- AI Agents
Explains what AI agents are, their characteristics, types, and real-world applications, including multi-agent systems and their impact on automation and decision-making.
- Agent Usage
This module explores the shift from monolithic models to compound AI systems highlighting how integrating models with tools and databases enables more flexible, accurate, and adaptable solutions for real-world tasks.
- Robotics Automation
This module introduces robotics and automation, explaining how robots work how AI technologies are integrated, and how robotics enables automation across industries, including the role of cobots and robotic process automation.
- AI and Business
This module explores how AI is transforming business operations, automating workflows, enhancing decision-making, and driving efficiency and innovation across industries such as customer service, HR, accounting, marketing manufacturing, and healthcare.
- Become AI Value Creator
This module explores the evolution from traditional AI to generative AI and foundation models, explaining modes of AI consumption, the importance of open knowledge, and the impact of value creation and extraction in the AI economy.
- RAG Introduction
This document introduces retrieval-augmented generation (RAG), its components benefits, limitations of generative AI, and practical applications, with a focus on implementation using Google Cloud tools.
- More About RAGs
This document explores the challenges of large language models and how retrieval-augmented generation (RAG) addresses issues of outdated knowledge and lack of sources, with practical examples.
- Adopting AI in Business
This document outlines the benefits, real-world examples, and step-by-step process for adopting artificial intelligence in business operations, with a focus on planning, data readiness, and continuous improvement.
- Adoption Framework
This document explains the IBM AI Ladder framework for AI adoption, details each stage from data collection to business integration, and explores the shift from +AI to AI+ for holistic transformation.
- Framework Adoption by Companies
This document compares AI adoption frameworks used by Amazon, OpenAI, and Facebook, detailing their phases and tools for effective, ethical, and scalable AI integration in business operations.
- AI Tools Utilisation
This document explores the practical use of AI tools across industries highlighting real-world applications for research, healthcare, content creation, language learning, customer support, and data analysis.
- AI Career Opportunities
This document explores the evolving landscape of AI careers, highlighting technical and non-technical roles, required skills, and strategies for transitioning into the AI field across diverse industries.
- Human vs AI
This document explores the strengths and limitations of human and AI decision-making, using fraud detection as a case study, and examines how augmented intelligence can combine the best of both.
- Module Summary
This document summarizes key concepts from the module, including AI agents robotics, cobots, RPA, generative AI, business adoption, AI tools, and career opportunities, providing a comprehensive overview of modern AI applications.