Prompt Engineering for Improved Performance

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Kesha Williams

1:53:35

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1. Course Overview

1. Course Overview.mp4

01:47

2. Prompting at a Glance

1. Introduction.mp4

01:52

2. Prompting Basics.mp4

03:21

3. Demo - ChatGPT in Action.mp4

05:05

4. Prompt Development.mp4

03:43

5. Demo - Zero-shot Learning.mp4

04:01

6. Demo - Few-shot Learning.mp4

03:47

7. Demo - Instruction Prompting.mp4

07:07

8. Prompting Failures.mp4

03:22

9. Conclusion.mp4

01:02

3. Master Advanced Prompting Techniques

1. Introduction.mp4

00:32

2. Chain-of-thought Prompting.mp4

01:42

3. Demo - Chain-of-thought Prompting.mp4

06:53

4. Knowledge Augmentation.mp4

02:55

5. Demo - Knowledge Augmentation.mp4

09:40

6. Prompt Tuning.mp4

03:49

7. Demo - Prompt Tuning.mp4

06:26

8. Conclusion.mp4

00:38

4. Optimize Prompts for Specific Use Cases

1. Introduction.mp4

00:32

2. Demo - Summarizing Text.mp4

05:58

3. Demo - Expanding Text.mp4

04:24

4. Text-to-image Generation.mp4

03:38

5. Demo - Text-to-image Generation.mp4

05:21

6. Demo - Inferring Sentiment.mp4

07:24

7. Text Transformation.mp4

01:51

8. Demo - Text Transformation.mp4

07:48

9. Conclusion.mp4

00:50

5. Design Prompts That Improve Performance

1. Introduction.mp4

00:29

2. Factors That Impact Latency.mp4

02:24

3. Improve Prompt Design.mp4

03:18

4. Conclusion.mp4

01:56

Description

Learn advanced prompt engineering techniques to enhance language model performance. Explore optimization techniques and gain insights into factors affecting latency and performance. Guide models to generate accurate, coherent, and relevant outputs.

What You'll Learn?

Advanced prompt engineering techniques can significantly enhance the performance of language models by guiding them to generate more accurate, coherent, and relevant outputs. In this course, Prompt Engineering for Improved Performance, you’ll gain the ability to harness the capabilities of language models effectively, ensuring they align with specific use cases, minimize biases, and deliver high-quality outputs.

First, you’ll journey beyond the realm of basic prompting techniques and learn how to leverage advanced prompting methods that elevate a model's performance on reasoning tasks.

Next, you’ll discover the art of prompt optimization for specific use cases by diving into optimization techniques for summarizing and expanding text, text-to-image generation, inferring sentiment, and transforming text from one format to another.

Finally, you’ll gain insights into the key factors that impact the latency and performance of text generation models and explore mitigation techniques to improve performance.

When you finish this course, you’ll have the knowledge of advanced prompt engineering techniques needed to harness the capabilities of language models effectively, ensuring they align with specific use cases, minimize biases, and deliver high-quality outputs.

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Programming Fundamentals

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Kesha Williams

Instructor's Courses

Kesha Williams is an award-winning technology leader with 25+ years of experience in tech. She's passionate about hands-on building and developing the next generation of leaders. She's versed in Java, AI/ML, and AWS and shares her knowledge with thousands of engineers around the globe through authoring courses, speaking at conferences, and writing technical blog posts.

Pluralsight

View courses Pluralsight

Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.