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AI+ Prompt Engineer Level 1™ Spanish
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Introduction
Course Introduction
Module 1: Foundations of AI and Prompt Engineering
1.1 Brief History and Evolution of AI
1.2 AI’s Impact on Various Industries
1.3 Key Milestones and Evolution of AI Techniques
1.4 Machine Learning: Supervised & Unsupervised
1.5 Basics of Deep Learning and Introduction to Neural Networks
1.6 Overview of NLP and AI NLP Applications
1.7 Definition and Priniciples of Prompt Engineering
Module 2: Principles of Effective Prompting
2.1 Prompting Importance: Enhancing with Well-Crafted Prompts
2.2 Clear and Concise Prompts: The Role of Specificity
2.3 Impact of AI Response Formats on Utility
2.4 Context Setting: Clarifying Tasks and Outcomes
2.5 Assessing AI Responses: Common Output Issues
2.6 Breaking Down Tasks: Sequential Structuring in AI Prompting
2.7 Principles Overview: Applications & Tools
2.8 Identifying Prompt Failures and Hands on Activity
Module 3: Introduction to AI Tools and Models
3.1 Comparing Generative AI and Traditional Models
3.2 ChatGPT: Architecture, Capabilities, and Applications
3.3 Advancements and Practical Applications of GPT-4
3.4 DALL-E 2: Introduction and Creative Applications
3.5 Claude-Instant-100k vs. DALL-E 3: A Comparison
3.6 StableDiffusionXL and Llama-2-70b-Groq: Overview and Applications
3.7 Claude-2-100k, Mistral-Medium, and Gemini-Pro: Features and Strategy
3.8 Google-PaLM and Integrating Google Models
3.9 AI Models: Strengths, Weaknesses, and Selection Criteria
3.10 Designing Use Cases and Tailoring Selection to Needs
3.11 Synthesis of Key Insights
Module 4: Mastering Prompt Engineering Techniques
4.1 Zero-Shot Learning and Designing Effective Prompts
4.2 Enhancing AI Understanding with Few-Shot Prompts
4.3 Thinking Aloud and Chain-of-Thought Prompts
4.4 Promoting Internal Consistency and Self-Checking
4.5 Fostering Creativity through Innovative Prompt Crafting
4.6 Sequential Prompting and Applications of Prompt Chains
4.7 Creative AI: Unlocking Multipath Solutions and Diverse Response
4.8 Augmenting AI with External Data for Better Quality
4.9 Graphical Data in AI Prompting and Insight Generation
4.10 Practical Exercises and Cross-Industry Use Cases
4.11 Optional Exercises and Challenging Projects
Module 5: Mastering Image Model Techniques
5.1 Overview and Distinction of Generative Image Models
5.2 Principles of Visual Content Generation
5.3 Enhancing Image Quality with Practical Insights
5.4 Mastering Prompt Dynamics in Image Generation
5.5 Power of Weighted Terms in AI Image Generation
5.6 Mastering Prompt Adjustments for AI Creativity
5.7 Prompt Rewriting in AI Image Generation: Case Studies
5.8 Mastering Inpainting and Outpainting Technique
5.9 Realistic Image Creation: Techniques for Lifelike Characters
5.10 Ensuring Consistency Across Characters
5.11 Realistic Methods for Consistent Character Models
5.12 Real-World Applications and Opportunities of Image Models
Module 6: Project-Based Learning Session
6.1 Project-Based Learning: Transforming AI Education
6.2 Choosing Relevant Themes
6.3 Theme Examples in AI Applications
6.4 Project Structuring: Scope, Timeline, and Resources
6.5 Refinement of AI Strategies and Practical Applications
6.6 Unified Models: Integration Case Studies
6.7 Iterative Assessment for Project Outcome
6.8 Enhancing Presentations Through Feedback Insights
6.9 Walkthrough of a Guided Project
6.10 Encouragement for Independent Projects
Module 7: Ethical Considerations and the Future of AI
7.1 Ethics in AI and Prompt Engineering
7.2 Understanding AI Bias
7.3 AI and Privacy: Ensuring Data Security
7.4 Need for Transparency and Enhancing Accountability
7.5 AI and the Environment: Driving Sustainability
7.6 Emerging AI Trends: The Evolving Role of Prompt Engineering
7.7 Applying Ethical Principles: Exploring Implications
7.8 AI Regulations and Implications for Practitioners
7.9 Ethical Frameworks and Practices
Course Summary
Course Summary
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AI+ Prompt Engineer Level 1™ Spanish
