This introductory module orients learners to the Data Analytics, GenAI, and Adaptive Systems program in partnership with IHFC – TIH of IIT Delhi, setting the foundation for the structured learning journey ahead.

This module builds proficiency in using Excel for business analytics, covering essential functions, data analysis techniques, and dashboard creation to derive actionable insights from business data.

This module covers SQL fundamentals and advanced querying techniques for data acquisition and manipulation, including database management, joins, subqueries, views, and indexing for efficient data retrieval.

This module provides comprehensive coverage of ETL processes, from data extraction and transformation to loading, automation, and performance optimization, preparing learners to build robust data pipelines for analytics workflows.

This module develops skills in data visualization using Tableau, covering chart creation, interactive dashboards, filters, parameters, and advanced visual types such as heat maps, treemaps, and Pareto charts for compelling data storytelling.

This module introduces Python programming from the ground up, covering core programming concepts including data types, operators, control flow, loops, and functions to build a strong foundation for data analytics applications.

This module applies Python to real-world data analytics tasks, covering data packages, statistical analysis, hypothesis testing, exploratory data analysis, visualization, and an introduction to machine learning and generative AI concepts.

This module builds foundational literacy in Generative AI, exploring machine learning types, generative algorithms, large language models, image and video generation tools, open-source AI platforms, and prompt engineering techniques.

This module explores practical applications of Generative AI in data analytics workflows, including data augmentation, AI-driven visualization, ETL optimization, forecasting, and ethical considerations in integrating GenAI into real-world analytics pipelines.

This module examines the ethical dimensions of data analytics, covering legal frameworks, data privacy, algorithmic bias, responsible visualization, and the societal implications of data-driven decision-making.

This culminating project module integrates all prior learning as students apply Excel, Python, SQL, Tableau, and other tools to solve real-world data challenges, with mentor support, demonstrating end-to-end analytics expertise to potential employers.

This elective masterclass, led by IHFC - TIH of IIT Delhi faculty, explores adaptive systems in changing environments, covering control strategies, software adaptation, and real-world applications in aerospace, robotics, and industrial systems.

This elective industry masterclass explores agentic AI systems in analytics, covering autonomous agent design, task automation including data prep and anomaly detection, and hands-on case studies for building ethical, self-driving analytics solutions.

This elective module equips learners with advanced Power BI skills for data analysis and interactive dashboard creation, covering responsive dashboards, Quick Insights, natural language Q&A, report design best practices, and workflow optimization for impactful data-driven narratives.

This elective module applies R programming to statistical analysis and data analytics, covering regression, clustering, and visualization techniques to derive insights from complex datasets.

This elective module covers foundational data concepts and Microsoft Azure's data services, including relational and non-relational databases, big data, cloud storage, Cosmos DB, data warehousing, real-time analytics, and visualization on the Azure platform.