MBA in Data Science (MBA DS)

Significant business decisions depend on statistical numbers, facts, trends, market scenarios, and other such data, thus, making data science the backbone of any industry. With a unique curriculum, the mba in data science program aims to provide courses that will transform your statistical skills into cognitive proficiency, thereby, enabling you to create and leverage accurate data for various business decisions. 

What You'll Learn

• Conduct Research on Challenging Issues: Utilize research-based knowledge and research methodologies, such as experiment design, data analysis and interpretation, and information synthesis, to yield reliable results.
• Utilization of Tools and Technologies: Usage of Tools and techniques to create models which can predict the outcomes keeping all the constraints.
• Engineering and Society: Use contextually informed reasoning to evaluate societal, health, safety, legal, and cultural issues, as well as the resulting obligations relevant to professional engineering practice.
• Environment and sustainability: Recognize how professional engineering solutions affect society and the environment to demonstrate knowledge of sustainable development and its importance.
• Ethics: Apply ethical principles and adhere to professional ethics, responsibilities, and engineering practice norms.
• Individual and Team Growth: Perform effectively and efficiently as an individual expert while working with various teams, as a leader, and in multidisciplinary situations.
• Presentation & Communication: Effective presentations, clear instructions, and the ability to understand and write effective reports and design documents are all examples of how to effectively communicate with the engineering community and society at large about complex engineering activities.

Program at a Glance

• Enter this challenging and evolving field as a learner, and leave an expert with the right combination of skills.

Highlights

• Learn about data science techniques such as big data, data visualization, machine learning, and predictive modeling that develop the ability to investigate, analyze, manage, and visualize various datasets using cutting-edge technology.
• Apply data science and analytical techniques to a variety of data-rich challenges, think critically about the data, and make informed decisions using the data.
• Master the technical, analytical, and practical skills needed to address real-world, data-driven problems.
• Develop the skills required for quantitative thought leadership, such as the ability to collaborate and communicate effectively while considering the moral and legal implications of data analytics.

Clusters

• Essentials to Data management: Core courses emphasize the development of skills in data processing, machine learning, dynamic modeling, and other important technologies.
• Advances in Data management: In electives, students can investigate cutting-edge technology, such as artificial intelligence and machine learning algorithms, and understand advanced data science approaches and applications in specific industries.
• Application of the Concepts: As a part of the capstone project, students will have the opportunity to apply their developed skills to solve real-world problems.

Year 1

• It includes a wide range of fundamental courses, audit bridge courses, and open online courses. This introductory year acclimates students to data science fundamentals, Python programming for data processing, data analysis and visualization, operations and human resource management, and hands-on experience in spreadsheet modeling.
• It also has advanced courses such as data visualization with Tableau and data structures and algorithms in Python included in the second semester.

Sem 1
Initiation

• Business Communication
• Managerial Economics
• Principles of Management
• Marketing Management
• Organizational Behavior
• Statistics for Business: Decision Science
• Mathematics for Data Science
• Introduction to Python Programming
• MOOC 1

Sem 2
Development

• Business Finance & Accounting
• Managerial Skills for Effectiveness
• Operations/Project Management
• Machine Learning using Pandas and Scikit
• Data Visualisation using Tableau
• Spreadsheet Modeling
• Data Structures and Algorithms in Python
• MOOC 2
• Internships

Year 2

• Students are expected to have a basic understanding of Data Science, Statistics for Business, Python Programming, Mathematics for Data Science, and niche areas of Business Management by the beginning of the second year. With live industry-led projects, industry practitioners' conclaves, seminars, workshops, and an entrepreneurial mindset, the advanced courses prepare them for the real-world workforce.
• The students now have the maturity and clarity to select a slew of high-level electives that will assist them in completing Capstone Project -1 and an industry-based project, resulting in a smooth transition to the industry.

Sem 3
Empiricism & Application

• Advanced Machine Learning
• Natural Language Processing
• Operations Management
• Elective 1
• Elective 2
• Elective 3
• Entrepreneurship
• Ethics, Data Privacy & Security
• Capstone Project-1

Sem 4
Empiricism & Application

• Elective 4
• Elective 5
• Elective 6
• Capstone Project 2

Electives

• Web & Social Media Analytics
• Finance and Risk Analytics
• Healthcare Analytics
• HR Analytics
• Supply Chain Analytics
• Marketing Analytics
• Deep Learning
• Cloud Computing
• Big Data Analytics
• Computational Linguistics - Advanced Python

Career opportunities
As an MBA DS graduate from School of Engineering and Emerging Technology, you can pursue the following careers:

Data Analyst

• Data Modeler
• Machine Learning engineers
• Risk Analyst

Business analyst

• Data Architect
• Market Research Analyst

Data engineers

• Personal Financial Advisor
• Operations Analyst

Data scientists

• Supply Chain Analyst
• Business Analytics Specialist
• Management Consultant

Admission and degree requirements

• A full-time graduate or undergraduate studies in Engineering/ Architecture/ STEM (Science, Engineering, Technology and Mathematics)/ other relevant disciplines.
• Candidates should apply through the website of NICMAR University, and based on the documents submitted, applications are screened and considered for admission.
• Undergraduate final-year students can apply, provided they must complete their graduation before commencing this program.
• Applicants must have a minimum of 50% aggregate marks in graduation.
• Eligible candidates are invited to appear for the selection procedure, which includes the NICMAR Common Admission Test (NCAT), Group Discussion (GD), Personal Interview (PI), and Assessment of Application.