MCA in Data Science and Artificial Intelligence
Master of Computer Application (MCA) with Specialization in Data Science and Artificial Intelligence is a 2-year postgraduate course offered by the School of Computer Application, Babu Banarasi Das University in collaboration with IBM. This course is designed to make the professional technically sound in advanced learning systems that are based on algorithms of data science and Artificial Intelligence.
The Global data science industry has consistently been among the fastest growing industries. The market is particularly strong for technology professionals who straddle computer science, applications, and data science.
This course will help the professional to integrate data science models into computer systems. It will develop both sound computing foundations and an incisive analytical mind. The program first builds foundations with a comprehensive software & computer applications curriculum and adds a deep-dive into data science, analytics techniques using artificial intelligence approach.
School of Computer Application has collaborated with IBM which is a leading name in this field. IBM is moving with the idea of helping organizations that are data-driven. With this collaboration, SoCA, BBDU is guiding students into a new direction of a more innovative and effective way of handling data.
It is a practical industry-focused curriculum that is appreciated by a panel of academic as well as industry experts.
Course Details
| School Name: | School of Computer Applications |
| Course Length: | 2 Years |
| Session Start | July |
| Course Type: | Full Time |
| Eligibility Criteria: | BCA or Graduation with CS/ IT or equivalent courses, rest all criteria will be as per UGC and State Government Norms |
| Programme Fee: | Rs. 60,000/- Per Semester |
| Syllabus | SCA BBDU MCA (DS and AI) 2021-22 First Year Students Academic Session-2023-24 (NEP-2020) |
| Program Outcomes | |
|---|---|
| P01 | Computer Application Knowledge: Apply the knowledge of mathematics and computing fundamentals to various real-life applications for any given requirement. |
| P02 | Problem analysis: Expertise to transform complex business scenarios and contemporary issues into problems, investigate, understand as well as propose integrated solutions using upcoming technological methods. |
| P03 | Design/Development of Solutions: Design applications for any desired needs with appropriate considerations for any specific need on societal and environmental aspects |
| P04 | Conduct Investigations of Complex Computing Problems: Ability to devise and conduct experiments, interpret data and provide well-informed conclusions. |
| P05 | Modern Tool Usage: Integrate and apply efficiently the contemporary IT tools to all computer applications. |
| P06 | Perennial Learning: Involve in perennial learning for continued career development and progress as a computer professional. |
| P07 | Individual and Team Work: Function effectively both as a team leader and team member on multidisciplinary projects to demonstrate computing and management skills. |
| P08 | Environment and Sustainability: Utilize the computing knowledge efficiently in projects with concern for societal, environmental, and cultural aspects. |
| P09 | Project Management: Function competently as an individual and as a leader in multidisciplinary projects. |
| P10 | Innovation: Create and design innovative methodologies to solve complex problems for the betterment of society. |
| P11 | Entrepreneurship: Apply the inherent skills with absolute focus to function as a successful entrepreneur. |
| P12 | Lifelong Learning: Recognize the need for, and have the preparation and ability to engage in independent and lifelong learning in technological change. |
| Program Specific Outcomes | |
|---|---|
| PSO1 | Apply algorithms to build machine intelligence and employ cutting edge technologies to analyze business problem, communicate findings and effectively present results using data visualization techniques |
| PSO2 | Learn techniques and tools for transformation of Data and Machine Learning. |
