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|---|---|
| Program Name | AI+ Prompting Fundamentals™ |
| Duration | Instructor-Led:1 day (live or virtual) | Self-Paced:8 hours (1 Day) |
| Prerequisites | Understand AI basics and how AI is used – no technical skills required. Willingness to think creatively to generate ideas and use AI tools effectively. |
| Exam Format | 50 questions, 70% passing, 90 minutes, online proctored exam |
Introduction to AI, its history, machine learning basics, deep learning, neural networks, and NLP.
Learn the essential principles of effective prompting, including giving directions, formatting responses.
Explore AI tools like ChatGPT, GPT-4, DALL-E 2, and specialized models, as well as understanding their practical applications.
Focus on advanced prompting techniques such as zero-shot, few-shot, chain-of-thought, prompt chaining.
Study the use of image models, style modifiers, image generation techniques, and practical applications.
Engage in hands-on projects to apply AI concepts, select themes, design AI projects, integrate text and image models.
Understand AI ethics, bias and fairness in models, privacy concerns, data security, transparency in AI.
Course Introduction Preview
1.1 Introduction to Artificial Intelligence Preview
1.2 History of AI Preview
1.3 Machine Learning Basics Preview
1.4 Deep Learning and Neural Networks
1.5 Natural Language Processing (NLP)
1.6 Prompt Engineering Fundamentals
2.1 Introduction to the Principles of Effective PromptingPreview
2.2 Giving DirectionsPreview
2.3 Formatting ResponsesPreview
2.4 Providing Examples
2.5 Evaluating Response Quality
2.6 Dividing Labor
2.7 Applying The Five Principles
2.8 Fixing Failing Prompts
3.1 Understanding AI Tools and Models Preview
3.2 Deep Dive into ChatGPT Preview
3.3 Exploring GPT-4 Preview
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
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
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 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
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
7.1 Introduction to AI Ethics
7.2 Bias and Fairness in AI Models
7.3 Privacy and Data Security in AI
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 Development
1. What Are AI Agents
2. Applications and Trends of AI Agents for Prompt Engineers
3. How Does an AI Agent Work
4. Core Characteristics of AI Agents
5. Importance of AI Agents
6. Types of AI Agents
Specializes in designing and optimizing AI prompts to improve model performance.
Focuses on designing the user experience (UX) by creating intuitive interactions between users and AI systems.
UX Engineers specialize in creating AI systems that prioritize user experience.
Communication Developers focus on building AI-driven systems that support communication tasks, such as chatbots or virtual assistants.
The course combines theoretical instruction with practical exercises and project-based learning sessions. This structure helps participants gain both conceptual knowledge and hands-on experience.
This certification is suitable for individuals from diverse backgrounds and levels of expertise who want to gain a comprehensive understanding of AI and prompt engineering. It is ideal for AI developers, data scientists, educators, and anyone interested in harnessing the full potential of AI models through effective prompting.
The certification covers principles of effective prompting, such as giving clear directions, formatting responses, providing examples, evaluating response quality, and fixing failing prompts. Participants will learn to apply these principles through practical exercises and real-life scenarios.
Completing the certification will equip you with essential skills in industries like AI content generation, customer support automation, and enterprise AI optimization.
You will apply AI and prompt engineering skills to various projects, improving your problem-solving, communication, and collaboration abilities.
70%
50 multiple-choice/multiple-response questions
