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INTEGRATED-MBA in Analytics at Indian Institute of Technology Mandi
Mandi, Himachal Pradesh
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About the Specialization
What is Analytics at Indian Institute of Technology Mandi Mandi?
This Integrated B.Tech.-MBA program at Indian Institute of Technology Mandi, with a strong focus on Analytics, combines rigorous engineering foundations in Data Science and Engineering with advanced management principles. It uniquely prepares students for data-driven decision-making in the dynamic Indian business landscape. The curriculum emphasizes the application of analytical tools and techniques to solve complex business problems across various sectors, addressing the growing industry demand for skilled analytics professionals.
Who Should Apply?
This program is ideal for scientifically inclined students who have excelled in their B.Tech. DSE foundation and aspire to leadership roles at the intersection of technology and business. It targets fresh graduates seeking entry into high-impact analytics roles within Indian and global firms, as well as those looking to leverage their technical background with strategic management skills. Candidates passionate about data, problem-solving, and driving organizational growth through insights are best suited.
Why Choose This Course?
Graduates of this program can expect to pursue lucrative India-specific career paths as Data Scientists, Business Analysts, Analytics Consultants, and Product Managers in leading Indian IT, finance, e-commerce, and manufacturing companies. Entry-level salaries typically range from INR 8-15 LPA, with experienced professionals earning significantly more. The program aligns with professional certifications like those from SAS, IBM, and various data science platforms, enhancing career progression and leadership growth trajectories within Indian companies.
Student Success Practices
Foundation Stage
Master Programming & Math Fundamentals- (Semester 1-6)
Dedicate significant time to mastering core programming languages (Python/R), data structures, algorithms, linear algebra, and probability & statistics. These are the bedrock for advanced analytics. Actively participate in coding challenges and problem-solving platforms.
Tools & Resources
HackerRank, LeetCode, CodeChef, Khan Academy, NPTEL courses on Data Structures, Algorithms, Linear Algebra, Probability & Statistics
Career Connection
Strong fundamentals enable efficient data manipulation, algorithm development, and understanding of complex analytical models, crucial for data science roles.
Develop a Data Science Portfolio Early- (Semester 3-6)
Begin building a portfolio of mini-projects using real datasets from platforms like Kaggle. Focus on exploratory data analysis, data cleaning, and basic machine learning implementations. Document your code and insights on GitHub.
Tools & Resources
Kaggle, GitHub, Google Colab/Jupyter Notebooks, Datasets from government portals (e.g., Data.gov.in)
Career Connection
A well-curated portfolio demonstrates practical skills and initiative to recruiters for internships and entry-level positions in analytics.
Cultivate Peer Learning & Group Study- (Semester 1-6)
Form study groups with peers to discuss complex concepts, solve assignments collaboratively, and prepare for exams. Teach concepts to each other to solidify understanding. Actively participate in department workshops and seminars.
Tools & Resources
Microsoft Teams, Google Meet, Campus study rooms, Academic mentors, Student clubs
Career Connection
Enhances problem-solving abilities, communication skills, and fosters a collaborative mindset, essential for teamwork in professional analytics roles.
Intermediate Stage
Integrate Business Acumen with Analytics Tools- (Semester 7-8)
While learning core MBA subjects, actively seek connections to how data and analytics can enhance decision-making in finance, marketing, operations, and HR. Apply analytics concepts to case studies from Indian businesses.
Tools & Resources
Harvard Business Review cases, IIM case studies, Business news (Economic Times, Livemint), Excel, Basic BI tools
Career Connection
Develops a holistic understanding of business problems, enabling more impactful analytical solutions and positioning you for strategic analytics roles.
Pursue Relevant Industry Certifications- (Semester 7-8)
Supplement academic learning with certifications in widely used analytics tools and platforms. Examples include Python for Data Science (IBM), R for Data Science, Tableau/Power BI certifications, or cloud platforms like AWS/Azure/GCP for data analytics.
Tools & Resources
Coursera, edX, Udemy, Official vendor sites (Tableau, Microsoft, AWS), SAS certifications
Career Connection
Certifications validate practical skills, making you more marketable for internships and full-time roles in data analytics across various Indian industries.
Engage in Data-Driven Case Competitions- (Semester 7-8)
Participate in inter-college or national-level data analytics and business case competitions. These provide hands-on experience with real-world business challenges and competitive problem-solving under time constraints.
Tools & Resources
Websites like D2C (Dare2Compete), Unstop, Company-sponsored hackathons
Career Connection
Builds critical thinking, teamwork, presentation skills, and provides networking opportunities with industry professionals and potential employers in India.
Advanced Stage
Specialize through Electives & Capstone Project- (Semester 9-10)
Strategically choose electives that align with your desired analytics career path (e.g., Marketing Analytics, Financial Analytics). Dedicate substantial effort to your Capstone Project/Dissertation, aiming for a significant business impact or novel analytical insight.
Tools & Resources
Advanced statistical software, Machine learning libraries, Domain-specific datasets, Faculty mentors, Industry experts
Career Connection
Deep specialization makes you a highly sought-after expert in a niche area, while the project provides a strong talking point and proof of capability during placements.
Network Proactively & Seek Mentorship- (Semester 9-10)
Attend industry conferences, workshops, and alumni meets. Connect with professionals on LinkedIn, especially those in analytics leadership roles in India. Seek out mentors who can guide your career trajectory and provide insights into industry trends.
Tools & Resources
LinkedIn, Industry events, IIT Mandi alumni network, Professional associations (e.g., NASSCOM, TiE)
Career Connection
Networking opens doors to job opportunities, informational interviews, and helps in understanding industry expectations and navigating the job market effectively for senior roles.
Master Interview & Presentation Skills- (Semester 9-10)
Practice technical interviews focusing on data structures, algorithms, SQL, and machine learning concepts. Simultaneously, hone your business communication and presentation skills, preparing to articulate complex analytical findings to non-technical stakeholders.
Tools & Resources
Mock interviews (peer/alumni), Behavioral interview guides, Presentation workshops, Business case discussions
Career Connection
Crucial for converting opportunities. Excelling in both technical and soft skills ensures you stand out in the competitive Indian job market for senior analytics and management roles.
Program Structure and Curriculum
Eligibility:
- Admission to B.Tech. DSE through JEE (Advanced) rank. For MBA component, students must complete 3 years of B.Tech. DSE with a minimum CGPA of 6.0 and no backlogs.
Duration: 5 years (10 semesters)
Credits: 225 (135 B.Tech + 90 MBA) Credits
Assessment: Assessment pattern not specified
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS101 | Introduction to Computing | Core | 3 | Programming Paradigms, Variables and Data Types, Control Structures, Functions, Basic Algorithms, Debugging |
| MA101 | Calculus | Core | 3 | Limits and Continuity, Differentiation, Integration, Sequences and Series, Multivariable Calculus |
| MA102 | Linear Algebra | Core | 3 | Vector Spaces, Matrices and Determinants, Eigenvalues and Eigenvectors, Linear Transformations, Orthogonality |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS102 | Data Structures and Algorithms | Core | 4 | Arrays, Linked Lists, Stacks, Queues, Trees and Graphs, Sorting and Searching Algorithms, Hashing, Time and Space Complexity |
| MA103 | Probability and Statistics | Core | 3 | Probability Theory, Random Variables and Distributions, Sampling Distributions, Hypothesis Testing, Regression Analysis, ANOVA |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS202 | Object-Oriented Programming and Design | Core | 4 | Classes and Objects, Inheritance and Polymorphism, Encapsulation and Abstraction, Design Patterns, GUI Programming, Exception Handling |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS204 | Database Management Systems | Core | 4 | Relational Model, SQL Query Language, Database Design and Normalization, Transaction Management, Data Warehousing Concepts, Indexing and Query Optimization |
| CS205 | Artificial Intelligence | Core | 3 | Intelligent Agents, Search Algorithms, Knowledge Representation, Machine Learning Basics, Natural Language Processing Introduction, Planning and Reasoning |
| MA201 | Numerical Methods | Core | 3 | Error Analysis, Solution of Nonlinear Equations, Interpolation and Approximation, Numerical Differentiation and Integration, Solving Ordinary Differential Equations |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS301 | Machine Learning | Core | 4 | Supervised Learning, Unsupervised Learning, Regression Models, Classification Algorithms, Model Evaluation and Validation, Neural Networks Basics |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS304 | Data Mining | Core | 3 | Data Preprocessing, Association Rule Mining, Clustering Techniques, Classification Methods, Outlier Detection, Data Mining Applications |
| CS305 | Introduction to Big Data | Core | 3 | Big Data Characteristics, Hadoop Ecosystem, MapReduce Framework, Apache Spark, Distributed Storage Systems, Data Streaming Concepts |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MN701 | Managerial Economics | Core | 3 | Demand and Supply Analysis, Production and Cost Theory, Market Structures, Pricing Strategies, Macroeconomic Indicators, Business Cycles |
| MN702 | Financial Management | Core | 3 | Financial Statements Analysis, Capital Budgeting, Working Capital Management, Cost of Capital, Dividend Policy, Mergers and Acquisitions |
| MN703 | Marketing Management | Core | 3 | Marketing Mix (4Ps), Consumer Behavior, Market Segmentation, Targeting, Positioning, Product Life Cycle, Branding and Advertising, Digital Marketing Basics |
| MN704 | Operations Management | Core | 3 | Production Planning and Control, Quality Management, Inventory Management, Supply Chain Design, Project Management, Lean Operations |
| MN705 | Organizational Behaviour | Core | 3 | Individual Behavior in Organizations, Group Dynamics and Teamwork, Motivation Theories, Leadership Styles, Organizational Culture, Conflict Management |
| MN706 | Quantitative Methods for Management | Core | 3 | Linear Programming, Decision Theory, Simulation Modeling, Queuing Theory, Forecasting Techniques, Statistical Inference |
| MN707 | Data Analytics for Business Decisions | Core | 3 | Data Visualization, Descriptive Analytics, Predictive Modeling Basics, Prescriptive Analytics, Business Intelligence Tools, Data-Driven Decision Making |
| MN708 | Business Communication | Core | 3 | Verbal and Non-verbal Communication, Presentation Skills, Report Writing, Negotiation Strategies, Cross-cultural Communication, Digital Communication Ethics |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MN801 | Strategic Management | Core | 3 | Strategic Analysis Frameworks, Strategy Formulation, Strategy Implementation, Competitive Advantage, Corporate Governance, Strategic Control |
| MN802 | Human Resource Management | Core | 3 | HR Planning and Recruitment, Training and Development, Performance Appraisal, Compensation and Benefits, Industrial Relations, Employee Engagement |
| MN803 | Entrepreneurship and Innovation | Core | 3 | Idea Generation and Feasibility, Business Plan Development, Startup Ecosystem in India, Funding and Venture Capital, Innovation Management, Intellectual Property Rights |
| MN804 | Research Methods | Core | 3 | Research Design, Data Collection Techniques, Sampling Methods, Qualitative and Quantitative Research, Statistical Data Analysis, Report Writing and Ethics |
| MN805 | Business Law & Ethics | Core | 3 | Contract Law, Company Law Basics, Consumer Protection Act, Intellectual Property Law, Ethical Frameworks in Business, Corporate Social Responsibility |
| MN806 | Global Business Environment | Core | 3 | International Trade Theories, Foreign Exchange Markets, Global Economic Institutions, Geopolitical Factors, Cultural Impact on Business, Global Marketing Strategies |
| MN807 | Supply Chain Management | Core | 3 | Supply Chain Design, Logistics and Transportation, Sourcing and Procurement, Inventory Optimization, Supply Chain Risk Management, Sustainable Supply Chains |
| Elective | Business Intelligence & Data Warehousing | Elective - Analytics Focus | 3 | Data Marts and Data Lakes, ETL Processes, OLAP and OLTP, Reporting and Dashboarding Tools, Data Governance and Quality, Predictive Analytics Integration |
| Elective | Machine Learning for Business | Elective - Analytics Focus | 3 | Customer Segmentation, Recommendation Systems, Fraud Detection, Churn Prediction Models, Image and Text Analytics Basics, Model Deployment Strategies |
Semester 9
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MN999 | Project / Dissertation | Project | 6 | Problem Definition and Literature Review, Methodology Design and Data Collection, Advanced Data Analysis and Interpretation, Solution Development and Validation, Report Writing and Presentation, Spans Semesters 9 and 10 |
| Elective | Big Data Technologies | Elective - Analytics Focus | 3 | Hadoop Ecosystem (HDFS, YARN), Apache Spark for Data Processing, NoSQL Databases (Cassandra, MongoDB), Data Lake Architectures, Cloud Analytics Platforms (AWS, Azure, GCP), Real-time Data Processing |
| Elective | Predictive Modeling | Elective - Analytics Focus | 3 | Linear and Logistic Regression, Decision Trees and Random Forests, Time Series Analysis (ARIMA, Prophet), Ensemble Methods, Model Evaluation Metrics, Cross-Validation Techniques |
| Elective | Social Media Analytics | Elective - Analytics Focus | 3 | Sentiment Analysis, Social Network Analysis, Influence and Engagement Measurement, Social Media Campaign Tracking, Text Mining for Social Data, Ethical Considerations in Social Analytics |
| Elective | Operations Analytics | Elective - Analytics Focus | 3 | Supply Chain Optimization, Forecasting Demand and Capacity, Resource Allocation Models, Quality Control Analytics, Process Improvement using Data, Logistics Network Design |
Semester 10
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| Elective | Financial Analytics | Elective - Analytics Focus | 3 | Portfolio Optimization, Risk Management Models, Algorithmic Trading Strategies, Credit Scoring and Fraud Detection, Market Prediction Techniques, Derivative Pricing Analytics |
| Elective | Marketing Analytics | Elective - Analytics Focus | 3 | Customer Lifetime Value (CLV), Marketing Mix Modeling, Campaign Optimization, Web and Digital Analytics, A/B Testing and Experimentation, Market Basket Analysis |
| Elective | HR Analytics | Elective - Analytics Focus | 3 | Workforce Planning Analytics, Employee Turnover Prediction, Performance Analytics, Recruitment and Retention Optimization, Diversity, Equity, and Inclusion (DEI) Analytics, Employee Sentiment Analysis |
| Elective | Healthcare Analytics | Elective - Analytics Focus | 3 | Patient Outcomes Analysis, Epidemiological Data Modeling, Clinical Trials Analytics, Healthcare Resource Optimization, Public Health Data Management, Telemedicine Data Insights |
| Elective | Risk Analytics | Elective - Analytics Focus | 3 | Credit Risk Modeling, Market Risk Assessment, Operational Risk Management, Regulatory Compliance Analytics, Stress Testing Scenarios, Enterprise Risk Management |
