Master of Science (M.Sc) Data Analytics and Artificial Intelligence AI

About the Program

M.Sc. Artificial Intelligence and Data Analytics, a two-year post graduate degree program is designed to develop their skills especially in the areas of Artificial Intelligence and Data Analytics. This program also provides necessary skills in theoretical computation and mathematics to handle real-world complexities and it aims to meet up a sharp growth in industries. Upcoming trends with respect to the software industry that impact a broad range of applications are demonstrated. Various data-driven AI solutions which can be implemented to reinforce and improve the decision-making set up are instructed. Students can understand the rapid change in the emerging fields of Artificial intelligence and data analytics of computational systems.

Salient Features

• Curriculum based on Research and Development and industry needs
• Career prospects in major sectors such as Agriculture. Healthcare, education and Infrastructure, Banking etc,

Eligibility Criteria

• B.Sc. (Computer Science)/ B.Sc. (Information Technology)/ B.C.A.
• B.Sc. (Applied Sciences) with Mathematics and Computer Science (10+2+3 scheme) from a recognized university.
• Any Bachelor’s degree in science (10+2+3) from a recognized university with at least 3 papers in Computer Science and 1 paper in Mathematics under Annual System.

PROGRAM’S EDUCATIONAL OBJECTIVES (PEO)

• PEO 1: To prepare graduates to be successful professionals in industry, government, academia, research, entrepreneurial pursuit, and consulting firms.
• PEO 2: To prepare graduates to achieve peer recognition, as individuals and as a team players, through demonstration of good analytical, design, implementation, and interpersonal skills.
• PEO 3: To prepare graduates to contribute to society as broadly educated, expressive, ethical, and responsible citizens with proven expertise.
• PEO 4: To prepare graduates to pursue life-long learning to fulfill their goals.
   

PROGRAM’S OUTCOMES (PO’S)

• Computational knowledge: Apply knowledge of computing fundamentals, computing specialization, mathematics, and domain knowledge appropriate for the computing specialization to the abstraction and conceptualization of computing models from defined problems and requirements.
• Problem analysis: Identify, formulate, research literature, and solve complex computing problems reaching substantiated conclusions using fundamental principles of mathematics, computing sciences, and relevant domain disciplines.
• Design/development of solutions: Design and evaluate solutions for complex computing problems, and design and evaluate systems, components, or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations.
• Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
• Modern tool usage: Modern Tool Usage: Create, select, adapt, and apply appropriate techniques, resources, and modern computing tools to complex computing activities, with an understanding of the limitations.
• Societal and Environmental Concern: Understand and assess societal, environmental, health, safety, legal, and cultural issues within local and global contexts, and the consequential responsibilities relevant to professional computing practice.
• Innovation and Entrepreneurship: Identify a timely opportunity and use innovation to pursue that opportunity to create value and wealth for the betterment of the individual and society at large.
• Professional Ethics: Understand and commit to professional ethics and cyber regulations, responsibilities, and norms of professional computing practice.
• Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
• Communication: Communicate effectively with the computing community, and with society, about complex computing activities by being able to comprehend and write effective reports, design documentation, make effective presentations, and give and understand clear instructions.
• Project management and finance: Demonstrate knowledge and understanding of the computing and management principles and apply these to one’s work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
• Life-long learning: Recognize the need, and have the ability, to engage in independent learning for continual development as a computing professional.

PROGRAM’S SPECIFIC OUTCOMES (PSO’S)

• PSO 1: Ability to solve complex problems in the domain of Artificial Intelligence and Data Analytics using the current software tools and technologies.
• PSO 2: Explore the concepts of Artificial Intelligence and Data Analytics and the development of computational systems in multidisciplinary fields.
• PSO 3: Create a new design, model, analyze, and evaluate the solution for new real-time problems in the field of Artificial Intelligence and Data Analytics.

About the Course

M.Sc. Artificial Intelligence and Data Analytics, a two-year postgraduate degree program is designed to develop their skills, especially in the areas of Artificial Intelligence and Data Analytics. This program also provides the necessary skills in theoretical computation and mathematics to handle real-world complexities and it aims to meet sharp growth in industries. Upcoming trends in the software industry that impact a broad range of applications are demonstrated. Various data-driven AI solutions that can be implemented to reinforce and improve the decision-making setup are instructed. Students can understand the rapid change in the emerging fields of Artificial intelligence and data analytics of computational systems.

Careers

With your qualification, you’ll be equipped to launch or enhance a career in the artificial intelligence and/or data science sectors, as well as giving them the skills they need to work in related consultancy or to start a new tech business. Career opportunities include (but are not limited to):

• Applied Artificial Intelligence and Data Science professional
• Graduate analyst
• Business analyst
• Business Intelligence Developer
• (Big) Data engineer/analyst/scientist/architect
• Machine learning developer
• Software engineer/architect
• Data mining expert
• Technology consultant
• Digital marketing analyst or manager