thinking and Writing2002
Advanced Engineering Mathematics – II3104
Environmental Sustainability and 
Climate Change - II
2002
TOTAL   23
,

Semester 3

CourseLTPCredit
Database Management Systems3003
Database Management Systems Lab0042
Discrete Mathematical Structures3003
Object Oriented Programming3003
Object Oriented Programming Lab0021
Operating Systems3003
Software Engineering3003
Exploratory-10003
Design Thinking0002
TOTAL   23
,

Semester 4

CourseLTPCredit
Artificial Intelligence and Machine 
Learning
2002
Artificial Intelligence and Machine 
Learning Lab
0021
Data communication and Networks3003
Data communication and Networks Lab0021
Design and Analysis of Algorithms3003
Design and Analysis of Algorithms Lab0021
Exploratory-23003
Linear Algebra 3003
PE-14004
PE-1 Lab0021
TOTAL   22
,

Semester 5

CourseLTPCredit
Cryptography and Network 
Security
3003
Formal Languages and 
Automata Theory
3003
Object Oriented Analysis and Design3003
Exploratory-33003
Start your Startup2002
Research Methodology in CS 3003
Probability, Entropy, and 
MC Simulation
3003
PE-24004
PE-2 Lab0021
TOTAL   25
,

Semester 6

CourseLTPCredit
Exploratory-43003
Leadership and Teamwork2002
Compiler Design 3003
Statistics and Data 
Analysis
3003
PE-34004
PE-3 Lab0021
Minor Project0055
TOTAL   21
,

Semester 7

CourseLTPCredit
Exploratory-53003
PE-44004
PE-4 Lab0021
PE-53003
PE-5 Lab0021
Capstone Project - Phase-10055
Summer Internship0001
TOTAL   18
,

Semester 8

CourseLTPCredit
IT Ethical Practices 3003
Capstone Project - Phase-20055
TOTAL   8
,

Program Elective 24 Credits

CourseLTPCredit
 Applied Machine Learning4004
Applied Machine Learning Lab                   0021
Deep Learning4004
Deep Learning Lab0021
Pattern and Visual Recognition4004
Pattern and Visual Recognition Lab0021
Computational Linguistics and 
Natural Language Processing
4004
Computational Linguistics and 
Natural Language Processing Lab
0021
Algorithm for Intelligent 
Systems and Robotics 
3003
Algorithm for Intelligent 
Systems and Robotics Lab
0021
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.

Enquiry Form

Please enter first name
Please enter last name
Please enter email address
+91 Please enter mobile number
Please Select Course Type
Please select Course
Please Select Condition