Course outline for
AI and Problem Solving
AI and Problem Solving Course Outline
Session One: Course Overview
Course Overview
Learning Objectives
Pre-Assignment
Pre-Course Assessment
Session Two: Introduction to AI and Problem-Solving
Overview
Key Concepts of Artificial Intelligence
Types Of AI Technologies Relevant to Problem-Solving
Identifying Problems Suitable for AI Solutions
Session Three: AI Tools and Technologies
Popular AI Platforms and Tools
AI Implementation Case Studies
Getting Started With a Simple AI Tool or Platform
Session Four: Data-Driven Problem-Solving
Techniques For Data Collection, Cleaning, And Preparation
Visualization And Interpretation of Data Outputs
AI Data Strategy Case Study Analysis
Session Five: Machine Learning Models in Problem-Solving
Overview
Machine Learning Method Discussion and Application Scenarios
Session Six: Implementing AI Solutions
Integration Of AI Into Existing Workflows and Systems
Project Management Strategies for AI in Projects
AI Integration Strategy Case Study
Session Seven: Ethical Considerations in AI Problem-Solving
Bias, Fairness and Privacy in AI Solutions
Case Study: Moneyball Strategies
Balancing Data and Human Decision-Making in An Organization
Necessary Human Intervention
Session Eight: Future of AI in Problem-Solving
Emerging AI Technologies and Their Potential Applications And Effects
Preparing for an AI-Driven Future
Session Nine: Preparing for an AI-Driven Future
Preparing for an AI-Driven Future
How Can I Ethically Engage With AI?
Personal Action Plan
Course Summary
Recommended Reading List
Post-Course Assessment
Pre- and Post-Course Assessment Answer Key
Pre-Course Assessment
Post-Course Assessment
Assignment Answer Key
Session Two: Introduction to AI and Problem-Solving
Session Three: AI Tools and Technologies
Session Four: Data-Driven Problem-Solving
Session Five: Machine Learning Models in Problem Solving
Session Six: Implementing AI Solutions
Session Seven: Ethical Considerations in AI Problem-Solving
Session Eight: Future of AI in Problem-Solving
Session Nine: Preparing for an AI-Driven Future
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