We may earn an affiliate commission when you visit our partners.
Charles Ivan Niswander II
By the end of this project, you will have learned the basics behind designing and coding Generative Adversarial Networks, or GANs. This project will familiarize you with concepts and techniques at work behind the scenes in GANs and deepfakes. The methods you...
Read more
By the end of this project, you will have learned the basics behind designing and coding Generative Adversarial Networks, or GANs. This project will familiarize you with concepts and techniques at work behind the scenes in GANs and deepfakes. The methods you...
Read more
By the end of this project, you will have learned the basics behind designing and coding Generative Adversarial Networks, or GANs. This project will familiarize you with concepts and techniques at work behind the scenes in GANs and deepfakes. The methods you will learn in the course of this project will enable you to build Generative Adversarial Networks for any potential purpose and provide valuable experience in your Machine Learning and Artificial Intelligence development journey.
Python experience is heavily recommended.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/urqgxj/building
Two deals to help you save
We found two deals and offers that may be relevant to this course.
Save money when you learn.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Course introduces the technical details behind the scenes of Generative Adversarial Networks (GANs) and deepfakes
Covers concepts, tools, and their practical applications in custom Generative Adversarial Networks
Provides a foundation for further Machine Learning and Artificial Intelligence (AI) exploration and development
Recommended for learners with Python experience
May be more suitable for students in North America
Save this course
Save Building your first GAN in Python to your list so you can find it easily later:
Save
Save
Reviews summary
Gan basics and implementation
Overall, this course may not be the best option for those looking for a thorough understanding of GANs. Many students have commented on how the explanations were too brief and not deep enough to give them a full grasp of the concepts. Some reviews also described the course as outdated, which may also be a concern for some learners. However, there have been some positive reviews, with some saying how interesting the topic was, which may also be a deciding factor for some learners.
Interesting topic
"Interesting topic! Thorough yet simplified. Recommended"
Outdated information
"...It also seems that this is very far from the current state of tensorflow and is using some outaded code..."
Unclear explanations
"...Doesn't take the time to explain what is being done or why."
"The explaination of the code is too brief to understand anything about what's going on."
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 Building your first GAN in Python with these
activities:
Explore pre-trained GAN models
Show steps
Increase your exposure to GANs. Start exploring existing GANs to get a sense of their capabilities and limitations.
Show steps
-
Find a pre-trained GAN that interests you
-
Study the GAN's architecture and training process
-
Use the GAN to generate your own data
Build a GAN from scratch
Show steps
Challenge yourself: Start with the raw theoretical knowledge covered in the course and apply them in a practical manner. Gain a deeper understanding of how GANs work and develop your skills.
Show steps
-
Code a generator model
-
Code a discriminator model
-
Create a training loop that trains the generator and discriminator models
-
Improve your GAN by tweaking the hyperparameters and architectures
-
Optionally, create a user interface for your GAN
Show all two activities
Explore pre-trained GAN models
Show steps
Increase your exposure to GANs. Start exploring existing GANs to get a sense of their capabilities and limitations.
Show steps
Show steps
Show steps
- Find a pre-trained GAN that interests you
- Study the GAN's architecture and training process
- Use the GAN to generate your own data
Build a GAN from scratch
Show steps
Challenge yourself: Start with the raw theoretical knowledge covered in the course and apply them in a practical manner. Gain a deeper understanding of how GANs work and develop your skills.
Show steps
Show steps
Show steps
- Code a generator model
- Code a discriminator model
- Create a training loop that trains the generator and discriminator models
- Improve your GAN by tweaking the hyperparameters and architectures
- Optionally, create a user interface for your GAN
Show all two activities
Career center
Learners who complete Building your first GAN in Python will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, builds, and maintains machine learning models and applications. This role may also involve developing and implementing machine learning algorithms, as well as working on projects related to artificial intelligence and data science. The Building your first GAN in Python course can help you prepare for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course will also teach you how to code GANs in Python, a valuable skill for any Machine Learning Engineer.
Data Scientist
Data Scientist
A Data Scientist uses data to solve problems and make decisions. This role may involve collecting, cleaning, and analyzing data, as well as developing and implementing machine learning models. The Building your first GAN in Python course can help you prepare for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course will also teach you how to code GANs in Python, a valuable skill for any Data Scientist.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This role may involve working on projects related to artificial intelligence and data science. The Building your first GAN in Python course can help you prepare for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course will also teach you how to code GANs in Python, a valuable skill for any Software Engineer.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
An Artificial Intelligence Engineer designs, develops, and maintains artificial intelligence systems. This role may involve working on projects related to machine learning, computer vision, and natural language processing. The Building your first GAN in Python course can help you prepare for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course will also teach you how to code GANs in Python, a valuable skill for any Artificial Intelligence Engineer.
Data Analyst
Data Analyst
A Data Analyst collects, cleans, and analyzes data to help businesses make decisions. This role may involve using machine learning and artificial intelligence to solve problems and improve business outcomes. The Building your first GAN in Python course can help you prepare for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course will also teach you how to code GANs in Python, a valuable skill for any Data Analyst.
Business Analyst
Business Analyst
A Business Analyst helps businesses identify and solve problems. This role may involve using data analysis and machine learning to improve business outcomes. The Building your first GAN in Python course can help you prepare for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course will also teach you how to code GANs in Python, a valuable skill for any Business Analyst.
Project Manager
Project Manager
A Project Manager plans, executes, and closes projects. This role may involve working with a team of engineers, designers, and other professionals to bring a project to completion. The Building your first GAN in Python course may be useful for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course may also teach you how to code GANs in Python, a skill that may be useful for project management.
Product Manager
Product Manager
A Product Manager oversees the development and marketing of a product. This role may involve working with engineers, designers, and marketers to bring a product to market. The Building your first GAN in Python course may be useful for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course may also teach you how to code GANs in Python, a skill that may be useful for product development.
Financial Analyst
Financial Analyst
A Financial Analyst researches and analyzes financial data to make investment recommendations. This role may involve using machine learning and artificial intelligence to improve investment outcomes. The Building your first GAN in Python course may be useful for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course may also teach you how to code GANs in Python, a skill that may be useful for financial analysis.
Marketing Analyst
Marketing Analyst
A Marketing Analyst researches and analyzes marketing data to improve marketing campaigns. This role may involve using machine learning and artificial intelligence to improve marketing outcomes. The Building your first GAN in Python course may be useful for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course may also teach you how to code GANs in Python, a skill that may be useful for marketing analysis.
Sales Analyst
Sales Analyst
A Sales Analyst researches and analyzes sales data to improve sales performance. This role may involve using machine learning and artificial intelligence to improve sales outcomes. The Building your first GAN in Python course may be useful for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course may also teach you how to code GANs in Python, a skill that may be useful for sales analysis.
Computer Scientist
Computer Scientist
A Computer Scientist researches and develops new computer technologies. This role may involve working on projects related to artificial intelligence, machine learning, and other areas of computer science. The Building your first GAN in Python course may be useful for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course may also teach you how to code GANs in Python, a skill that may be useful for computer science research.
Technical Writer
Technical Writer
A Technical Writer creates and maintains documentation for software and other technical products. This role may involve writing user manuals, training materials, and other documents. The Building your first GAN in Python course may be useful for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course may also teach you how to code GANs in Python, a skill that may be useful for technical writing.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematical and statistical models to solve business problems. This role may involve working on projects related to machine learning, artificial intelligence, and other areas of operations research. The Building your first GAN in Python course may be useful for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course may also teach you how to code GANs in Python, a skill that may be useful for operations research.
Statistician
Statistician
A Statistician collects, analyzes, and interprets data. This role may involve working on projects related to machine learning, artificial intelligence, and other areas of statistics. The Building your first GAN in Python course may be useful for this role by providing you with a foundational understanding of GANs, a type of machine learning model that can be used to generate realistic data. This course may also teach you how to code GANs in Python, a skill that may be useful for statistics research.
For more career information including salaries, visit:
OpenCourser.com/course/urqgxj/building
Reading list
We've selected ten 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
Building your first GAN in Python.
Save
Provides a comprehensive overview of GANs, covering the theoretical foundations, algorithms, and applications. It valuable resource for anyone interested in understanding and implementing GANs.
Save
Provides a broad overview of deep learning, including a discussion of GANs. It good starting point for anyone new to deep learning.
Provides a practical introduction to deep learning using Python. It good resource for anyone interested in implementing GANs in Python.
Provides a practical introduction to machine learning using Python. It good resource for anyone interested in implementing GANs in Python.
Provides a comprehensive overview of deep learning for natural language processing. It good resource for anyone interested in using GANs for natural language processing tasks.
Provides a comprehensive overview of machine learning in Python, including its history, theory, and applications. It valuable resource for anyone who wants to learn more about machine learning in Python.
Save
Provides a practical guide to machine learning, with a focus on building and training machine learning models. It valuable resource for anyone who wants to learn more about machine learning in Chinese.
Provides a comprehensive overview of data analysis in Python, including its history, theory, and applications. It valuable resource for anyone who wants to learn more about data analysis in Python.
Provides a comprehensive overview of statistical learning, including its history, theory, and applications. It valuable resource for anyone who wants to learn more about statistical learning.
Provides a gentle introduction to machine learning, with a focus on making machine learning accessible to everyone. It valuable resource for anyone who wants to learn more about machine learning in Chinese.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/urqgxj/building
Share
Similar courses
Here are nine courses similar to
Building your first GAN in Python.
Literacy Essentials: Core Concepts Generative Adversarial Network
OpenCourser.com/course/9y5k1i/literacy
Literacy Essentials: Core Concepts Generative Adversarial...
Most relevant
Build Basic Generative Adversarial Networks (GANs)
OpenCourser.com/course/wdzacy/build
Build Basic Generative Adversarial Networks (GANs)
Most relevant
Building Generative Adversarial Networks
OpenCourser.com/course/wdp89a/building
Building Generative Adversarial Networks
Most relevant
Build Better Generative Adversarial Networks (GANs)
OpenCourser.com/course/ree7t9/build
Build Better Generative Adversarial Networks (GANs)
Most relevant
Introduction to Generative AI
OpenCourser.com/course/cvp0l1/introduction
Introduction to Generative AI
Most relevant
Data Balancing with Gen AI: Credit Card Fraud Detection
OpenCourser.com/course/1dbbn2/data
Data Balancing with Gen AI: Credit Card Fraud Detection
Most relevant
Deep Learning - Generative Adversarial Networks
OpenCourser.com/course/sfbm6b/udacity
Deep Learning - Generative Adversarial Networks
Most relevant
Style Transfer with PyTorch
OpenCourser.com/course/p0gczd/style
Style Transfer with PyTorch
Most relevant
Exploring Generative AI Models and Architecture
OpenCourser.com/course/l1q963/exploring
Exploring Generative AI Models and Architecture
Most relevant
Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Charles Ivan Niswander II
Good to know
Course introduces the technical details behind the scenes of Generative Adversarial Networks (GANs) and deepfakes
Covers concepts, tools, and their practical applications in custom Generative Adversarial Networks
Provides a foundation for further Machine Learning and Artificial Intelligence (AI) exploration and development
Recommended for learners with Python experience
May be more suitable for students in North America
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser