Mastering Gen Ai – Prompt Engineering: A Hands-On Guide
Published 9/2024
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Hands-on Training in Generative AI – Prompt Engineering
What you’ll learn
Grasp Generative AI Fundamentals: Learn core concepts, applications, and models.
Master Prompt Engineering: Design, optimize, and troubleshoot effective prompts.
Apply Advanced Techniques: Explore advanced concepts and real-world applications of Generative AI.
Requirements
Basic Computer Skills: Familiarity with using a computer and navigating software applications.
No Prior Experience Needed: The course is designed for beginners, so no prior experience in Generative AI or prompt engineering is necessary.
Access to a Computer: A computer with an internet connection for accessing course materials and completing hands-on exercises.
Description
Overview
Section 1: Introduction to Generative AI
Lecture 1 Overview of Generative AI
Lecture 2 Key Applications of Generative AI
Lecture 3 A Brief History of Generative AI
Lecture 4 Types of Generative AI Models
Section 2: Fundamentals of Prompt Engineering
Lecture 5 Understanding Prompts in AI
Lecture 6 Demo – Understanding prompts in AI
Lecture 7 Demo – The Role and Importance of Prompt Engineering
Lecture 8 Best Practices for Effective Prompt Design
Lecture 9 Demo – Best practices in prompt design
Lecture 10 Challenges and Pitfalls in Prompt Engineering
Lecture 11 Demo – Common challenges in prompt engineering
Section 3: Hands-on: Building a Prompt Engineering Framework
Lecture 12 Setting up the Development Environment
Lecture 13 Writing a Basic Prompt Generation Script
Lecture 14 Demo – Creating a basic prompt generation script
Lecture 15 Customizing Prompts for Specific Use Cases
Lecture 16 Demo – Customizing prompts for specific tasks
Lecture 17 Demo – Testing and Fine-tuning Your Prompt Models
Section 4: Creating Effective Prompts
Lecture 18 Exploring Different Types of Prompts
Lecture 19 Demo – Understanding different types of prompts
Lecture 20 Formulating Precise Prompts for Desired Outputs
Lecture 21 Demo – Formulating Precise Prompts for Desired Outputs
Lecture 22 Demo – Iterating, Testing, and Refining Prompts
Lecture 23 Aligning Prompts with Specific Project Goals
Lecture 24 Demo – Using prompt engineering to achieve specific goals
Section 5: Optimizing Prompt Generation
Lecture 25 Tools and Techniques to Optimize Prompt Generation
Lecture 26 Demo – Tools and techniques for optimizing prompt generation
Lecture 27 Enhancing Efficiency and Accuracy of Prompts
Lecture 28 Demo – Strategies for improving prompt efficiency and accuracy
Lecture 29 Ethical Implications in Prompt Engineering
Lecture 30 Demo – Considering ethical implications in prompt engineering
Lecture 31 Real-world Applications of Optimized Prompts
Lecture 32 Demo – Real-world applications of optimized prompt generation
Section 6: Advanced Concepts in Generative AI
Lecture 33 Exploring Transfer Learning in Generative AI
Lecture 34 Demo – Transfer learning in Generative AI
Lecture 35 Zero-shot and Few-shot Learning Techniques
Lecture 36 Demo – Zero-shot and few-shot learning techniques
Lecture 37 Ethical Design in Advanced Prompt Engineering
Lecture 38 Demo – Ethical considerations in prompt design
Lecture 39 Recent Breakthroughs in Generative AI Research
Lecture 40 Demo – Recent advances in Generative AI research
Section 7: Applications of Prompt Engineering
Lecture 41 Leveraging Prompt Engineering for Content Generation
Lecture 42 Demo – Natural language generation for content creation
Lecture 43 Automating Code Generation Using Prompts
Lecture 44 Demo – Automated code generation using prompts
Lecture 45 Using Prompts for Personalized Recommendations
Lecture 46 Demo – Personalized recommendation systems with prompt engineering
Lecture 47 Enhancing Virtual Assistants with Prompt-driven Responses
Lecture 48 Demo – Enhancing chatbots and virtual assistants with prompt design
Section 8: Case Studies and Real-world Examples
Lecture 49 Case Study: GPT-3 and the Role of Prompt Engineering
Lecture 50 Demo – Case study- GPT-3 and prompt engineering
Lecture 51 Real-world Implementations of Prompt-based Systems
Lecture 52 Demo – Real-world examples of successful prompt-based systems
Lecture 53 Lessons from Failed Prompt Engineering Projects
Lecture 54 Demo – Lessons learned from failed prompt engineering projects
Lecture 55 Future Trends in Generative AI and Prompt Engineering
Lecture 56 Demo – Future prospects and trends in Generative AI and prompt engineering
Beginners in AI: Individuals with little to no experience in Generative AI who want to explore this growing field.,Aspiring Prompt Engineers: Those interested in learning how to design and optimize effective prompts for AI models.,Developers and Data Scientists: Professionals seeking to enhance their skills in AI by applying hands-on prompt engineering techniques.,Content Creators and Innovators: Creatives looking to leverage Generative AI for content generation, automation, or product innovation.
