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MBA in Artificial Intelligence And Data Science at SRM Institute of Science and Technology
Chengalpattu, Tamil Nadu
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About the Specialization
What is Artificial Intelligence and Data Science at SRM Institute of Science and Technology Chengalpattu?
This Artificial Intelligence and Data Science program at SRM Institute of Science and Technology focuses on equipping future business leaders with advanced analytical and AI skills. It’s designed to meet the escalating demand in the Indian market for professionals who can leverage data-driven insights and AI technologies to drive strategic decision-making and foster innovation across industries.
Who Should Apply?
This program is ideal for fresh graduates seeking entry into data-driven business roles, as well as working professionals looking to upskill in AI and data science domains. It caters to those with a strong analytical aptitude or a background in quantitative fields, aiming to transition into high-growth areas like business intelligence, data strategy, and machine learning applications in India.
Why Choose This Course?
Graduates of this program can expect to secure roles such as Data Scientist, AI Consultant, Business Intelligence Manager, or Analytics Lead within Indian companies and MNCs. Entry-level salaries typically range from INR 6-10 LPA, with experienced professionals commanding significantly higher packages. The program also aligns with certifications in Python, machine learning, and data visualization tools, fostering strong career growth.
Student Success Practices
Foundation Stage
Master Business & Analytical Fundamentals- (Semester 1-2)
Focus diligently on core MBA subjects like Business Analytics, Accounting for Management, and Marketing Management. Understand how data underpins these traditional business functions to build a strong base for AI & DS application.
Tools & Resources
SRMIST library resources, Faculty office hours, Study groups, Coursera (Introduction to Data Analytics)
Career Connection
A solid grasp of business fundamentals ensures graduates can bridge the gap between technical AI/DS solutions and actual business problems, making them more valuable in managerial roles.
Develop Foundational Programming Skills (Python)- (Semester 1-2)
Even before specialized Python courses, start self-learning basic Python programming and data structures. This early exposure will make the ''''Python for Data Science'''' course much easier and allow for deeper understanding.
Tools & Resources
W3Schools Python tutorial, Python.org documentation, HackerRank (beginner problems), LeetCode (beginner problems)
Career Connection
Python is the lingua franca of Data Science. Early proficiency is crucial for internships and entry-level analytical roles, differentiating candidates during placements.
Engage in Early Case Study Analysis & Presentations- (Semester 1-2)
Actively participate in case study discussions and presentations across all subjects. This builds critical thinking, problem-solving, and communication skills essential for an analytics career.
Tools & Resources
SRMIST internal case competitions, Harvard Business Review case studies (if accessible), Feedback from professors
Career Connection
The ability to analyze complex business scenarios and articulate solutions is vital for roles that involve presenting data-driven insights to stakeholders.
Intermediate Stage
Undertake Industry-Relevant Mini-Projects- (Semester 3-4)
Beyond regular coursework, engage in personal or group mini-projects using real-world datasets from platforms like Kaggle. Apply concepts learned in Data Mining, Python for Data Science, and Machine Learning.
Tools & Resources
Kaggle, Google Colab, Jupyter Notebook, Python libraries (scikit-learn, Pandas, NumPy, Matplotlib)
Career Connection
A strong portfolio of projects demonstrates practical skills to recruiters, significantly boosting internship and placement prospects in AI/DS roles.
Network Actively with Professionals & Peers- (Semester 3-4)
Attend industry webinars, guest lectures, and workshops organized by SRMIST or external bodies. Connect with alumni and professionals on LinkedIn. Collaborate with peers on projects to build a professional network.
Tools & Resources
LinkedIn, SRMIST alumni network events, Industry association meetings (e.g., NASSCOM events)
Career Connection
Networking opens doors to mentorship, internship leads, and job opportunities that might not be publicly advertised, and provides insights into industry trends.
Prepare for Certifications in Key Technologies- (Semester 3-4)
While pursuing core subjects, prepare for industry-recognized certifications in areas like Python for Data Science (e.g., PCAP, PCEP), SQL, or specific cloud platforms (AWS/Azure/GCP Data Engineer associate certifications).
Tools & Resources
Official certification guides, Online training courses (Udemy, Coursera), Practice exams
Career Connection
Certifications validate skills beyond the degree, making candidates more competitive and demonstrating initiative to potential employers in the Indian tech market.
Advanced Stage
Execute a Robust Summer Internship & Business Research Project- (Summer after Semester 2, and Semester 4)
Choose an internship that provides significant exposure to AI/DS projects. Treat the Business Research Project as a capstone, applying all learned concepts to solve a real business problem, preferably with an industry partner.
Tools & Resources
Mentorship from faculty and industry guides, Company resources, Advanced analytical software
Career Connection
A strong internship can lead to a Pre-Placement Offer (PPO), and a well-executed research project showcases depth of knowledge and problem-solving abilities crucial for senior analytical roles.
Specialize and Deepen Expertise in Chosen AI/DS Niche- (Semester 3-4)
Identify a sub-area within AI/DS (e.g., NLP, Computer Vision, Marketing Analytics, Financial AI) that aligns with career goals. Take relevant electives and focus projects in this niche.
Tools & Resources
Advanced online courses, Research papers, Specialized libraries/frameworks (TensorFlow, PyTorch, SpaCy), Participation in hackathons
Career Connection
Deep specialization makes candidates highly desirable for roles requiring specific expertise, allowing for targeted career paths and faster growth in niche areas within the Indian market.
Intensive Placement Preparation & Mock Interviews- (Semester 4)
Dedicate time to mock interviews (technical, HR, case-based), resume building, and developing strong presentation skills. Practice explaining AI/DS concepts clearly and concisely to both technical and non-technical audiences.
Tools & Resources
SRMIST''''s placement cell, Alumni mentors, Online interview platforms (Pramp, InterviewBit), Industry interview guides
Career Connection
Effective interview performance and a well-articulated profile are paramount for securing desirable placements in top analytics and AI companies.
Program Structure and Curriculum
Eligibility:
- A pass in any Bachelor''''s Degree with minimum aggregate of 50% in any discipline from a recognized University. Performance in SRMJEEM / CAT / MAT / XAT / GMAT / CMAT / NMAT.
Duration: 2 years (4 semesters)
Credits: 90 Credits
Assessment: Internal: 40% (for theory), 60% (for practicals), External: 60% (for theory), 40% (for practicals)
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22MB101T | Principles of Management | Core | 3 | Management Theories, Planning and Organizing, Staffing and Directing, Controlling and Coordination, Decision Making |
| 22MB102T | Business Economics | Core | 3 | Demand and Supply Analysis, Production and Cost, Market Structures, Macroeconomic Concepts, Fiscal and Monetary Policies |
| 22MB103T | Accounting for Management | Core | 3 | Financial Accounting Principles, Cost Accounting, Management Accounting Techniques, Budgeting and Variance Analysis, Financial Statement Analysis |
| 22MB104T | Organizational Behaviour | Core | 3 | Individual Behavior, Group Dynamics, Leadership and Motivation, Organizational Culture, Change Management |
| 22MB105T | Marketing Management | Core | 3 | Marketing Concepts, Product and Brand Management, Pricing Strategies, Distribution Channels, Promotion and Digital Marketing |
| 22MB106T | Business Analytics | Core | 3 | Data Analysis Fundamentals, Statistical Tools for Business, Descriptive Analytics, Predictive Modeling Basics, Data Visualization Techniques |
| 22MB107P | Business Communication & Negotiation Skills Lab | Practical | 1 | Verbal and Non-verbal Communication, Presentation Skills, Business Report Writing, Negotiation Strategies, Cross-cultural Communication |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22MB201T | Financial Management | Core | 3 | Capital Budgeting, Working Capital Management, Cost of Capital, Financial Markets and Institutions, Risk and Return |
| 22MB202T | Human Resource Management | Core | 3 | HR Planning and Recruitment, Training and Development, Performance Management, Compensation and Benefits, Industrial Relations |
| 22MB203T | Operations Management | Core | 3 | Production Planning and Control, Inventory Management, Quality Management, Supply Chain Management, Project Management |
| 22MB204T | Research Methods for Management | Core | 3 | Research Design, Data Collection Methods, Sampling Techniques, Hypothesis Testing, Report Writing and Ethics |
| 22MB205T | Legal Aspects of Business | Core | 3 | Contract Law, Company Law, Consumer Protection Act, Intellectual Property Rights, Cyber Laws |
| 22MB206T | Entrepreneurship Development | Core | 3 | Concept of Entrepreneurship, Business Idea Generation, Business Plan Development, Funding and Startup Ecosystem, Small Business Management |
| 22MB207P | Soft Skills and Personality Development Lab | Practical | 1 | Self-awareness and Goal Setting, Time and Stress Management, Interpersonal Skills, Group Discussion Techniques, Interview Preparation |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22MBE701T | Foundation of Artificial Intelligence | Elective (AI & DS Specialization) | 3 | Introduction to AI and ML, Search Algorithms, Knowledge Representation, Expert Systems, AI Applications in Business |
| 22MBE702T | Data Mining and Data Warehousing | Elective (AI & DS Specialization) | 3 | Data Preprocessing, Association Rule Mining, Classification and Prediction, Clustering Techniques, Data Warehouse Architecture |
| 22MBE703T | Python for Data Science | Elective (AI & DS Specialization) | 3 | Python Programming Fundamentals, NumPy and Pandas for Data Manipulation, Data Visualization with Matplotlib, Statistical Analysis with Python, Introduction to Sci-kit Learn |
| 22MBE704T | Big Data Analytics | Elective (AI & DS Specialization) | 3 | Introduction to Big Data, Hadoop Ecosystem (HDFS, MapReduce), Spark Framework, NoSQL Databases, Big Data Tools and Technologies |
| 22MB308P | Summer Internship Project | Practical (Mandatory) | 2 | Project Planning and Execution, Data Collection and Analysis, Report Writing, Presentation Skills, Industry Exposure |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22MBE705T | Machine Learning for Business | Elective (AI & DS Specialization) | 3 | Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering), Decision Trees and Random Forests, Support Vector Machines, Model Evaluation and Deployment |
| 22MBE706T | Deep Learning and Neural Networks | Elective (AI & DS Specialization) | 3 | Neural Network Architecture, Backpropagation, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Applications of Deep Learning |
| 22MBE707T | Natural Language Processing and Computer Vision | Elective (AI & DS Specialization) | 3 | Text Preprocessing and Analysis, Sentiment Analysis, Image Processing Basics, Object Detection, Generative Models |
| 22MBE708T | Data Visualization and Storytelling | Elective (AI & DS Specialization) | 3 | Principles of Data Visualization, Tools (Tableau, Power BI), Dashboard Design, Storytelling with Data, Interactive Visualizations |
| 22MB409P | Business Research Project | Project (Mandatory) | 6 | Problem Formulation, Literature Review, Methodology Design, Data Analysis and Interpretation, Report Writing and Viva Voce |
