Problem Solving via Prompt Engineering

• The Role of Prompts in Interacting with ChatGPT
• Anatomy of a Well-Constructed Prompt
• Exploring Different Prompt Styles
• Prompt Examples and Analysis
• The Evolving Landscape of AI-Generated Content
• Addressing Bias and Fairness in Prompts and Responses
• Ethical Considerations for Prompt Engineering
• Data Basics
• Types of Data
• Big Data
• Databases and Other Tools
• Data Process
• Ethics and Governance
• More Data Terms and Concepts

4 LiveLab in this lesson — see the labs panel →

• Leveraging Context for More Relevant Responses
• Harnessing Prior Chat Turns for Smooth Conversations
• Incorporating The User’s Name and Details for Personalization
• Techniques for Asking Clear and Direct Questions
• Navigating Ambiguity: How to Get Precise Answers
• Uncovering Hidden Information With Well-Formed Queries
• Setting Constraints for Desired Output
• Ensuring Ethical and Responsible Responses
• Combining Constraints for Tailored Content
• The Challenges of NLP
• Understanding How AI Translates Language
• Voice Recognition
• NLP in the Real World
• Voice Commerce
• Virtual Assistants
• Chatbots
• Future of NLP

5 LiveLab in this lesson — see the labs panel →

• Using Temperature, Top-P, and Max Tokens for Control
• Incorporating Conditional Logic in Prompts
• Dynamic Prompts for Interactive Experiences
• New Features Announced with GPTs
• How to Build GPTS
• Example 1-A GPT App for Coloring Pages
• Example 2-A GPT App for Story Writers
• Winding Down The ChatGPT Plugins
• The Future of GPTS and GPT Builder
• What Is RPA?
• Pros and Cons of RPA
• What Can You Expect from RPA?
• How to Implement RPA
• RPA and AI
• RPA in the Real World
• Approaches to Implementing AI
• The Steps for AI Implementation
• Identify a Problem to Solve
• Forming the Team
• The Right Tools and Platforms
• Deploy and Monitor the AI System

6 LiveLab in this lesson — see the labs panel →

• Interpreting and Analyzing Model Responses
• Identifying Misunderstandings and Errors
• Strategies for Iterating and Improving Prompts
• An Introduction to Plugins
• Integrating Plugins for Enhanced AI Conversations
• Benefits of Using Plugins
• Popular Chatgpt/GPT-4 Plugins
• What Is Machine Learning?
• Standard Deviation
• The Normal Distribution
• Bayes’ Theorem
• Correlation
• Feature Extraction
• What Can You Do with Machine Learning?
• The Machine Learning Process
• Applying Algorithms
• Common Types of Machine Learning Algorithms
• Naïve Bayes Classifier (Supervised Learning/Classification)
• K-Nearest Neighbor (Supervised Learning/Classification)
• Linear Regression (Supervised Learning/Regression)
• Decision Tree (Supervised Learning/Regression)
• Ensemble Modelling (Supervised Learning/Regression)
• K-Means Clustering (Unsupervised/Clustering)

4 LiveLab in this lesson — see the labs panel →

• Inspiring Creative Writing with Open-Ended Prompts
• Generating Poetry, Stories, and Dialogues
• Using Prompts to Generate Ideas and Concepts
• Exploring Creativity Through Multimodal Prompts
• Applying Prompt Engineering in Customer Support
• Generating Content for Social Media and Marketing
• Educational Use Cases: Teaching and Learning with ChatGPT
• Business Applications
• Technical and Engineering Applications
• Autonomous Cars
• US vs. China
• Technological Unemployment
• The Weaponization of AI
• Drug Discovery
• Government
• AGI (Artificial General Intelligence)
• Social Good

5 LiveLab in this lesson — see the labs panel →