In this module you will get introduced to the concept of data, exploring its various types, including structured, unstructured, and semi-structured data. You will learn the importance of data in driving insights, decision-making, and AI/GenAI applications, while addressing common challenges such as data quality, privacy, and integration. You will also look at key principles for preparing data effectively for AI and GenAI, ensuring readiness for analysis, modeling, and deployment.

In this module, you'll learn the fundamentals of data analytics and how it enables data-driven decision-making. You'll explore how to perform exploratory data analysis to uncover patterns and trends, apply different analytical techniques based on the problem context, and translate insights into meaningful business decisions.

In this module, you'll learn what artificial intelligence is and explore its different types and real-world relevance. You'll understand how AI relates to machine learning and why these technologies matter in today’s world. You'll also explore current trends shaping the AI landscape. The module also introduces the fundamentals of machine learning, including common algorithms and the different types of machine learning techniques used to build intelligent systems.

In this module you will be introduced to Generative AI, Neural Networks, and Deep Learning, exploring their foundational principles and applications. You will learn about the different types of Generative AI, including Agentic AI, and introduces Transformers and Foundational Models, key architectures driving modern AI advancements.

In this module you will learn about career opportunities in AI across various industries and the essential skills required to work with AI teams effectively. You will also learn about the role AI plays across sectors and the need for ethical considerations in AI development and deployment.