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MBA in Data Analytics Sibm Scmhrd Scit at Symbiosis International University
Pune, Maharashtra
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About the Specialization
What is Data Analytics (SIBM, SCMHRD, SCIT) at Symbiosis International University Pune?
This MBA in Data Analytics program at Symbiosis International University (through SIBM Pune) focuses on equipping future leaders with cutting-edge analytical skills and business acumen. It integrates core management principles with advanced data science techniques, preparing professionals to leverage data for strategic decision-making in the dynamic Indian industry landscape. The program''''s interdisciplinary approach addresses the critical demand for data-driven expertise across various sectors in India.
Who Should Apply?
This program is ideal for fresh graduates from diverse backgrounds, including engineering, commerce, and science, who aspire to build careers in data-intensive roles. It also caters to working professionals seeking to upskill and transition into data analytics, business intelligence, or consulting. Individuals with a keen interest in problem-solving using quantitative methods and a desire to impact business strategy will find this specialization highly rewarding in the Indian context.
Why Choose This Course?
Graduates of this program can expect to secure roles such as Data Scientist, Business Analyst, Marketing Analyst, Financial Analyst, or Consultant in leading Indian and multinational corporations operating in India. Entry-level salaries typically range from INR 6-12 LPA, with significant growth potential as experience accrues. The curriculum aligns with industry-recognized certifications in data science and analytics, enhancing employability and professional growth trajectories in Indian companies.
Student Success Practices
Foundation Stage
Master Foundational Analytical Tools- (Semester 1-2)
Dedicate significant time to mastering Python programming for data analysis and core statistical concepts. Utilize online platforms for coding practice and problem-solving, ensuring a strong base for advanced subjects. Early proficiency is key to understanding complex data problems.
Tools & Resources
HackerRank, LeetCode (Python), Kaggle (introductory datasets), Khan Academy (Statistics), Coursera courses on Python
Career Connection
A strong command of Python and statistics is non-negotiable for most data roles in India, enabling efficient data manipulation, analysis, and building foundational models for future advanced applications.
Build Business Acumen Early- (Semester 1-2)
Actively engage with core management subjects like Marketing, Finance, and Operations. Understand how data analytics integrates into these functions by reading business case studies and industry news, especially focusing on Indian companies and their data strategies.
Tools & Resources
Harvard Business Review, Economic Times, Business Standard, NASSCOM reports, McKinsey/BCG insights
Career Connection
Combining analytical skills with solid business understanding is crucial for becoming a valuable data professional who can translate insights into actionable business strategies, a key demand in the Indian market.
Participate in Peer Learning Groups- (Semester 1-2)
Form study groups with peers to discuss complex concepts, solve problems collaboratively, and prepare for exams. Teach each other challenging topics to solidify understanding and develop communication skills vital for team-based analytics projects.
Tools & Resources
WhatsApp groups, Google Meet, shared notes on Notion or Google Docs
Career Connection
Enhances problem-solving through diverse perspectives and improves teamwork abilities, which are essential soft skills sought by Indian employers in collaborative data science environments.
Intermediate Stage
Engage in Real-World Data Projects- (Semester 3)
Seek opportunities for short-term projects, freelancing, or academic assignments that involve real-world datasets. Focus on applying machine learning and predictive analytics techniques to solve practical business problems, building a practical portfolio.
Tools & Resources
Kaggle competitions, local business hackathons, university research projects, LinkedIn for project opportunities
Career Connection
Builds a portfolio of practical experience, demonstrating capability to future employers in India, especially for roles requiring direct application of analytical models and problem-solving skills.
Develop Strong Data Visualization Skills- (Semester 3)
Practice creating compelling data visualizations and dashboards using industry-standard tools. Focus on communicating insights effectively through storytelling with data, a crucial skill for presenting findings to business stakeholders in any industry.
Tools & Resources
Tableau Public, Power BI Desktop, D3.js (for advanced users), YouTube tutorials, data storytelling books
Career Connection
Essential for a Business Analyst or Data Analyst role in Indian companies, where explaining complex data to non-technical audiences is a daily requirement for driving data-driven decisions.
Network with Industry Professionals- (Semester 3)
Attend industry seminars, workshops, and guest lectures to interact with data analytics professionals. Leverage LinkedIn for informational interviews and to build professional connections, focusing on the vibrant Indian analytics ecosystem.
Tools & Resources
LinkedIn, industry conferences (e.g., NASSCOM Data Science Summit, Analytics India Magazine events), alumni network events
Career Connection
Opens doors to internship and placement opportunities, provides mentorship, and offers insights into current industry trends and demands in the Indian job market, fostering career growth.
Advanced Stage
Deepen Specialization through Electives and Thesis- (Semester 4)
Strategically choose electives that align with desired career paths (e.g., Financial Analytics, Marketing Analytics). Dedicate rigorous effort to the Master Thesis, using it as an opportunity to apply advanced AI/Deep Learning techniques to a significant business problem.
Tools & Resources
Academic journals, research papers, specialized libraries for chosen domain, advanced coding environments (e.g., Google Colab)
Career Connection
Differentiates candidates for niche roles, demonstrates deep expertise in a specific domain, and provides a substantial talking point for job interviews at top-tier analytics firms in India.
Prepare for Placement Drives and Interviews- (Semester 4)
Actively participate in mock interviews, resume workshops, and group discussions organized by the college''''s placement cell. Focus on behavioral questions, case studies, and technical interview preparation, specifically tailored for Indian companies and their hiring processes.
Tools & Resources
University placement cell resources, Glassdoor (for company-specific interview questions), mock interview platforms, peer practice sessions
Career Connection
Directly impacts success in securing desired placements with leading companies in India, ensuring readiness for competitive recruitment processes and a confident entry into the professional world.
Cultivate Continuous Learning Mindset- (Semester 4)
Stay updated with the latest trends in AI, machine learning, and data governance through online courses, blogs, and industry publications. Develop a habit of lifelong learning beyond the academic curriculum to remain competitive.
Tools & Resources
Online platforms (e.g., Coursera, edX, DataCamp), Towards Data Science blog, Analytics Vidhya, industry webinars
Career Connection
Ensures long-term career growth and adaptability in the rapidly evolving data analytics field, making graduates valuable assets to Indian organizations seeking innovation and expertise.
Program Structure and Curriculum
Eligibility:
- Graduate with minimum 50% marks (45% for SC/ST) in any discipline from a recognized University. Students appearing for final year examinations can also apply, subject to obtaining a minimum of 50% marks (45% for SC/ST). A candidate must have appeared for the Symbiosis National Aptitude (SNAP) Test.
Duration: 2 years / 4 semesters
Credits: 96 Credits
Assessment: Assessment pattern not specified
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 201010101 | Business Statistics | Core | 3 | Descriptive Statistics, Probability Distributions, Hypothesis Testing, Regression Analysis, Correlation |
| 201010102 | Microeconomics | Core | 3 | Demand and Supply, Consumer Behavior, Production Costs, Market Structures, Pricing Strategies |
| 201010103 | Management Accounting | Core | 3 | Cost Concepts, Budgeting, Variance Analysis, Performance Measurement, Decision Making |
| 201010104 | Organizational Behaviour | Core | 3 | Individual Behavior, Group Dynamics, Motivation Theories, Leadership Styles, Organizational Culture |
| 201010105 | Marketing Management | Core | 3 | Marketing Mix (4Ps), Consumer Buying Behavior, Market Segmentation, Product Life Cycle, Branding and Positioning |
| 201010106 | Operations Management | Core | 3 | Process Design, Quality Management, Inventory Control, Supply Chain Management, Project Planning |
| 201010107 | Database Management Systems | Core | 3 | Relational Databases, SQL Queries, Data Modeling, Database Design, Data Warehousing Concepts |
| 201010108 | Python Programming for Data Analytics | Core | 3 | Python Fundamentals, Data Structures in Python, NumPy and Pandas Libraries, Data Manipulation, Basic Visualization with Matplotlib |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 201010109 | Macroeconomics | Core | 3 | National Income Accounting, Inflation and Unemployment, Monetary Policy, Fiscal Policy, International Trade |
| 201010110 | Financial Management | Core | 3 | Capital Budgeting, Working Capital Management, Financial Markets, Risk and Return, Valuation Models |
| 201010111 | Human Resource Management | Core | 3 | HR Planning, Recruitment and Selection, Performance Management, Training and Development, Industrial Relations |
| 201010112 | Research Methodology | Core | 3 | Research Design, Data Collection Methods, Sampling Techniques, Statistical Analysis, Report Writing |
| 201010113 | Legal Aspects of Business | Core | 3 | Contract Law, Company Law, Consumer Protection Act, Intellectual Property Rights, Cyber Law |
| 201010114 | Marketing Research & Consumer Analytics | Core | 3 | Market Research Design, Survey Methods, Consumer Behavior Insights, Market Segmentation Analytics, Predictive Modelling in Marketing |
| 201010115 | Machine Learning for Business Analytics | Core | 3 | Supervised Learning, Unsupervised Learning, Regression Models, Classification Algorithms, Model Evaluation Metrics |
| 201010116 | Data Visualization & Storytelling | Core | 3 | Principles of Visualization, Data Storytelling, Dashboard Design, Tools (Tableau/Power BI), Infographics and Reporting |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 201010117 | Big Data Technologies | Core | 3 | Hadoop Ecosystem, Spark Framework, NoSQL Databases, Distributed Computing, Data Lakes and Data Warehouses |
| 201010118 | IT Infrastructure & Cloud Computing | Core | 3 | Cloud Models (IaaS, PaaS, SaaS), Virtualization Technologies, Cloud Security, AWS/Azure Fundamentals, Data Centers and Networking |
| 201010119 | Predictive Analytics | Core | 3 | Time Series Analysis, Forecasting Models, Regression Techniques, Classification Trees, Model Validation |
| 201010120 | Prescriptive Analytics | Core | 3 | Optimization Techniques, Simulation Models, Decision Analysis, Linear Programming, What-If Analysis |
| 201010121 | Financial Analytics | Elective | 4 | Financial Modeling, Risk Management Analytics, Portfolio Optimization, Algorithmic Trading Strategies, Credit Risk Scoring |
| 201010122 | Marketing Analytics | Elective | 4 | Customer Segmentation, Campaign Optimization, Churn Prediction, Pricing Analytics, Digital Marketing Metrics |
| 201010123 | HR Analytics | Elective | 4 | Workforce Planning, Employee Churn Analysis, Performance Analytics, Recruitment Optimization, HR Metrics and Dashboards |
| 201010124 | Supply Chain Analytics | Elective | 4 | Demand Forecasting, Inventory Optimization, Logistics Analytics, Network Design, Supplier Performance Analysis |
| 201010125 | Healthcare Analytics | Elective | 4 | Clinical Data Analysis, Population Health Management, Predictive Diagnostics, Hospital Operations Analytics, Health Outcomes Research |
| 201010126 | Summer Internship Project | Project | 6 | Project Planning, Data Collection and Cleaning, Analytical Model Application, Report Writing, Presentation of Findings |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 201010127 | Artificial Intelligence & Deep Learning | Core | 4 | Neural Networks, Deep Learning Architectures, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Natural Language Processing with Deep Learning |
| 201010128 | Data Governance & Ethics | Core | 4 | Data Privacy Regulations (GDPR, India''''s DPDPA), Compliance Frameworks, Data Security Measures, Ethical AI Principles, Data Quality Management |
| 201010121 | Financial Analytics (Elective from Sem 3 Basket) | Elective | 4 | Financial Modeling, Risk Management Analytics, Portfolio Optimization, Algorithmic Trading Strategies, Credit Risk Scoring |
| 201010122 | Marketing Analytics (Elective from Sem 3 Basket) | Elective | 4 | Customer Segmentation, Campaign Optimization, Churn Prediction, Pricing Analytics, Digital Marketing Metrics |
| 201010123 | HR Analytics (Elective from Sem 3 Basket) | Elective | 4 | Workforce Planning, Employee Churn Analysis, Performance Analytics, Recruitment Optimization, HR Metrics and Dashboards |
| 201010124 | Supply Chain Analytics (Elective from Sem 3 Basket) | Elective | 4 | Demand Forecasting, Inventory Optimization, Logistics Analytics, Network Design, Supplier Performance Analysis |
| 201010125 | Healthcare Analytics (Elective from Sem 3 Basket) | Elective | 4 | Clinical Data Analysis, Population Health Management, Predictive Diagnostics, Hospital Operations Analytics, Health Outcomes Research |
| 201010129 | Master Thesis / Dissertation | Project | 10 | Research Problem Formulation, Advanced Data Collection and Analysis, Model Development and Validation, Comprehensive Report Writing, Thesis Defense Preparation |
