This module introduces the core concepts of prompt engineering, focusing on how to effectively design inputs to maximize generative AI performance. Learners will explore prompt types, common mistakes, and advanced techniques like Chain of Thought, Tree of Thought, and the Nova System. By the end, students will be able to craft structured, goal-oriented prompts tailored to various AI applications.

This module provides a foundational understanding of Generative AI concepts and their practical applications in business environments. It introduces leading AI tools such as ChatGPT, Claude, Gemini, and Microsoft Copilot, highlighting their unique capabilities and use cases. Learners will also explore a range of AI productivity tools designed to enhance communication, content creation, data handling, and overall business efficiency.

This module focuses on leveraging AI tools to enhance real-time data analysis, forecasting, and decision-making with minimal technical complexity. Learners will explore how to use familiar platforms like Excel for analytics, integrate AI features, and create impactful data visualizations. The module also covers identifying and applying AI-powered business analytics tools to drive smarter, faster insights across various functions.

This module explores how AI tools can streamline and optimize workflows and routine business processes across various functions. Learners will examine popular AI-powered workflow tools and discover practical methods for integrating AI into existing operational systems. Special focus is given to AI applications in both manufacturing and service industries to improve efficiency, accuracy, and scalability.

This module introduces the fundamentals of cybersecurity within the context of AI adoption, focusing on common threats and essential protection strategies. Learners will gain an understanding of cloud and endpoint security, governance frameworks, regulatory compliance, and risk mitigation techniques. The module also highlights the critical roles of governance in ensuring secure and responsible AI implementation across organizations.

This module provides an introduction to computer vision, covering key concepts and common tasks such as image recognition, object detection, and pattern analysis. Learners will explore real-world use cases of computer vision in manufacturing, including quality control and automation, as well as in service industries for tasks like customer interaction and surveillance. The module emphasizes how computer vision technologies can drive efficiency, accuracy, and innovation across diverse sectors.

This module explores the integration of robotics and automation in modern business environments, highlighting their transformative impact on operations and efficiency. Learners will examine key business applications, benefits, and strategic considerations for launching automation initiatives. Through real-world use cases, the module demonstrates how organizations across industries are leveraging robotics to reduce costs, increase productivity, and drive innovation.

This module introduces both general-purpose Generative AI tools and specialized solutions tailored to specific industries. Learners will explore how AI is being applied in sectors such as manufacturing, healthcare, financial services, marketing, retail, and legal to address unique challenges and improve outcomes. The module emphasizes selecting and applying the right tools for industry-specific needs to drive innovation, efficiency, and competitive advantage.

This hands-on module guides learners through the creation of a loan approval program using Generative AI techniques. In Project 1, students will build a basic loan approval system using Python to understand logic and structure. In Project 2, they will redesign the same system using GenAI prompts, showcasing how no-code AI solutions can streamline development and decision-making processes.