kingers Posted Friday at 08:13 PM Report Share Posted Friday at 08:13 PM Understanding Prompt Engineering Last updated 3/2024 Duration: 43m | .MP4 1920x1080, 30 fps(r) | AAC, 44100 Hz, 2ch | 1.85 GB Genre: eLearning | Language: EnglishTowards Excellence What you'll learn - This course delves into the principles, strategies, and best practices of prompt engineering, a crucial aspect in shaping AI models' behavior and performance. - Digital Challenges and Problem-Solving: - Enhance self-awareness and provide insights into patterns and triggers. - Help individuals stay present, observe their emotions without judgment, and reduce reactivity. Requirements - No programming experience needed Description This course delves into prompt engineering principles, strategies, and best practices, a crucial aspect in shaping AI models' behaviour and performance. Understanding Prompt Engineering is a comprehensive course designed to equip learners with the knowledge and skills to effectively generate and utilize prompts in natural language processing (NLP) and machine learning (ML) applications. This course delves into prompt engineering principles, strategies, and best practices, a crucial aspect in shaping AI models' behaviour and performance. Module 1: Introduction to Prompt Engineering Lesson 1: Foundations of Prompt Engineering Overview of prompt engineering and its significance in NLP and ML. Historical context and evolution of prompt-based approaches. Module 2: Types of Prompts and Their Applications Lesson 2: Closed-Ended Prompts Understanding and creating prompts for specific answers. Applications in question-answering systems. Lesson 3: Open-Ended Prompts Crafting prompts for creative responses. Applications in language generation models. Module 3: Strategies for Effective Prompting Lesson 4: Probing Prompts Designing prompts to reveal model biases. Ethical considerations in using probing prompts. Lesson 5: Adversarial Prompts Creating prompts to stress-test models. Enhancing robustness through adversarial prompting. Module 4: Fine-Tuning and Optimizing with Prompts Lesson 6: Fine-Tuning Models with Prompts Techniques for incorporating prompts during model training. Balancing prompt influence and generalization. Lesson 7: Optimizing Prompt Selection Methods for selecting optimal prompts for specific tasks. Customizing prompts based on model behavior. Module 5: Evaluation and Bias Mitigation Lesson 8: Evaluating Prompt Performance Metrics and methodologies for assessing model performance with prompts. Interpreting and analyzing results. Lesson 9: Bias Mitigation in Prompt Engineering Strategies to identify and address biases introduced by prompts. Ensuring fairness and inclusivity in prompt-based models. Module 6: Real-World Applications and Case Studies Lesson 10: Case Studies in Prompt Engineering Exploration of successful implementations and challenges in real-world scenarios. Guest lectures from industry experts sharing their experiences. Who this course is for: - Intended Learners for basics More Info Please check out others courses in your favourite language and bookmark them - - - -DDownloadhttps://ddownload.com/6dj3ne2ludoq/yxusj.Understanding.Prompt.Engineering.part1.rarhttps://ddownload.com/br0rlbc0q1nf/yxusj.Understanding.Prompt.Engineering.part2.rarRapidGatorhttps://rapidgator.net/file/939a017c6754d37de8f494ae5343c3af/yxusj.Understanding.Prompt.Engineering.part1.rarhttps://rapidgator.net/file/0fdc004fbce8eeddda38b58a8e6ff2d6/yxusj.Understanding.Prompt.Engineering.part2.rarNitroFlarehttps://nitroflare.com/view/6BC2B8C96BD2FCD/yxusj.Understanding.Prompt.Engineering.part1.rarhttps://nitroflare.com/view/7E864728DB9C21B/yxusj.Understanding.Prompt.Engineering.part2.rar Link to comment Share on other sites More sharing options...
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