AI+ Prompt Engineer Level 1AIPEAHAI CertsAH-AIPE1.0<ul>
<li>Understand AI basics and how AI is used – no technical skills required</li><li>Willingness to think creatively to generate ideas and use AI tools effectively</li></ul><ul>
<li>Business Professionals</li><li>AI Enthusiasts and Beginners</li><li>Content Creators</li><li>Digital Marketers</li><li>Developers</li><li>Aspiring AI Engineers</li></ul><h4>Module 1: Foundations of Artificial Intelligence (AI) and Prompt Engineering</h4><ul>
<li>1.1 Introduction to Artificial Intelligence</li><li>1.2 History of AI</li><li>1.3 Basics of Machine Learning</li><li>1.4 Deep Learning and Neural Networks</li><li>1.5 Natural Language Processing (NLP)</li><li>1.6 Prompt Engineering Fundamentals</li></ul><h4>Module 2: Principles of Effective Prompting</h4><ul>
<li>2.1 Introduction to the Principles of Effective Prompting</li><li>2.2 Giving Direction</li><li>2.3 Formatting Responses</li><li>2.4 Providing Examples</li><li>2.5 Evaluating Quality</li><li>2.6 Dividing Labor</li><li>2.7 Applying The Five Principles</li><li>2.8 Fixing Failing Prompts</li></ul><h4>Module 3: Introduction to AI Tools and Models</h4><ul>
<li>3.1 Understanding AI Tools and Models</li><li>3.2 Deep Dive into ChatGPT</li><li>3.3 Exploring GPT-4</li><li>3.4 Revolutionizing Art with DALL-E 2</li><li>3.5 Introduction to Emerging Tools using GPT</li><li>3.6 Specialized AI Models</li><li>3.7 Advanced AI Models</li><li>3.8 Google AI Innovations</li><li>3.9 Comparative Analysis of AI Tools</li><li>3.10 Practical Application Scenarios</li><li>3.11 Harnessing AI’s Potential</li></ul><h4>Module 4: Mastering Prompt Engineering Techniques</h4><ul>
<li>4.1 Zero-Shot Prompting</li><li>4.2 Few-Shot Prompting</li><li>4.3 Chain-of-Thought Prompting</li><li>4.4 Ensuring Self-Consistency in AI Responses</li><li>4.5 Generate Knowledge Prompting</li><li>4.6 Prompt Chaining</li><li>4.7 Tree of Thoughts: Exploring Multiple Solutions</li><li>4.8 Retrieval Augmented Generation</li><li>4.9 Graph Prompting and Advanced Data Interpretation</li><li>4.10 Application in Practice: Real-Life Scenarios</li><li>4.11 Practical Exercises</li></ul><h4>Module 5: Mastering Image Model Techniques</h4><ul>
<li>5.1 Introduction to Image Models</li><li>5.2 Understanding Image Generation</li><li>5.3 Style Modifiers and Quality Boosters in Image Generation</li><li>5.4 Advanced Prompt Engineering in AI Image Generation</li><li>5.5 Prompt Rewriting for AI Image Models</li><li>5.6 Image Modification Techniques: Inpainting and Outpainting</li><li>5.7 Realistic Image Generation</li><li>5.8 Realistic Models and Consistent Characters</li><li>5.9 Practical Application of Image Model Techniques</li></ul><h4>Module 6: Project-Based Learning Session</h4><ul>
<li>6.1 Introduction to Project-Based Learning in AI</li><li>6.2 Selecting a Project Theme</li><li>6.3 Project Planning and Design in AI</li><li>6.4 AI Implementation and Prompt Engineering</li><li>6.5 Integrating Text and Image Models</li><li>6.6 Evaluation and Integration in AI Projects</li><li>6.7 Engaging and Effective Project Presentation</li><li>6.8 Guided Project Example</li></ul><h4>Module 7: Ethical Considerations and Future of AI</h4><ul>
<li>7.1 Introduction to AI Ethics</li><li>7.2 Bias and Fairness in AI Models</li><li>7.3 Privacy and Data Security</li><li>7.4 The Imperative for Transparency in AI Operations</li><li>7.5 Sustainable AI Development: An Imperative for the Future</li><li>7.6 Ethical Scenario Analysis in AI: Navigating the Complex Landscape</li><li>7.7 Navigating the Complex Landscape of AI Regulations and Governance</li><li>7.8 Navigating the Regulatory Landscape: A Guide for AI Practitioners</li><li>7.9 Ethical Frameworks and Guidelines in AI Development</li></ul>- Understand AI basics and how AI is used – no technical skills required
- Willingness to think creatively to generate ideas and use AI tools effectively- Business Professionals
- AI Enthusiasts and Beginners
- Content Creators
- Digital Marketers
- Developers
- Aspiring AI EngineersModule 1: Foundations of Artificial Intelligence (AI) and Prompt Engineering
- 1.1 Introduction to Artificial Intelligence
- 1.2 History of AI
- 1.3 Basics of Machine Learning
- 1.4 Deep Learning and Neural Networks
- 1.5 Natural Language Processing (NLP)
- 1.6 Prompt Engineering Fundamentals
Module 2: Principles of Effective Prompting
- 2.1 Introduction to the Principles of Effective Prompting
- 2.2 Giving Direction
- 2.3 Formatting Responses
- 2.4 Providing Examples
- 2.5 Evaluating Quality
- 2.6 Dividing Labor
- 2.7 Applying The Five Principles
- 2.8 Fixing Failing Prompts
Module 3: Introduction to AI Tools and Models
- 3.1 Understanding AI Tools and Models
- 3.2 Deep Dive into ChatGPT
- 3.3 Exploring GPT-4
- 3.4 Revolutionizing Art with DALL-E 2
- 3.5 Introduction to Emerging Tools using GPT
- 3.6 Specialized AI Models
- 3.7 Advanced AI Models
- 3.8 Google AI Innovations
- 3.9 Comparative Analysis of AI Tools
- 3.10 Practical Application Scenarios
- 3.11 Harnessing AI’s Potential
Module 4: Mastering Prompt Engineering Techniques
- 4.1 Zero-Shot Prompting
- 4.2 Few-Shot Prompting
- 4.3 Chain-of-Thought Prompting
- 4.4 Ensuring Self-Consistency in AI Responses
- 4.5 Generate Knowledge Prompting
- 4.6 Prompt Chaining
- 4.7 Tree of Thoughts: Exploring Multiple Solutions
- 4.8 Retrieval Augmented Generation
- 4.9 Graph Prompting and Advanced Data Interpretation
- 4.10 Application in Practice: Real-Life Scenarios
- 4.11 Practical Exercises
Module 5: Mastering Image Model Techniques
- 5.1 Introduction to Image Models
- 5.2 Understanding Image Generation
- 5.3 Style Modifiers and Quality Boosters in Image Generation
- 5.4 Advanced Prompt Engineering in AI Image Generation
- 5.5 Prompt Rewriting for AI Image Models
- 5.6 Image Modification Techniques: Inpainting and Outpainting
- 5.7 Realistic Image Generation
- 5.8 Realistic Models and Consistent Characters
- 5.9 Practical Application of Image Model Techniques
Module 6: Project-Based Learning Session
- 6.1 Introduction to Project-Based Learning in AI
- 6.2 Selecting a Project Theme
- 6.3 Project Planning and Design in AI
- 6.4 AI Implementation and Prompt Engineering
- 6.5 Integrating Text and Image Models
- 6.6 Evaluation and Integration in AI Projects
- 6.7 Engaging and Effective Project Presentation
- 6.8 Guided Project Example
Module 7: Ethical Considerations and Future of AI
- 7.1 Introduction to AI Ethics
- 7.2 Bias and Fairness in AI Models
- 7.3 Privacy and Data Security
- 7.4 The Imperative for Transparency in AI Operations
- 7.5 Sustainable AI Development: An Imperative for the Future
- 7.6 Ethical Scenario Analysis in AI: Navigating the Complex Landscape
- 7.7 Navigating the Complex Landscape of AI Regulations and Governance
- 7.8 Navigating the Regulatory Landscape: A Guide for AI Practitioners
- 7.9 Ethical Frameworks and Guidelines in AI Development1 day995.00995.00995.00995.001375.00995.00995.00