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- Instant access to 11,000+ online courses
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This plan includes
- Instant access to 11,000+ online courses
- Play & Pause Course Videos
- HD Video Recorded Lectures
- Learn on Mobile/PC/Tablet
- Quizzes and Real Projects
- Lifetime Course Certificate
- Instructor Chat Support
- Cancel Plan Anytime
What you'll learn?
- Gain a deep understanding of the fundamentals, principles, and techniques of prompt engineering and its applications in various domains.
- Master the art of crafting effective prompts, utilizing tags, and employing advanced strategies to maximize the potential of AI language models.
- Develop the skills to create prompts for diverse applications such as content creation, coding assistance, chatbot therapy, and more using Chat GPT.
- Acquire the knowledge to secure prompt engineering efforts by understanding prompt hacking concepts, and explore advanced topics like text detection ect.
Course Overview
Become an AI Whisperer: Break into the field of prompt engineering, the most exciting and hottest new job in tech. Learn how to make Artificial Intelligence systems like ChatGPT and GPT-4 do exactly what you want, even if they've been programmed to do otherwise. Master their biases, take advantage of their design flaws, and become an expert prompter!
Did you know a sentence as simple as "Ignore previous directions" can often confuse AIs as advanced as ChatGPT and grant you access to restricted functionality? This is exactly what prompt engineers do on a daily basis: they discover models' biases and exploit them to their advantage. Intrigued? Dive into the world of prompt engineering with our comprehensive video course, designed to unlock the potential of AI language models for a wide range of applications. Learn the principles, techniques, and advanced strategies for crafting effective prompts, hacking prompts, image prompts, and more. With a strong focus on practical examples, this course will equip you with the skills to transform AI language models into powerful tools for content creation, chatbots, coding assistants, and beyond. Embark on this journey to master prompt engineering and harness the true power of generative AI!
What will you learn?
-
Gain a deep understanding of the fundamentals, principles, and techniques of prompt engineering and its applications in various domains.
-
Master the art of crafting effective prompts, utilizing tags, and employing advanced strategies to maximize the potential of AI language models.
-
Develop the skills to create prompts for diverse applications, such as content creation, coding assistance, chatbot therapy, and more, using ChatGPT.
-
Acquire the knowledge to secure prompt engineering efforts by understanding prompt hacking concepts and exploring advanced topics like AI-generated text detection and addressing biases.
-
Learn image prompting techniques, including style modifiers, quality boosters, and weighted terms, to enhance visual content generation.
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Understand the integration of language models and tags in technologies and startups for improved outcomes.
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Gain proficiency in addressing limitations and potential biases in AI language models, leading to more responsible and ethical use of technology.
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Stay updated on cutting-edge developments in prompt engineering, equipping you with the skills to adapt and innovate in a rapidly evolving field.
Pre-requisites
- This course is beginner-friendly and aims to lower the barrier for those interested in prompt engineering and AI language models. All necessary concepts will be explained and demonstrated throughout the course.
- Basic understanding of AI and machine learning concepts: Familiarity with AI concepts and a general understanding of machine learning will be beneficial for grasping prompt engineering concepts.
- Interest in natural language processing (NLP): A curiosity about language models, NLP, and text generation will help learners better engage with the course material.
- Access to a computer and internet connection: Learners will need a computer with a reliable internet connection to access the video course and work on practical examples.
- No prior programming experience required: This course is designed to be accessible for learners without a programming background, although those with experience may find it easier to apply the concepts.
Target Audience
- Content creators and digital marketers looking to leverage the power of AI language models for generating high-quality, engaging content across various platforms.
- Developers and engineers interested in integrating AI language models, such as Chat GPT, into their projects for tasks like coding assistance, chatbot development, and more.
- AI and machine learning enthusiasts seeking a comprehensive understanding of prompt engineering techniques and strategies to enhance their skillset in natural language processing.
- Startup founders and product managers aiming to harness AI language models to create innovative products or improve existing services in their businesses.
- Educators and researchers focused on responsible AI practices, who wish to explore prompt engineering for addressing biases, limitations, and ethical considerations in AI language models.
Curriculum 62 Lectures 02:40:46
-
Section 1 : Section 1: Introduction to Prompt Engineering
- Lecture 2 :
- What is Prompt Engineering
- Lecture 3 :
- Generative AI Tools
- Lecture 4 :
- Cons of Prompt Engineering
- Lecture 5 :
- Future Trends of Prompt Engineering
-
Section 2 : Principles of Prompt Engineering
- Lecture 1 :
- Introduction to Principles of Prompt Engineering
- Lecture 2 :
- Prompt Formula
- Lecture 3 :
- Less Effective Prompts
- Lecture 4 :
- Prompt Formulation
- Lecture 5 :
- Prompt Commands
- Lecture 6 :
- Basic Prompt Examples
-
Section 3 : Prompt Engineering Techniques
- Lecture 1 :
- Introduction and chapter overview
- Lecture 2 :
- About Language Models
- Lecture 3 :
- Important Vocabulary
- Lecture 4 :
- Tokens and Tokenization
- Lecture 5 :
- Tokenization Strategies
- Lecture 6 :
- Context and Conversation History
- Lecture 7 :
- Balancing Prompt Length
- Lecture 8 :
- Balancing Prompt Lenght Examples
- Lecture 9 :
- Zero Shot Prompting
- Lecture 10 :
- Few Shot Prompting
- Lecture 11 :
- Chain Of Though
- Lecture 12 :
- Least to Most Prompting
- Lecture 13 :
- Directional Stimulus Prompting
- Lecture 14 :
- PAL (Program-Aided Language Models)
- Lecture 15 :
- ReAct (Reversible Actuation)
- Lecture 16 :
- Self Consistency
- Lecture 17 :
- Generated Knowledge Prompting (GKP)
- Lecture 18 :
- Applications and Limitations of Language Models
-
Section 4 : Tags in Prompt Engineering
- Lecture 1 :
- Introduction Chapter overview
- Lecture 2 :
- Introduction to Tags in Prompt Engineering
- Lecture 3 :
- Types of Tags
- Lecture 4 :
- Combining Tags
- Lecture 5 :
- Bing Chat
- Lecture 6 :
- Integration of LLM and Chat GPT in Technologies & Startups
-
Section 5 : Chapter 5 - Crafting Prompts for Chat GPT
- Lecture 1 :
- Introduction Chapter overview
- Lecture 2 :
- Coding Assistant
- Lecture 3 :
- Content Creation
- Lecture 4 :
- Structuring Data
- Lecture 5 :
- ChatBot Therapist
- Lecture 6 :
- Act as a ChatGPT Prompt Generator
-
Section 6 : Prompt Hacking
- Lecture 1 :
- Understanding Prompt Injection
- Lecture 2 :
- Understanding Prompt Leaking
- Lecture 3 :
- Understanding Prompt Jailbreaking Part1
- Lecture 4 :
- Understanding Prompt Jailbreaking Part2
- Lecture 5 :
- Defensive Mechanisms for Prompt Engineering
- Lecture 6 :
- Introduction Chapter overview
-
Section 7 : Image Prompting
- Lecture 1 :
- Introduction and Chapter Overview
- Lecture 2 :
- Style Modifiers in Image Prompting
- Lecture 3 :
- Quality Boosters in Image Prompting
- Lecture 4 :
- Emphasizing Keywords through Repetition
- Lecture 5 :
- Weighted Terms in Image Prompting
- Lecture 6 :
- Improving images with Negative Prompts
- Lecture 7 :
- MindJourney Parameters
- Lecture 8 :
- Effective DALE Prompts
- Lecture 9 :
- Tools and Resources
-
Section 8 : Chapter 8 - Advanced Topics
- Lecture 1 :
- Introduction and Chapter Overview
- Lecture 2 :
- Detecting AI-Generated Text An Overview
- Lecture 3 :
- The Watermark Method
- Lecture 4 :
- Evading Detection Methods for AI-Generated Text
- Lecture 5 :
- Improving Prompt Engineering for LLMs
- Lecture 6 :
- Addressing Biases in Prompt Engineerin
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