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Kesha Williams

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.

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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.

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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What's inside

Syllabus

Course Overview
Prompting at a Glance
Master Advanced Prompting Techniques
Optimize Prompts for Specific Use Cases
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Design Prompts That Improve Performance

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops advanced prompt engineering skills, which are increasingly employed across business and industry
Taught by Kesha Williams, an experienced instructor in prompt engineering
Provides techniques to optimize prompts for specific tasks, enhancing the performance of AI models
Helps learners understand factors affecting latency and performance, enabling informed decisions for more efficient model deployment
Requires a good understanding of basic prompting techniques and natural language processing concepts, making it suitable for intermediate learners
Focuses on advanced prompt engineering techniques and may not cover foundational concepts in great detail

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Prompt Engineering for Improved Performance with these activities:
Brush up on background knowledge
Reinforce your understanding of core concepts in prompt engineering to prepare for more advanced techniques covered in the course.
Browse courses on Prompt Engineering
Show steps
  • Review the course syllabus and identify key concepts.
  • Read introductory articles or blog posts on prompt engineering.
  • Complete practice exercises or tutorials on basic prompt engineering techniques.
Seek guidance from experienced prompt engineers
Accelerate your learning by connecting with experienced prompt engineers who can provide valuable insights and support.
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Show steps
  • Identify potential mentors through online platforms or industry events.
  • Reach out and introduce yourself, expressing your interest in their expertise.
  • Schedule regular meetings or calls to receive guidance and feedback.
Explore State-of-the-Art Prompt Engineering Techniques
Stay up-to-date with cutting-edge research and advancements in prompt engineering to improve your model performance.
Browse courses on Prompt Engineering
Show steps
  • Identify reputable sources for prompt engineering research (e.g., conference papers, journals).
  • Review and analyze recent advancements in prompt engineering techniques.
  • Experiment with implementing these techniques in your own projects.
Eight other activities
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Explore advanced prompt engineering methods
Delve deeper into advanced prompt engineering techniques and their applications in various scenarios.
Show steps
  • Identify specific use cases or tasks you want to improve.
  • Research and compare different advanced prompt engineering methods.
  • Follow online tutorials or workshops to learn how to implement these methods.
  • Experiment with different prompts and techniques to optimize performance.
Prompt Model Development in Practice
Develop practical proficiency in prompt model development to enhance your understanding and application of advanced prompting techniques.
Browse courses on Prompt Engineering
Show steps
  • Select a specific NLP task (e.g., summarization, text generation).
  • Craft a set of prompts based on advanced prompting methods (e.g., prefix tuning, in-context learning).
  • Train and evaluate a language model using your prompts.
  • Analyze the performance of your model and iterate on your prompts as needed.
Share your knowledge and assist fellow learners
Enhance your understanding of the course material while helping others by answering questions or providing guidance.
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  • Join online forums or communities related to prompt engineering.
  • Offer assistance to other learners who may be struggling with concepts.
  • Share your insights and experiences to foster a collaborative learning environment.
Apply prompt engineering to real-world scenarios
Put your prompt engineering skills to the test by applying them to real-world tasks and challenges.
Browse courses on Text Summarization
Show steps
  • Choose a specific use case or task to focus on.
  • Prepare a dataset or gather relevant materials.
  • Experiment with different prompts and techniques to achieve desired outputs.
  • Analyze and evaluate the results of your experiments.
  • Refine and optimize your prompts based on your findings.
Create a Comprehensive Guide to Prompt Engineering Best Practices
Synthesize your knowledge and understanding of prompt engineering by creating a resource that benefits the broader learning community.
Browse courses on Prompt Engineering
Show steps
  • Research and compile best practices for prompt engineering from various sources.
  • Organize and structure the information into a comprehensive guide.
  • Write clear and concise instructions, providing examples and explanations.
  • Publish your guide on a relevant platform (e.g., Medium, GitHub).
Attend workshops and conferences focused on prompt engineering
Stay up-to-date with the latest advancements and best practices in prompt engineering by participating in industry events.
Show steps
  • Research upcoming workshops and conferences related to prompt engineering.
  • Register for events that align with your interests and learning goals.
  • Attend sessions, engage in discussions, and network with experts.
Build a portfolio showcasing your prompt engineering skills
Create a collection of projects and examples that demonstrate your proficiency in prompt engineering and its applications.
Browse courses on Portfolio Development
Show steps
  • Identify the types of projects or examples you want to include.
  • Gather and organize relevant materials.
  • Develop or refine your prompts to achieve desired outputs.
  • Document your process, techniques, and results.
  • Present your portfolio to potential employers or clients.
Contribute to open-source projects related to prompt engineering
Deepen your understanding by collaborating on open-source projects and enhancing existing prompt engineering tools and resources.
Browse courses on Collaborative Development
Show steps
  • Identify open-source projects that align with your interests.
  • Join online communities and forums to connect with project contributors.
  • Review project documentation and codebase to understand its functionality.
  • Suggest improvements, report bugs, or contribute code to the project.

Career center

Learners who complete Prompt Engineering for Improved Performance will develop knowledge and skills that may be useful to these careers:
Language Model Engineer
Language Model Engineers specialize in developing and maintaining language models, the underlying technology that powers many applications such as chatbots, automated customer service, and machine translation. Advanced Prompt Engineering techniques improve the accuracy and performance of language models, making this course an important step for Engineers seeking to advance their abilities within this role.
Natural Language Processing Scientist
Natural Language Processing (NLP) Scientists apply their knowledge of computational linguistics and machine learning to enable computers to understand and generate human language. Advanced Prompt Engineering techniques help NLP Scientists to extract meaning from text and generate more natural-sounding language, enhancing the performance of NLP applications.
Machine Learning Engineer
Machine Learning Engineers build, deploy, and maintain machine learning models. Prompt Engineering is an essential technique in machine learning, as it allows Engineers to fine-tune models and improve their performance. This course can help Machine Learning Engineers to develop the skills they need to succeed in this role.
Computational Linguist
Computational Linguists study the relationship between language and computation. Advanced Prompt Engineering techniques are based on computational linguistics, and this course can help Computational Linguists to develop the skills they need to build and evaluate language models.
Data Scientist
Data Scientists use data to solve business problems. Advanced Prompt Engineering techniques can help Data Scientists to extract insights from text data, which is often unstructured and difficult to analyze. This course can help Data Scientists to improve the accuracy and efficiency of their work.
Technical Writer
Technical Writers create documentation and other materials that explain complex technical information. Advanced Prompt Engineering techniques can help Technical Writers to improve the clarity and accuracy of their writing, making it easier for readers to understand technical concepts.
Editor
Editors review, edit, and proofread written content. Advanced Prompt Engineering techniques can help Editors to improve the quality and consistency of their work, making it easier to produce high-quality written content.
Content Writer
Content Writers create content for websites, blogs, and other online platforms. Advanced Prompt Engineering techniques can help Content Writers to create more engaging and informative content, which can help to attract and retain readers.
Sales Manager
Sales Managers develop and execute sales strategies. Advanced Prompt Engineering techniques can help Sales Managers to identify and qualify leads, close deals, and manage customer relationships.
Customer Success Manager
Customer Success Managers help customers to achieve success with a product or service. Advanced Prompt Engineering techniques can help Customer Success Managers to identify and resolve customer issues, and to build strong customer relationships.
User Experience (UX) Designer
UX Designers create user interfaces that are easy to use and understand. Advanced Prompt Engineering techniques can help UX Designers to gather feedback from users and improve the usability of their designs.
Project Manager
Project Managers plan and execute projects. Advanced Prompt Engineering techniques can help Project Managers to gather feedback from stakeholders and improve the quality of their projects.
Product Manager
Product Managers develop and manage products. Advanced Prompt Engineering techniques can help Product Managers to gather feedback from users and improve the quality of their products.
Operations Manager
Operations Managers oversee the day-to-day operations of a business. Advanced Prompt Engineering techniques can help Operations Managers to identify and resolve operational issues, and to improve the efficiency of their operations.
Marketing Manager
Marketing Managers develop and execute marketing campaigns. Advanced Prompt Engineering techniques can help Marketing Managers to create more effective marketing campaigns, which can help to attract and retain customers.

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Prompt Engineering for Improved Performance.
This foundational textbook offers a comprehensive understanding of natural language understanding, providing a valuable resource for those interested in prompt engineering and performance improvement.
This comprehensive textbook introduces NLP techniques using Python, providing a valuable resource for understanding prompt engineering and model performance.
This introductory textbook provides a solid foundation in NLP concepts and techniques, including topics relevant to prompt engineering and performance optimization.
This comprehensive textbook provides a strong foundation in speech and language engineering, covering topics relevant to prompt engineering, such as natural language understanding and generation.
This practical guide covers essential machine learning techniques using popular libraries, providing a solid foundation for understanding prompt engineering and performance optimization.
This foundational book by the creator of Keras offers a comprehensive introduction to deep learning with Python, providing insights into model training and optimization relevant to prompt engineering.
This approachable guide to deep learning with Fastai and PyTorch offers practical insights into model training and optimization, which can enhance prompt engineering and performance.
Serves as a foundational resource for speech and language processing, providing a comprehensive understanding of the principles that inform prompt engineering techniques.
Offers a comprehensive analysis of human communication, providing a theoretical foundation for understanding the principles of language use.
Explores deep learning methods for natural language understanding, offering insights into the techniques used in prompt engineering.

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