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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.