AI+ Prompt Engineer Level 1™
Master AI Prompts: Elevate Your Engineering Skills
Certificate Code:
AC-130
About This Course
- Foundational Knowledge: Covers generative AI, ML, NLP, and neural networks essentials
- Hands-on Learning: Offers practical training in designing and optimizing prompts
- Industry-Relevant Skills: Prepares learners to build effective AI solutions across sectors
- Prompting Expertise: Certifies participants to craft impactful, domain-specific prompts
Certificate Overview
Included
Instructor-led OR Self-paced course + Official exam + Digital badge
Duration
- Instructor-Led: 1 day (live or virtual)
- Self-Paced: 8 hours of content
Prerequisites
Understand AI basics, Willingness to think creatively to generate ideas and use AI tools effectively.
Exam Format
50 questions, 70% passing, 90 minutes, online proctored exam
Course Modules
1
Course Overview
- Course Introduction Preview
2
Module 1: Foundations of Artificial Intelligence (AI) and Prompt Engineering
3
Module 2: Principles of Effective Prompting
4
Module 3: Introduction to AI Tools and Models
- 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
5
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
6
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 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
7
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
8
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 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
9
Optional Module: AI Agents for Prompt Engineering
- 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
AI Tools You'll Learn
LangChain
