Did you know that mastering Generative AI (GenAI) and selecting the right models can significantly enhance your projects and organization? Learn how to leverage advanced AI technologies to make informed decisions and optimize your workflows.
GenAI and Model Selection
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September 2024
1 assignment
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There are 4 modules in this course
Welcome to GenAI and Model Selection! This course empowers professionals like you to harness the transformative potential of Generative AI (GenAI) in optimizing organizational strategies. Imagine leveraging advanced AI models to make informed decisions, streamline workflows, and drive innovation within your organization.
What's included
1 video1 reading
In this lesson, you will gain a comprehensive understanding of GenAI models, their importance, and practical benefits. The lesson will cover foundational concepts, discussing the advantages for various roles and how these models enhance decision-making and efficiency. It provides an overview of Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformers, detailing their features, similarities, and differences. Practical examples, such as AI-generated faces, AI-assisted driving, and advanced natural language processing, will illustrate real-world applications, equipping learners to make informed decisions about model selection in their projects.
What's included
3 videos
This lesson provides you with a comprehensive guide to evaluating and selecting GenAI models. It begins with a video on key performance metrics, data requirements, and computational resources needed for GenAI models. Reading material offers an in-depth guide on these evaluation criteria. The next video discusses criteria for model selection based on project goals and compares different models. Learners will participate in a hands-on session to practice selecting the most suitable model for specific needs.
What's included
2 videos2 readings
This final lesson equips you with essential knowledge and skills for selecting and integrating generative AI models into existing systems. Starting with a comparison of building custom models versus purchasing pre-built solutions, you will explore key decision factors. The focus will then shift to effective integration guidelines for ensuring seamless performance and future adaptability. The lesson wraps up with additional resources for continued learning in generative AI integration, preparing learners to drive innovation and operational excellence in diverse settings.
What's included
2 videos2 readings1 assignment
Instructor
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Recommended if you're interested in Data Analysis
Fractal Analytics
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Coursera Instructor Network
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Frequently asked questions
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.