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DETAILS
In our Master of Computer Application (MCA) with specialisation in Artificial Intelligence and Machine Learning course, apart from essential concepts such as data structures, algorithms, OOPS concepts using Java and python, databases, software engineering and design processes. Students will also obtain an in-depth knowledge of machine learning and artificial intelligence by implementing relevant real-world problems in a wide variety of application domains such as robotics, computer vision, natural language processing, etc. Students will be experienced in machine learning pipeline, data models, algorithms, and empirics.
Duration of Program
2 years (4 Semesters)
Seats
35*
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
- Business Intelligence Developer
- Machine Learning Engineer
- Data Scientist
- Expert System Developer
- AI Developer/Consultant
Minimum 50% in 10th & 12th & 50% aggregate marks in BCA or B.Sc. (Computer Science) or B.Sc. (Information Technology) or any Graduation with Computer Science / IT as a subject for three years OR with (Mathematics or Statistics or Business Math or Business Statistics or QT as one of the subjects at Graduation or 10+2 level) or equivalent.
Personal Interview
SEMESTER I
| Subject Code | Subject | Credits |
| Python Programming | 3 | |
| Web Technologies Through PHP | 3 | |
| Software Engineering and Project Management | 3 | |
| Business Communication and Ethics | 3 | |
| Domain Elective-1 | 3 | |
| Social Internship | 1 | |
| PRACTICAL | ||
| Python Programming Lab | 2 | |
| Web Technologies Through PHP Lab | 1 | |
| TOTAL | 19 |
SEMESTER II
| Subject Code | Subject | Credits |
| Data Base Management Systems | 3 | |
| Operating Systems | 4 | |
| Object-Oriented Analysis and Design Using UML | 3 | |
| Venture Ideation and Enterprenureship | 2 | |
| Domain Elective-2 | 3 | |
| Domain Elective-3 | 3 | |
| Java Programming *1 | 3 | |
| PRACTICAL | ||
| DBMS Lab | 1 | |
| Domain Elective-2 Lab | 1 | |
| Java Programming Lab | 2 | |
| Object-Oriented Analysis and Design Using UML Lab | 1 | |
| TOTAL | 26 |
SEMESTER III
| Subject Code | Subject | Credits |
| Modeling and simulation | 3 | |
| Computer Networks | 3 | |
| Domain Elective-4 | 3 | |
| Domain Elective-5 | 3 | |
| Domain Elective-6 | 3 | |
| Computer Graphics | 3 | |
| PRACTICAL | ||
| Domain Elective-5 Lab | 1 | |
| Domain Project | 4 | |
| TOTAL | 23 |
SEMESTER IV
| Subject Code | Subject | Credits |
| PRACTICAL | ||
| Full time Industry Project and Seminar | 20 | |
| TOTAL | 20 |
| Semester-I | Domain Elective-1 | 3 |
| Problem Domains of AI *5 | ||
| Semester-II | Domain Elective-2 | 3+1 |
| Soft Computing | ||
| Semester-II | Domain Elective-3 | 3 |
| Knowledge Engineering and Expert Systems | ||
| Semester-III | Domain Elective-4 | 3 |
| Machine Learning - Using Data for Artificial Intelligence | ||
| Semester-III | Domain Elective-5 | 3+1 |
| Deep learning and ANN | ||
| Semester-III | Domain Elective-6 | 3 |
| Natural language Processing | ||
| Game Theory and Heuristics | ||
| Image Processing and Machine Vision | ||
| Information retrieval | ||
| Data Visualization | ||
| Biometric processing | ||
| Business Analytics and Optimization | ||
| Agent based Intelligent Systems |
Details
Career Prospects
- Business Intelligence Developer
- Machine Learning Engineer
- Data Scientist
- Expert System Developer
- AI Developer/Consultant
Eligibility
Minimum 50% in 10th & 12th & 50% aggregate marks in BCA or B.Sc. (Computer Science) or B.Sc. (Information Technology) or any Graduation with Computer Science / IT as a subject for three years OR with (Mathematics or Statistics or Business Math or Business Statistics or QT as one of the subjects at Graduation or 10+2 level) or equivalent.
Selection Criteria
Personal Interview
Curriculum
SEMESTER I
| Subject Code | Subject | Credits |
| Python Programming | 3 | |
| Web Technologies Through PHP | 3 | |
| Software Engineering and Project Management | 3 | |
| Business Communication and Ethics | 3 | |
| Domain Elective-1 | 3 | |
| Social Internship | 1 | |
| PRACTICAL | ||
| Python Programming Lab | 2 | |
| Web Technologies Through PHP Lab | 1 | |
| TOTAL | 19 |
SEMESTER II
| Subject Code | Subject | Credits |
| Data Base Management Systems | 3 | |
| Operating Systems | 4 | |
| Object-Oriented Analysis and Design Using UML | 3 | |
| Venture Ideation and Enterprenureship | 2 | |
| Domain Elective-2 | 3 | |
| Domain Elective-3 | 3 | |
| Java Programming *1 | 3 | |
| PRACTICAL | ||
| DBMS Lab | 1 | |
| Domain Elective-2 Lab | 1 | |
| Java Programming Lab | 2 | |
| Object-Oriented Analysis and Design Using UML Lab | 1 | |
| TOTAL | 26 |
SEMESTER III
| Subject Code | Subject | Credits |
| Modeling and simulation | 3 | |
| Computer Networks | 3 | |
| Domain Elective-4 | 3 | |
| Domain Elective-5 | 3 | |
| Domain Elective-6 | 3 | |
| Computer Graphics | 3 | |
| PRACTICAL | ||
| Domain Elective-5 Lab | 1 | |
| Domain Project | 4 | |
| TOTAL | 23 |
SEMESTER IV
| Subject Code | Subject | Credits |
| PRACTICAL | ||
| Full time Industry Project and Seminar | 20 | |
| TOTAL | 20 |
| Semester-I | Domain Elective-1 | 3 |
| Problem Domains of AI *5 | ||
| Semester-II | Domain Elective-2 | 3+1 |
| Soft Computing | ||
| Semester-II | Domain Elective-3 | 3 |
| Knowledge Engineering and Expert Systems | ||
| Semester-III | Domain Elective-4 | 3 |
| Machine Learning - Using Data for Artificial Intelligence | ||
| Semester-III | Domain Elective-5 | 3+1 |
| Deep learning and ANN | ||
| Semester-III | Domain Elective-6 | 3 |
| Natural language Processing | ||
| Game Theory and Heuristics | ||
| Image Processing and Machine Vision | ||
| Information retrieval | ||
| Data Visualization | ||
| Biometric processing | ||
| Business Analytics and Optimization | ||
| Agent based Intelligent Systems |
