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In this course, you will learn about the technical foundations and key terminology related to generative artificial intelligence (AI). You will also learn how to evaluate the risks and benefits of using generative AI, and explore the steps to planning a generative AI project.
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What's inside
Syllabus
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Explores generative artificial intelligence (AI), which is a popular topic in tech companies such as OpenAI and Google DeepMind
Taught by AWS Instructors, who are a trusted source in cloud computing and machine learning
Develops skills in evaluating the risks and benefits of using generative AI, which are necessary to developing AI systems
Covers planning a generative AI project, which is helpful for understanding the real-world applications of generative AI
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Reviews summary
Strategic planning for generative ai
According to students, this course offers a largely positive experience for those looking to understand the strategic aspects of generative AI. Learners commend its ability to provide a clear understanding of core concepts and terminology, making complex topics accessible. Many appreciate the practical steps for planning a generative AI project, highlighting its immediate applicability. The course effectively covers how to evaluate the risks and benefits associated with Gen AI initiatives. While some with technical backgrounds might find it a high-level overview, it's widely regarded as highly beneficial for project managers and strategic thinkers aiming to navigate the Gen AI landscape. The lectures are clear and well-structured, reflecting a high-quality learning experience by Amazon Web Services.
Geared towards strategic planning, not deep technical coding.
"As a project manager, I found the strategic focus perfect for my needs, not too technical."
"If you're looking for coding or deep dives into models, this course is more about project management and high-level concepts."
"I think it's better for those who need to understand how to plan and oversee a Gen AI project rather than build one."
Content is well-structured and easy to follow.
"The content provided by Amazon Web Services was well-organized and presented clearly."
"I found the course material to be very concise and to the point, making it easy to absorb."
"The lectures were straightforward and didn't get bogged down in jargon, which was a plus."
Comprehensive analysis of Gen AI risks and benefits.
"Understanding the risks and benefits of generative AI was crucial, and this course covered it well."
"The course helped me evaluate potential ethical and practical challenges effectively."
"I appreciated the balanced perspective on both the upsides and downsides of Gen AI adoption."
Excellent overview of Gen AI fundamentals and terminology.
"This course offered a really clear explanation of generative AI terminology and concepts."
"I finally feel like I understand the technical foundations of Gen AI without getting bogged down in code."
"It was great for grasping the key terms needed to discuss Gen AI projects effectively."
Provides actionable steps for planning Gen AI projects.
"I found the sections on planning a generative AI project to be highly practical and immediately applicable."
"The course clearly outlined the steps needed to initiate and manage a Gen AI initiative."
"It gave me a solid framework for approaching real-world Gen AI implementations."
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 Planning a Generative AI Project with these
activities:
Define Generative AI Concepts
Show steps
Solidify your understanding of the fundamental concepts and terminology used in generative AI.
Browse courses on
Generative AI
Show steps
-
Read course materials on generative AI fundamentals
-
Define key terms such as generative models, GANs, and VAEs
Warm up on Generative AI fundamentals
Show steps
Helps you refresh your knowledge of generative AI and its use cases.
Browse courses on
Generative AI
Show steps
Explore Generative AI Applications
Show steps
Expand your knowledge by exploring real-world applications of generative AI, such as image generation, text summarization, and music composition.
Browse courses on
Generative AI Applications
Show steps
-
Identify different industries and sectors where generative AI is used
-
Review case studies and examples of successful generative AI implementations
Three other activities
Expand to see all activities and additional details
Show all six activities
Use Generative AI tools on real-world datasets
Show steps
Practice using Generative AI tools on real-world datasets to gain hands-on experience.
Browse courses on
Generative AI Tools
Show steps
-
Identify a real-world dataset that is relevant to your project.
-
Select a Generative AI tool that is appropriate for the dataset.
-
Train the Generative AI model using the dataset.
-
Evaluate the performance of the model.
Discuss Generative AI Ethics
Show steps
Engage with peers to discuss the ethical implications of generative AI, such as bias, privacy, and potential misuse.
Browse courses on
Responsible AI
Show steps
-
Research and identify potential ethical concerns related to generative AI
-
Participate in group discussions to share perspectives and ideas
Build a Generative AI Model
Show steps
Apply your knowledge by building a simple generative AI model, such as a text generator or image synthesizer.
Browse courses on
Generative Models
Show steps
-
Choose a generative model type (e.g., GAN, VAE)
-
Gather and prepare training data
-
Implement the model architecture and training process
-
Evaluate and refine the model's performance
Define Generative AI Concepts
Show steps
Solidify your understanding of the fundamental concepts and terminology used in generative AI.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Read course materials on generative AI fundamentals
- Define key terms such as generative models, GANs, and VAEs
Warm up on Generative AI fundamentals
Show steps
Helps you refresh your knowledge of generative AI and its use cases.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
Explore Generative AI Applications
Show steps
Expand your knowledge by exploring real-world applications of generative AI, such as image generation, text summarization, and music composition.
Browse courses on
Generative AI Applications
Show steps
Show steps
Show steps
- Identify different industries and sectors where generative AI is used
- Review case studies and examples of successful generative AI implementations
Three other activities
Expand to see all activities and additional details
Show all six activities
Use Generative AI tools on real-world datasets
Show steps
Practice using Generative AI tools on real-world datasets to gain hands-on experience.
Browse courses on
Generative AI Tools
Show steps
Show steps
Show steps
- Identify a real-world dataset that is relevant to your project.
- Select a Generative AI tool that is appropriate for the dataset.
- Train the Generative AI model using the dataset.
- Evaluate the performance of the model.
Discuss Generative AI Ethics
Show steps
Engage with peers to discuss the ethical implications of generative AI, such as bias, privacy, and potential misuse.
Browse courses on
Responsible AI
Show steps
Show steps
Show steps
- Research and identify potential ethical concerns related to generative AI
- Participate in group discussions to share perspectives and ideas
Build a Generative AI Model
Show steps
Apply your knowledge by building a simple generative AI model, such as a text generator or image synthesizer.
Browse courses on
Generative Models
Show steps
Show steps
Show steps
- Choose a generative model type (e.g., GAN, VAE)
- Gather and prepare training data
- Implement the model architecture and training process
- Evaluate and refine the model's performance
Career center
Learners who complete Planning a Generative AI Project will develop knowledge and skills
that may be useful to these careers:
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers research, design, develop, deploy, and maintain artificial intelligence systems. Typically requiring at least a master's degree, AI Engineers may benefit from the foundational knowledge provided by a course like Planning a Generative AI Project. This course will help build a solid understanding of the technical foundations and key terminology related to generative artificial intelligence (AI).
Machine Learning Scientist
Machine Learning Scientist
Machine Learning Scientists research and develop new machine learning algorithms and techniques. Typically requiring a PhD, this role would benefit from a foundational course like Planning a Generative AI Project. This course would provide an introduction to generative AI and its potential applications.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers research, design, develop, deploy, and maintain machine learning systems. Typically requiring a master's degree, this role may benefit from the technical foundation provided by a course like Planning a Generative AI Project. Generative AI is a subset of machine learning, so this course would be particularly relevant to this role.
Data Architect
Data Architect
Data Architects design and implement data architectures for organizations. A course like Planning a Generative AI Project may be useful to Data Architects because generative AI can be used to generate synthetic data. This data can be used to test and train machine learning models.
Software Engineer
Software Engineer
Software Engineers apply engineering principles to design, develop, maintain, test, and evaluate computer software. A course like Planning a Generative AI Project may be useful to Software Engineers because generative AI can be used to generate code. This can save time and improve the quality of the code.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. A course like Planning a Generative AI Project may be useful to Product Managers because generative AI can be used to generate ideas for new products and to create prototypes.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical techniques to solve business problems. A course like Planning a Generative AI Project may be useful to Operations Research Analysts because generative AI can be used to generate data and insights that can help businesses make better decisions.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. A course like Planning a Generative AI Project may be useful to Quantitative Analysts because generative AI can be used to generate synthetic data. This data can be used to test and train financial models.
Data Scientist
Data Scientist
Data Scientists use many tools to extract knowledge from data. It is a multidisciplinary function that extracts actionable insights from raw data. A course like Planning a Generative AI Project may be useful because it will provide you with the knowledge to understand the technical foundations and key terminology related to generative artificial intelligence (AI). This would be helpful when carrying out data analysis and extracting business insights.
Business Analyst
Business Analyst
Business Analysts work with stakeholders to understand their business needs and develop solutions to improve their organizations. A course like Planning a Generative AI Project may be useful to Business Analysts because generative AI can be used to generate reports and insights that can help businesses make better decisions.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to understand customer behavior and develop marketing campaigns. A course like Planning a Generative AI Project may be useful to Marketing Analysts because generative AI can be used to generate content and insights that can help businesses reach their target audience.
Risk Manager
Risk Manager
Risk Managers identify, assess, and mitigate risks. A course like Planning a Generative AI Project may be useful to Risk Managers because generative AI can be used to generate scenarios and insights that can help businesses identify and mitigate risks.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain large-scale data systems. A course like Planning a Generative AI Project may be useful to Data Engineers because generative AI can be used to create synthetic data sets. These data sets are useful for testing and training machine learning models.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data to make investment recommendations. A course like Planning a Generative AI Project may be useful to Financial Analysts because generative AI can be used to generate financial data and insights that can help investors make better decisions.
User Experience Designer
User Experience Designer
User Experience Designers design and develop the user interface for websites and applications. A course like Planning a Generative AI Project may be useful to User Experience Designers because generative AI can be used to generate user interfaces and prototypes.
For more career information including salaries, visit:
OpenCourser.com/course/wrsmff/planning
Reading list
We've selected six 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
Planning a Generative AI Project.
Save
This textbook provides a comprehensive overview of deep learning, a fundamental technique used in generative AI. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks.
This classic textbook provides a comprehensive overview of reinforcement learning algorithms. It valuable resource for anyone interested in understanding the foundations of generative AI.
This textbook provides a comprehensive overview of statistical learning, a foundation for generative AI. It covers topics such as linear regression, logistic regression, and decision trees.
Provides a practical guide to machine learning using popular libraries such as Scikit-Learn, Keras, and TensorFlow. It valuable resource for anyone interested in applying generative AI in practice.
Save
Provides a comprehensive overview of computer vision, a field closely related to generative AI. It covers topics such as image formation, feature extraction, and object recognition.
Save
Provides a broader perspective on the development of AI, discussing its potential impact on society and the economy. It is written by Pedro Domingos, a leading researcher in the field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/wrsmff/planning
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