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Level up your Generative AI skills with Udacity's Zero-Shot & Few-Shot Training Course. Unlock your AI prompt optimization skills, and more. Sign up today!
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What's inside
Syllabus
Optimize your generative AI prompts using zero-shot and few-shot learning techniques.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops zero-shot and few-shot prompt optimization skills, which are valuable for AI practitioners
Taught by experts in the field of generative AI, providing access to industry-leading insights
Offered through Udacity, a reputable platform known for its high-quality online courses
Covers foundational concepts and techniques in zero-shot and few-shot learning, making it suitable for both beginners and experienced practitioners
Requires a familiarity with generative AI concepts, making it less accessible to complete novices
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Save Zero-Shot and Few-Shot Learning to your list so you can find it easily later:
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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 Zero-Shot and Few-Shot Learning with these
activities:
Read Introduction to Statistical Learning
Show steps
This book provides a comprehensive overview of statistical learning methods, which are essential for generative AI.
View
An Introduction to Statistical Learning: with...
on Amazon
Show steps
-
Read the book
-
Take notes
-
Complete the exercises
Join a study group or online forum
Show steps
Joining a study group or online forum is a great way to connect with other learners and get help with your studies.
Browse courses on
AI
Show steps
-
Find a study group or online forum
-
Introduce yourself
-
Participate in discussions
-
Ask for help when you need it
Attend a workshop on generative AI
Show steps
Attending a workshop is a great way to learn about generative AI from experts in the field.
Browse courses on
AI
Show steps
-
Find a workshop on generative AI
-
Register for the workshop
-
Attend the workshop
-
Take notes
-
Ask questions
Five other activities
Expand to see all activities and additional details
Show all eight activities
Udacity's Zero-Shot & Few-Shot Training AI tutorial
Show steps
This tutorial is a great way to get started with generative AI and learn about zero-shot and few-shot learning techniques.
Browse courses on
AI
Show steps
-
Watch the video tutorials
-
Follow along with the code examples
-
Complete the practice exercises
Practice using zero-shot and few-shot learning techniques
Show steps
Practice is essential for mastering any new skill. This is especially true for generative AI, which can be a complex and challenging topic.
Browse courses on
AI
Show steps
-
Find a dataset that you can use to practice zero-shot and few-shot learning techniques
-
Build a model that can use zero-shot and few-shot learning techniques
-
Train your model on the dataset
-
Evaluate your model's performance
Write a blog post about zero-shot and few-shot learning techniques
Show steps
Writing a blog post is a great way to share your knowledge and insights with others.
Browse courses on
AI
Show steps
-
Choose a topic for your blog post
-
Write an outline
-
Write the first draft
-
Edit and revise your blog post
-
Publish your blog post
Build a generative AI project
Show steps
The best way to learn generative AI is to build a project. This will give you the opportunity to apply your skills and knowledge to a real-world problem.
Browse courses on
AI
Show steps
-
Come up with an idea for a generative AI project
-
Gather the data you need to train your model
-
Build a model
-
Train your model
-
Evaluate your model's performance
-
Deploy your model
Contribute to an open-source generative AI project
Show steps
Contributing to an open-source project is a great way to learn about generative AI and get involved in the community.
Browse courses on
AI
Show steps
-
Find an open-source generative AI project
-
Read the project's documentation
-
Choose a way to contribute
-
Submit your contribution
Read Introduction to Statistical Learning
Show steps
This book provides a comprehensive overview of statistical learning methods, which are essential for generative AI.
View
An Introduction to Statistical Learning: with...
on Amazon
Show steps
Show steps
Show steps
- Read the book
- Take notes
- Complete the exercises
Join a study group or online forum
Show steps
Joining a study group or online forum is a great way to connect with other learners and get help with your studies.
Browse courses on
AI
Show steps
Show steps
Show steps
- Find a study group or online forum
- Introduce yourself
- Participate in discussions
- Ask for help when you need it
Attend a workshop on generative AI
Show steps
Attending a workshop is a great way to learn about generative AI from experts in the field.
Browse courses on
AI
Show steps
Show steps
Show steps
- Find a workshop on generative AI
- Register for the workshop
- Attend the workshop
- Take notes
- Ask questions
Five other activities
Expand to see all activities and additional details
Show all eight activities
Udacity's Zero-Shot & Few-Shot Training AI tutorial
Show steps
This tutorial is a great way to get started with generative AI and learn about zero-shot and few-shot learning techniques.
Browse courses on
AI
Show steps
Show steps
Show steps
- Watch the video tutorials
- Follow along with the code examples
- Complete the practice exercises
Practice using zero-shot and few-shot learning techniques
Show steps
Practice is essential for mastering any new skill. This is especially true for generative AI, which can be a complex and challenging topic.
Browse courses on
AI
Show steps
Show steps
Show steps
- Find a dataset that you can use to practice zero-shot and few-shot learning techniques
- Build a model that can use zero-shot and few-shot learning techniques
- Train your model on the dataset
- Evaluate your model's performance
Write a blog post about zero-shot and few-shot learning techniques
Show steps
Writing a blog post is a great way to share your knowledge and insights with others.
Browse courses on
AI
Show steps
Show steps
Show steps
- Choose a topic for your blog post
- Write an outline
- Write the first draft
- Edit and revise your blog post
- Publish your blog post
Build a generative AI project
Show steps
The best way to learn generative AI is to build a project. This will give you the opportunity to apply your skills and knowledge to a real-world problem.
Browse courses on
AI
Show steps
Show steps
Show steps
- Come up with an idea for a generative AI project
- Gather the data you need to train your model
- Build a model
- Train your model
- Evaluate your model's performance
- Deploy your model
Contribute to an open-source generative AI project
Show steps
Contributing to an open-source project is a great way to learn about generative AI and get involved in the community.
Browse courses on
AI
Show steps
Show steps
Show steps
- Find an open-source generative AI project
- Read the project's documentation
- Choose a way to contribute
- Submit your contribution
Career center
Learners who complete Zero-Shot and Few-Shot Learning will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers develop, test, and manage machine learning models. They work on a variety of projects, from building self-driving cars to developing new medical treatments. This course can help you build a strong foundation in machine learning, which is essential for success in this field. The course covers topics such as supervised learning, unsupervised learning, and deep learning.
Data Scientist
Data Scientist
Data Scientists use data to solve problems and make decisions. They work in a variety of industries, including finance, healthcare, and retail. This course can help you develop the skills you need to be a successful Data Scientist. The course covers topics such as data cleaning, data analysis, and data visualization.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. They work on a variety of projects, from building websites to developing mobile apps. This course can help you build a strong foundation in software engineering, which is essential for success in this field. The course covers topics such as software design, software development, and software testing.
Data Analyst
Data Analyst
Data Analysts use data to identify trends and patterns. They work in a variety of industries, including finance, healthcare, and retail. This course can help you develop the skills you need to be a successful Data Analyst. The course covers topics such as data cleaning, data analysis, and data visualization.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data. They work in a variety of industries, including finance, insurance, and healthcare. This course can help you develop the skills you need to be a successful Quantitative Analyst. The course covers topics such as probability, statistics, and financial modeling.
Business Analyst
Business Analyst
Business Analysts use data to help businesses make better decisions. They work in a variety of industries, including finance, healthcare, and retail. This course can help you develop the skills you need to be a successful Business Analyst. The course covers topics such as data analysis, business process modeling, and project management.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. They work in a variety of industries, including finance, healthcare, and government. This course can help you develop the skills you need to be a successful Statistician. The course covers topics such as probability, statistics, and data analysis.
Actuary
Actuary
Actuaries use mathematical and statistical models to assess risk. They work in a variety of industries, including insurance, finance, and healthcare. This course can help you develop the skills you need to be a successful Actuary. The course covers topics such as probability, statistics, and financial modeling.
Risk Analyst
Risk Analyst
Risk Analysts use data to identify and assess risks. They work in a variety of industries, including finance, insurance, and healthcare. This course can help you develop the skills you need to be a successful Risk Analyst. The course covers topics such as probability, statistics, and financial modeling.
Financial Analyst
Financial Analyst
Financial Analysts use data to analyze financial markets and make investment decisions. They work in a variety of industries, including finance, insurance, and investment management. This course can help you develop the skills you need to be a successful Financial Analyst. The course covers topics such as financial modeling, investment analysis, and portfolio management.
Investment Manager
Investment Manager
Investment Managers manage investment portfolios for individuals and institutions. They work in a variety of industries, including finance, insurance, and investment management. This course can help you develop the skills you need to be a successful Investment Manager. The course covers topics such as investment analysis, portfolio management, and risk management.
Professor
Professor
Professors teach and research at colleges and universities. They work in a variety of fields, including science, engineering, and business. This course can help you develop the skills you need to be a successful Professor. The course covers topics such as teaching, research, and curriculum development.
Researcher
Researcher
Researchers conduct research in a variety of fields, including science, engineering, and business. They work in a variety of settings, including universities, government labs, and private companies. This course can help you develop the skills you need to be a successful Researcher. The course covers topics such as research design, data analysis, and scientific writing.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data systems. They work in a variety of industries, including finance, healthcare, and retail. This course can help you develop the skills you need to be a successful Data Engineer. The course covers topics such as data warehousing, data mining, and big data.
Machine Learning Researcher
Machine Learning Researcher
Machine Learning Researchers develop new machine learning algorithms and techniques. They work in a variety of settings, including universities, government labs, and private companies. This course can help you develop the skills you need to be a successful Machine Learning Researcher. The course covers topics such as machine learning theory, deep learning, and reinforcement learning.
For more career information including salaries, visit:
OpenCourser.com/course/9e5wfh/zero
Reading list
We've selected seven 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
Zero-Shot and Few-Shot Learning.
Offers a theoretical and practical exploration of generative AI models. It provides a deep dive into the mathematical foundations and practical applications of generative models, including zero-shot and few-shot learning.
This popular book provides a comprehensive introduction to deep learning using Python. While it is not specific to zero-shot and few-shot learning, it offers a solid foundation for understanding the underlying concepts.
Provides a comprehensive introduction to optimization for deep learning, covering a wide range of topics, including gradient descent, backpropagation, and hyperparameter tuning. It is particularly useful for readers who want to understand the theoretical foundations of optimization for deep learning.
While not specifically focused on zero-shot or few-shot learning, this book provides a comprehensive overview of deep learning techniques used in natural language processing and speech recognition. It offers a solid foundation for understanding the underlying algorithms.
Transformers are widely used in zero-shot and few-shot learning. offers a detailed exploration of transformer architectures and their applications in natural language processing tasks.
While not specifically focused on zero-shot or few-shot learning, this book provides a solid foundation in deep learning techniques used in natural language processing. It offers a comprehensive overview of the field and can serve as a valuable background resource.
Save
Provides a comprehensive overview of computer vision algorithms and techniques. While it does not specifically cover zero-shot and few-shot learning, it offers valuable background knowledge for understanding these methods.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/9e5wfh/zero
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Effort
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Via
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Language
English
Good to know
Develops zero-shot and few-shot prompt optimization skills, which are valuable for AI practitioners
Taught by experts in the field of generative AI, providing access to industry-leading insights
Offered through Udacity, a reputable platform known for its high-quality online courses
Covers foundational concepts and techniques in zero-shot and few-shot learning, making it suitable for both beginners and experienced practitioners
Requires a familiarity with generative AI concepts, making it less accessible to complete novices
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