Program Overview
In the rapidly evolving business landscape, mastering data science, artificial intelligence (AI), machine learning (ML), deep learning, and generative AI is crucial for managers seeking to enhance their understanding and drive innovation within their organizations. This intensive, hands-on program is tailored to equip business executives with the essential skills and tools required to navigate and leverage a data-rich environment effectively. Participants will engage in practical sessions that allow them to apply these technologies, thereby enhancing decision-making and strategic planning across various business functions.
Program Objectives
- Develop Practical Skills in Data Science and AI: Equip participants with both foundational and advanced techniques for effective data analysis and predictive modeling.
- Explore Advanced AI Applications: Introduce transformative AI technologies, including Machine Learning, Natural Language Processing (NLP), deep learning, and generative AI, with a focus on their practical business applications.
- Gain Hands-on Experience: Utilize real-world case studies and datasets to simulate business environments where data science can drive strategic outcomes.
- Empower Leadership in Data-Driven Initiatives: Enable participants to lead data-centric strategies and cultivate a culture of informed decision-making within their organizations.
Program Details
Program Dates: 27-29 March, 2025 (3 Days)
Timings: 9:30 AM – 4:30 PM
Mode of delivery: In-Person Class Room
Program Fee: INR 24000 per participant (plus 18% GST)
Prerequisites :
Participants are expected to have a basic understanding of data analysis and business fundamentals. Familiarity with statistical concepts and programming languages such as Python will be beneficial but not mandatory.
Who May Attend
This program is tailored for
- Managers Seeking Enhanced Analytical Capabilities.
- Managers of Data-Driven Projects
- Decision-makers across industries who seek to harness the power of data and AI
Key Topics
- Data Analysis with Microsoft Excel: Techniques for data cleaning, analysis, and visualization to extract actionable insights.
- Data Visualization using Tableau: Training in modern data visualization tools to effectively interpret and present business data.
- Machine Learning Model Building with Python: Practical experience in constructing, testing, and analyzing ML models to anticipate market trends and customer behavior.
- Natural Language Processing: Exploring Python applications in NLP to analyze unstructured data and automate decision-making processes.
- Generative AI: Hands-on experience with generative AI, foundations of Deep Learning, large language models (LLMs) and prompt engineering, while understanding the business value and ethical implications of AI adoption.
Specific Modules:
DESCRIPTIVE ANALYTICS
- Data Driven Decisions using Descriptive Analytics
- Data Analysis and Visualization - Hands on with MS Excel
- Data Story Telling using Tableau – Hands On
- Prediction Model using Multiple Linear Regression
- Python Programming - Hands On
MACHINE LEARNING (ML)
- Supervised Learning
- Linear regression
- Logistic regression
- Decision Tree
- Unsupervised learning: Customer Segmentation and Market Basket Analysis
NATURAL LANGUAGE PROCESSING (NLP)
- Tokenization
- Vectorization
- Sentiment analysis
- Topic modeling
GENERATIVE ARTIFICIAL INTELLIGENCE (GenAI)
- Introduction to Generative Artificial Intelligence (GAI)
- Fundamentals of Deep Learning
- Large language models
- Prompt engineering:
- Business value of GAI
- Responsible AI
Pedagogy :
- Hands on Sessions with real world dataset using Python, Tableau and MS Excel.
- Classroom Discussion using Use Cases.
Key Takeaways
- Comprehensive Data Analysis Skills: Proficiency in using Excel, Tableau and Python for a wide range of analytical tasks, from basic data manipulation to complex algorithmic modeling.
- Applied AI Techniques: Practical experience in implementing AI solutions, including ML, NLP, and Generative AI, in diverse business scenarios.
- Leadership in Data-Driven Strategy: Insights into leading and nurturing data-driven projects and initiatives within organizations.
Program Directors
Dr. Sridhar Vaithianathan
Prof. (Dr.) Sridhar Vaithianathan is the Director of the Centre of Excellence in Analytics & Data Science and Professor at SBM, SVKM's NMIMS, Mumbai. With over two decades of experience in teaching, research, and consultancy, he is passionate about Statistics, Business Analytics, Machine Learning, and Data Visualization, which are also his teaching interests. Under his leadership, the MBA-Business Analytics program at NMIMS has seen remarkable growth in student intake and placement packages. An award-winning academician, Dr. Sridhar has conducted numerous workshops on Machine Learning, Data Visualization, and Structural Equation Modeling. His research interests include technology adoption and sports analytics. He has published in national and international journals. He is active in consultancy projects and dedicated to fostering industry-academia collabora_ons to enhance management education in India. Dr. Sridhar holds a Ph.D. in Management from Icfai University, an MBA from the Na_onal Ins_tute of Technology, Warangal, and a B.E. in Electronics and Communication from M.S. University, Tamil Nadu.
Dr. Siby Abraham
Dr. Siby Abraham is a Professor of Data Science with over three decades of experience at leading academic institutions. He earned his PhD in Computer Science, specializing in Machine Learning from the University of Mumbai, and holds a Master's degree in Mathematics. His expertise includes Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP). With more than twenty years of teaching experience in AI and related fields, Dr. Abraham has supervised numerous PhD candidates in Computer Science, focusing on ML and DL. He has published approximately forty-five international research papers and serves on the editorial boards of two international journals.