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University of California, Davis

AI for Knowledge Workers

Sadie St. Lawrence

Instructor: Sadie St. Lawrence

7,383 already enrolled

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Gain insight into a topic and learn the fundamentals.

190 reviews

Beginner level
No prior experience required
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.

190 reviews

Beginner level
No prior experience required
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

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Build your subject-matter expertise

This course is part of the Working Smarter with AI Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

Welcome to Module 1! In this module, you’ll explore the broad field of artificial intelligence (AI) and learn key terms and concepts related to machine learning, deep learning, and generative AI. You’ll examine how machine learning differs from traditional programming and discover how deep learning builds on machine learning techniques to solve more complex problems. By the end of this module, you’ll identify the main characteristics and applications of generative AI and gain a foundational understanding of how AI technologies are used in real-world settings. We have a lot to cover, so let's get started on this exciting topic!

What's included

8 videos2 readings1 assignment2 discussion prompts

Welcome to Module 2! In this module, we’ll begin by discussing the importance of checking for approved AI tools or policies in the workplace, initial steps to start using AI tools, and the prerequisites and resources needed for using those tools. You’ll gain insights into common challenges but also best practices for overcoming them when adapting AI tools in a professional setting. We’ll discuss the distinction between creative and critical thinking tasks supported by GenAI, and identify practical applications of GenAI in both creative and analytical domains. Finally, you’ll develop essential prompting skills by learning different prompting techniques and styles, as well as when and how to apply them to achieve more accurate, useful, and effective AI-generated results. By the end of this module, you’ll be better prepared to use AI tools confidently and strategically in professional settings. Let's get started!

What's included

12 videos2 readings2 assignments1 discussion prompt

Welcome to Module 3! In this module, you’ll explore how generative AI can support both critical and creative thinking in professional settings. Through demonstrations and real-world scenarios, you’ll examine how different types of knowledge workers use GenAI tools to enhance productivity, problem-solving, and innovation.Welcome to Module 3! In this module, you’ll explore how generative AI can support both critical and creative thinking in professional settings. Through demonstrations and real-world scenarios, you’ll examine how different types of knowledge workers use GenAI tools to enhance productivity, problem-solving, and innovation. You’ll learn how creative and analytical tasks can be supported by GenAI, evaluate common challenges associated with AI adoption, and explore practical strategies for selecting the right AI tools based on specific task needs. By the end of the module, you’ll better understand the role of GenAI in knowledge work and develop a mindset of experimentation and thoughtful AI integration. Let’s get started!

What's included

15 videos1 assignment2 discussion prompts

Welcome to the final module! In this module, we have some important topics to discuss regarding safety considerations when using AI and expanding your learning. We’ll explore key limitations and challenges of AI. You’ll learn how to use AI ethically and safely, and we’ll discuss practical concerns related to current AI models and their applications. You’ll comprehend the implications of AI’s lack of transparency and explainability then identify privacy and security risks associated with sensitive data in AI. We’ll discuss sources and manifestations of bias in AI systems and assess strategies to identify, report, and address algorithmic bias and explore methods to promote ethical considerations, fairness, and inclusivity in AI. We’ll then assess improvements made in AI training to reduce hallucinations. You’ll also learn about explainability in AI and its importance in decision-making processes. Finally, we’ll explore the future of work and methods for adapting to AI advancements and find reliable sources of information about AI tools and updates. Let's finish strong!

What's included

10 videos2 readings1 assignment3 discussion prompts

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Instructor

Instructor ratings
(58 ratings)
Sadie St. Lawrence
University of California, Davis
4 Courses735,779 learners

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