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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console.
This lab focuses on the essentials and best practices of prompt design to help you learn how to design good quality prompts, how to interact with PaLM to get the responses you’re looking for, and how to be aware of hallucinations in responses.
Register for this course and see more details by visiting:
OpenCourser.com/course/mvgmd2/prompt
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What's inside
Syllabus
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Read about what's good
what should give you pause and
possible dealbreakers
Uses a self-paced lab in the Google Cloud console, giving learners hands-on experience
Covers the essentials and best practices of prompt design
Provides guidance on interacting with PaLM to get desirable responses
Focuses on prompt design, which is crucial for effective AI interaction
Emphasizes awareness of hallucinations in responses, promoting critical thinking
Taught by Google Cloud Training, recognized for their expertise in cloud technologies
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Reviews summary
Palm prompt design essentials
According to learners, this course offers an incredibly well-structured and concise introduction to prompt engineering, specifically with Google's PaLM model. Students consistently highlight the practical, hands-on lab experience within the Google Cloud console as a major strength, finding it highly effective for solidifying understanding. The course is praised for its clear examples and focus on best practices, particularly in mitigating AI hallucinations and getting effective responses. While it provides a solid foundational knowledge for beginners, some more experienced users expressed that the content could be too rudimentary or lacking in advanced depth, positioning it more as a starting point rather than a comprehensive guide.
Provides valuable insights on handling AI hallucinations and best practices.
"The part on mitigating hallucinations was particularly insightful."
"The focus on best practices and anticipating common issues, like unintended responses, made it immediately applicable to my work."
"I appreciated the specific tips on getting better responses from PaLM and understanding its limitations, especially regarding 'hallucinations'."
Offers a clear and concise introduction perfect for new learners.
"This course is incredibly well-structured and concise. It provides a fantastic hands-on introduction to prompt engineering with PaLM, especially useful for those new to the field."
"A very good starting point for understanding prompt design principles. It delivers solid foundational knowledge."
"It's definitely for absolute beginners, not intermediate users."
The hands-on lab in Google Cloud console is highly effective for learning.
"I gained practical skills for designing effective prompts and loved the clear examples. The part on mitigating hallucinations was particularly insightful."
"Absolutely brilliant! As a developer, I found the practical nature of this lab invaluable. It cut straight to the chase..."
"The practical exercises are excellent and really help you grasp the concepts. Good for a quick skill upgrade."
May be too basic for those with prior prompt engineering experience.
"I came into this with some prior experience in LLMs and prompt engineering, and frankly, I found it a bit too rudimentary."
"My only wish is that it covered a broader range of advanced prompting techniques..."
"Felt a bit too short and high-level for me. I was looking for something more in-depth on prompt optimization and advanced techniques."
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 Design using PaLM with these
activities:
Follow tutorials on NLP basics
Show steps
Enhance your understanding of core NLP concepts through guided tutorials covering tokenization, stemming, and part-of-speech tagging.
Browse courses on
Natural Language Processing
Show steps
-
Find tutorials on NLP basics
-
Complete the tutorials
-
Practice NLP tasks
Practice NLP exercises
Show steps
Reinforce your learning by completing exercises focusing on NLP tasks like text classification and sentiment analysis.
Browse courses on
Natural Language Processing
Show steps
-
Find NLP exercises
-
Complete the exercises
-
Review your results
Attend NLP study group meetings
Show steps
Connect with peers, exchange knowledge, and engage in discussions on NLP topics, fostering a collaborative learning environment.
Browse courses on
Natural Language Processing
Show steps
-
Find an NLP study group
-
Attend the meetings
-
Participate in discussions
Two other activities
Expand to see all activities and additional details
Show all five activities
Try out online NLP courses
Show steps
Expand your knowledge through online NLP courses, delving deeper into specific aspects of the field and gaining a more comprehensive understanding.
Browse courses on
Natural Language Processing
Show steps
-
Find online NLP courses
-
Enroll in the courses
-
Complete the courses
Create a blog post on NLP use cases
Show steps
Demonstrate your understanding by writing a blog post that explores real-world applications of NLP, showcasing your knowledge and critical thinking skills.
Browse courses on
Natural Language Processing
Show steps
-
Choose NLP use cases
-
Research the use cases
-
Write the blog post
Follow tutorials on NLP basics
Show steps
Enhance your understanding of core NLP concepts through guided tutorials covering tokenization, stemming, and part-of-speech tagging.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Find tutorials on NLP basics
- Complete the tutorials
- Practice NLP tasks
Practice NLP exercises
Show steps
Reinforce your learning by completing exercises focusing on NLP tasks like text classification and sentiment analysis.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Find NLP exercises
- Complete the exercises
- Review your results
Attend NLP study group meetings
Show steps
Connect with peers, exchange knowledge, and engage in discussions on NLP topics, fostering a collaborative learning environment.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Find an NLP study group
- Attend the meetings
- Participate in discussions
Two other activities
Expand to see all activities and additional details
Show all five activities
Try out online NLP courses
Show steps
Expand your knowledge through online NLP courses, delving deeper into specific aspects of the field and gaining a more comprehensive understanding.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Find online NLP courses
- Enroll in the courses
- Complete the courses
Create a blog post on NLP use cases
Show steps
Demonstrate your understanding by writing a blog post that explores real-world applications of NLP, showcasing your knowledge and critical thinking skills.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Choose NLP use cases
- Research the use cases
- Write the blog post
Career center
Learners who complete Prompt Design using PaLM will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist analyzes data to extract insights and make predictions. This course may be useful for Data Scientists who want to learn how to design prompts that effectively interact with PaLM, a large language model, to get the responses they're looking for. This course can help Data Scientists improve the quality of their data analysis and make more accurate predictions.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning models. This course may be useful for Machine Learning Engineers who want to learn how to design prompts that effectively interact with PaLM to enhance the performance and accuracy of their machine learning models.
Natural Language Processing Engineer
Natural Language Processing Engineer
A Natural Language Processing Engineer develops and applies techniques to process and analyze natural language data. This course may be useful for Natural Language Processing Engineers who want to learn how to design prompts that effectively interact with PaLM to improve the accuracy and efficiency of their natural language processing tasks.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course may be useful for Software Engineers who want to learn how to design prompts that effectively interact with PaLM to automate tasks, improve code quality, and increase productivity.
Product Manager
Product Manager
A Product Manager defines and manages the development of products. This course may be useful for Product Managers who want to learn how to design prompts that effectively interact with PaLM to gather user feedback, generate ideas, and make data-driven decisions.
Data Analyst
Data Analyst
A Data Analyst collects, analyzes, and interprets data to identify trends and patterns. This course may be useful for Data Analysts who want to learn how to design prompts that effectively interact with PaLM to uncover insights and make better decisions.
Business Analyst
Business Analyst
A Business Analyst analyzes business processes and identifies areas for improvement. This course may be useful for Business Analysts who want to learn how to design prompts that effectively interact with PaLM to gain insights into business operations and make recommendations for improvement.
UX Designer
UX Designer
A UX Designer designs user interfaces and experiences. This course may be useful for UX Designers who want to learn how to design prompts that effectively interact with PaLM to gather user feedback, improve user experience, and increase usability.
Content Writer
Content Writer
A Content Writer creates and edits written content. This course may be useful for Content Writers who want to learn how to design prompts that effectively interact with PaLM to generate ideas, write better content, and improve their storytelling skills.
Technical Writer
Technical Writer
A Technical Writer creates and edits technical documentation. This course may be useful for Technical Writers who want to learn how to design prompts that effectively interact with PaLM to write clear and concise technical documentation.
Instructional Designer
Instructional Designer
An Instructional Designer creates and develops educational materials. This course may be useful for Instructional Designers who want to learn how to design prompts that effectively interact with PaLM to create engaging and effective learning experiences.
Project Manager
Project Manager
A Project Manager plans, executes, and closes projects. This course may be useful for Project Managers who want to learn how to design prompts that effectively interact with PaLM to manage projects, track progress, and communicate with stakeholders.
Marketing Manager
Marketing Manager
A Marketing Manager develops and executes marketing campaigns. This course may be useful for Marketing Managers who want to learn how to design prompts that effectively interact with PaLM to generate creative ideas, target the right audience, and track campaign performance.
Sales Manager
Sales Manager
A Sales Manager leads and manages a sales team. This course may be useful for Sales Managers who want to learn how to design prompts that effectively interact with PaLM to identify potential customers, close deals, and build relationships.
Customer Success Manager
Customer Success Manager
A Customer Success Manager ensures that customers are satisfied with a company's products or services. This course may be useful for Customer Success Managers who want to learn how to design prompts that effectively interact with PaLM to resolve customer issues, build relationships, and increase customer satisfaction.
For more career information including salaries, visit:
OpenCourser.com/course/mvgmd2/prompt
Reading list
We've selected 11 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 Design using PaLM.
Provides a comprehensive overview of language models, including their history, architectures, and applications. It valuable resource for anyone who wants to learn more about this rapidly evolving field.
Save
Comprehensive overview of deep learning. It covers a wide range of topics, including neural networks, deep learning architectures, and applications.
Hands-on guide to deep learning. It covers a wide range of topics, including neural networks, deep learning architectures, and applications.
Practical guide to machine learning with Python. It covers a wide range of topics, including data preprocessing, feature engineering, model selection, and hyperparameter tuning.
Practical guide to machine learning with R. It covers a wide range of topics, including data preprocessing, feature engineering, model selection, and hyperparameter tuning.
Practical guide to machine learning with Python. It covers a wide range of topics, including data preprocessing, feature engineering, model selection, and hyperparameter tuning.
Provides a probabilistic perspective on machine learning. It covers a wide range of topics, including Bayesian inference, graphical models, and Gaussian processes.
Comprehensive overview of reinforcement learning. It covers a wide range of topics, including Markov decision processes, value functions, and reinforcement learning algorithms.
Comprehensive overview of deep reinforcement learning. It covers a wide range of topics, including deep neural networks, reinforcement learning algorithms, and applications.
Save
Comprehensive overview of generative adversarial networks. It covers a wide range of topics, including GAN architectures, training techniques, and applications.
Comprehensive overview of machine learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/mvgmd2/prompt
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