Artificial Intelligence Essentials (AIE) v1

Module 01 Introduction to Artificial Intelligence

LO#01: Understand the Similarities, Differences, and Collaboration between Human and Artificial Intelligence

• Human Intelligence
• What is Artificial Intelligence?
• AI vs Human Intelligence
• AI and Human Intelligence: Partners, Not Competitors
• Human-AI Collaboration: Skills and Mindsets for Success
• What is NOT AI?
• Limitations of Current AI

LO#02: Explain How Data, Algorithms, and Models form the Foundation of AI Systems

• Fundamental Concepts of AI
• Role of Data and Algorithms in AI
• Model: The Outcome of Learning
• How AI Works Differently from Traditional Software
• AI vs Traditional Software: Key Capabilities

LO#03: Summarize Major Milestones and Developments in the Evolution of AI

• Early AI History
• Modern AI History

LO#04: Explore Recent Advancements and Future Directions Shaping AI Technologies

• Emerging Trends in AI
• Technological Advancements Driving AI
• The Road Ahead: Opportunities and Challenges
• Module Summary

 

Module 02 Everyday AI Tools and Use cases

LO#01: Identify Common AI Technologies Used in Daily Life

• Impact of AI in Daily Life
• AI in Entertainment
• AI as Personal Assistants
• AI in Smart Homes
• AI in Fitness
• AI in Shopping and E-Commerce
• AI in Customer Service
• AI in Travel and Navigation
• AI in Budgeting

LO#02: Recognize AI Tools in the Workplace and How they Improve Workflow and Decision-Making

• AI: The Smart Work Companion
• Optimize Workplace Productivity with AI
• AI-Driven Collaboration in the Workplace
• AI-Driven Decision-Making at Work
• AI-Powered Financial Decision Support
• Optimize Hiring and Job Search with AI
• AI Tools in Workspace

LO#03: Explain How AI Improves Manufacturing and Industrial Processes

• Smart Industry with AI
• AI-Powered Predictive Maintenance of Machinery
• Product Quality Inspection with AI
• AI in Supply Chain Optimization
• AI-Powered Cobots in Manufacturing

LO#04: Explain How AI Improves Transportation Safety, Efficiency, and Sustainability

• Making Travel Smarter with AI
• AI in Autonomous Vehicles
• Smart Traffic Management with AI
• Smart Logistics and Fleet Management
• Safety and Collision Detection Systems
• Disaster Management: Google AI for Wildfire Detection
• Sustainability: John Deere’s AI for Precision Agriculture
• Renewable Energy Management using AI

LO#05: Identify How AI Personalizes Learning and Provides Feedback

• AI in Education: Transforming the Future of Learning
• AI-Driven Intelligent Tutoring Systems
• AI-Driven Grading and Feedback Systems
• AI-Driven Student Performance Analytics
• AI-Driven Adaptive Learning Platforms

LO#06: Identify How AI Improves Security by Detecting Threats, Protecting Data, and Ensuring Privacy

• Smarter Security Starts with AI
• AI in Cybersecurity
• AI for Data Privacy & Identity Verification
• Module Summary

 

Module 03 Building Blocks of AI

• AI and its Disciplines

LO#01: Understand the Role of Data for Effective AI Systems

• Data
• Importance of Data Quality for Effective AI
• AI Data Categories and Origins
• Types of AI Data
• AI Data Flow Basics
• Structured vs. Unstructured Datasets
• Labeled vs. Unlabeled Datasets
• Creating Datasets for AI Models
• Ways to Sample Data

LO#02: Identify the Different AI Models and Explain How They are Developed and Trained

• Key Features of AI Models
• Types of AI Model
• AI Model Development Process
• How AI Models are Trained
• Challenges in Training AI Models
• Testing AI Models
• Improving AI Models
• Evaluating Model Performance

LO#03: Understand Machine Learning and Neural Networks

• What is Machine Learning?
• Machine Learning Algorithms
• How Machine Learning Improves Decision-Making
• Limitations of Machine Learning
• Neural Networks
• Layers, Nodes, and Weights in Neural Networks
• Deep Learning (DL)
• How DL Overcomes Limitations of ML
• Working of DL
• DL Algorithms
• Computer Vision

LO#04: Understand Natural Language Processing (NLP) and its Role in AI

• Natural Language Processing (NLP)
• Why NLP is Important in AI
• How NLP Processes Human Language
• Processing Text for NLP Tasks
• Key NLP Tasks
• Sentiment Analysis in NLP
• Text Summarization in NLP
• Language Translation in NLP
• Challenges in NLP

LO#05: Explain Generative AI (GenAI) and Large Language Models (LLMs)

• What is Generative AI?
• Traditional AI vs Generative AI
• Foundation Models of Generative AI
• Popular GenAI Tools
• Large Language Models (LLMs)
• Small vs. Large Language Models
• Key Terms for GenAI and Language Models

LO#06: Understand Advanced AI Systems and Technologies

• Robotics
• Multimodal AI
• AI Agents
• Agentic AI
• XAI (Explainable Artificial Intelligence)
• Expert Systems

LO#07: Select the Appropriate Tools Based on AI Project Requirements

• Select the Appropriate Tools for AI Projects
• Understand Project Type
• Consider Tool Characteristics
• Recommended AI Tools by Use Case
• Module Summary

 

Module 04 Prompt Crafting for Effective AI Interactions

LO#01: Understand the Basics of Prompt Engineering

• What is a Prompt?
• How AI Responds to Prompts
• What is Prompt Engineering?
• Why is Prompt Engineering Important?
• How does Prompt Engineering Work?
• How Different AI Models Interpret Prompts
• Comparison of AI Platform Responses

LO#02: Learn How to Craft Effective Prompts

• Key Principles of Crafting Effective Prompts
• Ask the Right Question
• Make Prompts Clear
• Make Prompts Specific
• Make Prompts Relevant
• Test and Refine Prompts
• Handle Unsatisfactory Responses
• Rephrasing Prompts

LO#03: Learn Prompt Engineering Techniques

• Prompting Techniques for Written Projects
• Prompting Techniques for Image or Video Project
• Prompting Techniques for Multimodal AI
• Chain of Thought (CoT) Prompting Techniques
• Iterative Prompting Techniques
• Managing Long Conversations
• Module Summary

 

Module 05 AI Ethics and Responsible AI

• AI Ethics and Responsible AI

LO#01: Identify Key Ethical, Societal, and Security Concerns in AI Systems

• AI Concerns
• AI Ethical Concern: Bias and Discrimination
• AI Ethical Concern: Lack of Transparency
• AI Ethical Concern: Accountability and Responsibility
• AI Ethical Concern: Intellectual Property and Copyright Violations
• Ethical Concerns Introduced by GenAI
• Privacy and Security Concern: Privacy and Surveillance
• Real-world Privacy and Data Protection Implications
• Privacy and Security Concern: Cyber Attacks
• Societal Concern: Job Displacement
• Societal Concern: Mental Health Impact
• Societal Concern: Hallucinations
• Societal Concern: Misinformation and Deepfakes
• Long-Term Concerns: Autonomous Weapons
• Long-Term Concerns: Emergence of AGI

LO#02: Explain the Principles and Importance of Using AI Ethically and Fairly

• What is Responsible AI?
• Why Responsible AI Use Matters?
• Using AI Responsibly in Daily Life

LO#03: Apply Responsible Practices, Governance, and Global Standards in AI Usage.

• Maintain Accountability in AI Usage
• Avoid Over-Reliance on AI
• Configure Privacy Settings in AI Tools
• Setting Up Privacy Controls in ChatGPT
• Exercise Caution Sharing Personal Data with AI Tools
• Managing AI App Permissions Effectively
• Stay Updated on AI Policy Changes and News
• Regularly Update and Audit AI Tools
• Use AI Applications Ethically
• Ethical AI Design: Key Considerations
• Considerations for Navigating GenAI Ethical Challenges
• Safeguard Against AI Security Risks
• Regulation and Governance in AI
• Responsible AI Global Initiatives
• Legal Foundation of Responsible AI
• AI Regulations in Action: GDPR, CCPA, and DPDP Act
• Building a Responsible AI Future
• Module Summary