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Phil Gold

This course aims to empower general users with a friendly and non-technical understanding of Generative AI. It emphasizes the importance of transparency in AI systems, helping learners to comprehend how AI decisions are made.

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This course aims to empower general users with a friendly and non-technical understanding of Generative AI. It emphasizes the importance of transparency in AI systems, helping learners to comprehend how AI decisions are made.

By highlighting the importance of user awareness, transparency, and informed decision-making, learners will be better equipped to make informed choices and interact with AI responsibly and confidently. The strategies and insights provided will help learners explore the creative potential of Generative AI while ensuring ethical practices and safeguarding against potential risks.

The course encourages active participation and emphasizes the collective responsibility of users in shaping the future of AI.

This course is designed for any employee or manager of a business that is either using or contemplating using AI and Generative AI, or anyone seeking to enhance their knowledge of the subject. The course is designed to give students a plain-language basic understanding of the topic and some of the nuances of using AI.

There are no specific prerequisites for this course. A basic understanding of computers and business will be helpful, but not mandatory. An open mind and curiosity about the broader societal impact of AI will enhance the learning experience.

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Syllabus

User Awareness and Education for Generative AI
This course aims to empower general users with a friendly and non-technical understanding of Generative AI. It emphasizes the importance of transparency in AI systems, helping learners to comprehend how AI decisions are made. The course encourages active participation and emphasizes the collective responsibility of users in shaping the future of AI.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Examines the ethical and responsible use of Generative AI, empowering learners to make informed decisions
Designed for general users and business professionals, providing a non-technical understanding of Generative AI
Emphasizes transparency in AI systems, helping learners understand how decisions are made
Encourages active participation and collective responsibility in shaping the future of AI

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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 User Awareness and Education for Generative AI with these activities:
Review Key Concepts from Probability Theory
Brush up on fundamental statistical concepts to strengthen your foundation in Generative AI.
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Show steps
  • Read through notes from previous statistics courses or textbooks.
  • Solve practice problems to test your understanding of probability distributions, Bayesian inference, and hypothesis testing.
Review core computer science concepts
Prepare for success by reviewing prerequisite computer science skills.
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  • Review basic programming concepts such as variables, data types, and control structures.
  • Practice writing and executing simple C programs.
  • Revise fundamental data structures like arrays, linked lists, and stacks.
Seek guidance from experienced professionals in the field of Generative AI
Enhance your learning journey by connecting with experts who can provide valuable insights and support.
Show steps
  • Identify potential mentors through online platforms, industry events, or personal connections.
  • Reach out to mentors and express your interest in learning about Generative AI.
  • Schedule regular meetings or calls to receive guidance and advice.
Eight other activities
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Show all 11 activities
Participate in Generative AI Study Groups
Collaborate with peers to discuss and understand Generative AI concepts more deeply.
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Show steps
  • Join an online forum or study group dedicated to Generative AI.
  • Engage in discussions, share your insights, and seek clarification from other participants.
Explore Generative AI Platforms and Tools
Gain hands-on experience with Generative AI models and techniques.
Browse courses on Generative AI
Show steps
  • Choose a Generative AI platform (e.g., OpenAI, Google Cloud AI Platform) and create an account.
  • Follow tutorials to build and train Generative AI models for specific tasks (e.g., text generation, image synthesis).
Complete online tutorials on Generative AI
Gain hands-on experience and reinforce understanding by following structured tutorials.
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  • Identify suitable online tutorials covering Generative AI concepts and techniques.
  • Follow the tutorials step-by-step, completing all exercises and assignments.
  • Experiment with different Generative AI models and explore their capabilities.
Participate in online study groups focused on Generative AI
Engage with peers, share insights, and enhance understanding through collaborative learning.
Show steps
  • Identify or create an online study group for Generative AI.
  • Attend regular study sessions and actively participate in discussions.
  • Collaborate on projects and assignments within the group.
Compile a curated list of Generative AI resources
Expand your knowledge and stay up-to-date by compiling a comprehensive collection of Generative AI resources.
Show steps
  • Identify and collect relevant articles, tutorials, videos, and tools related to Generative AI.
  • Organize and categorize the resources for easy access.
  • Share the curated list with peers or online communities.
Develop a Generative AI Project
Apply your understanding to create a practical Generative AI project that solves a real-world problem.
Browse courses on Generative AI
Show steps
  • Define the problem you want to solve and gather relevant data.
  • Choose and train a Generative AI model that aligns with your project goals.
  • Evaluate your model's performance and refine it as needed.
Develop a presentation on a chosen Generative AI application
Deepen understanding and develop communication skills by creating a presentation on a specific Generative AI application.
Show steps
  • Research and select a specific Generative AI application of interest.
  • Gather information and examples to support the presentation.
  • Develop a clear and engaging presentation structure.
  • Practice delivering the presentation and incorporate feedback.
Participate in online hackathons or competitions related to Generative AI
Challenge yourself, test your skills, and gain valuable experience in applying Generative AI.
Show steps
  • Identify suitable online hackathons or competitions focused on Generative AI.
  • Form a team or collaborate with others.
  • Develop innovative solutions using Generative AI.

Career center

Learners who complete User Awareness and Education for Generative AI will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers build, deploy, and maintain machine learning models. Generative AI is a type of machine learning, so this course can help build a foundation for success as a Machine Learning Engineer. It empowers learners with a friendly and non-technical understanding of Generative AI and emphasizes the importance of transparency in AI systems
Marketing Manager
Marketing Managers develop and execute marketing campaigns. This course may be useful in providing a foundational understanding of Generative AI, as well as its potential risks and benefits. An understanding of AI can help inform decisions about marketing campaign development and execution.
Project Manager
Project Managers plan, execute, and close projects. This course may be useful in providing a foundational understanding of Generative AI, as well as its potential risks and benefits. An understanding of AI can help inform decisions about project planning, execution, and closing.
Sales Manager
Sales Managers lead and motivate sales teams. This course may be useful in providing a foundational understanding of Generative AI, as well as its potential risks and benefits. An understanding of AI can help inform decisions about sales team leadership and motivation.
Data Scientist
Data Scientists collect, analyze, and interpret data to help businesses make informed decisions. This course may be useful in providing a foundational understanding of Generative AI, as well as its potential risks and benefits. An understanding of AI can help inform decisions about data collection, analysis, and interpretation.
Business Analyst
Business Analysts help businesses identify and solve problems. This course may be useful in providing a foundational understanding of Generative AI, as well as its potential risks and benefits. An understanding of AI can help inform decisions about problem identification and solving.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course may be useful in providing a foundational understanding of Generative AI, as well as its potential risks and benefits. An understanding of AI can help inform decisions about software design, development, and maintenance.
Product Manager
Product Managers are responsible for the development and launch of new products. This course may be useful in providing a foundational understanding of Generative AI, as well as its potential risks and benefits. An understanding of AI can help inform decisions about product development and launch.
Operations Manager
Operations Managers plan and execute business operations. This course may be useful in providing a foundational understanding of Generative AI, as well as its potential risks and benefits. An understanding of AI can help inform decisions about business operations planning and execution.
Risk Manager
Risk Managers identify and mitigate risks to a business. This course may be useful in providing a foundational understanding of Generative AI, as well as its potential risks and benefits. An understanding of AI can help inform decisions about risk identification and mitigation.
Customer Success Manager
Customer Success Managers help customers achieve success with a product or service. This course may be useful in providing a foundational understanding of Generative AI, as well as its potential risks and benefits. An understanding of AI can help inform decisions about customer success management.
Compliance Manager
Compliance Managers ensure that a business complies with applicable laws and regulations. This course may be useful in providing a foundational understanding of Generative AI, as well as its potential risks and benefits. An understanding of AI can help inform decisions about compliance management.
Financial Manager
Financial Managers oversee the financial function of a business. This course may be useful in providing a foundational understanding of Generative AI, as well as its potential risks and benefits. An understanding of AI can help inform decisions about financial management.
Human Resources Manager
Human Resources Managers oversee the human resources function of a business. This course may be useful in providing a foundational understanding of Generative AI, as well as its potential risks and benefits. An understanding of AI can help inform decisions about human resources management.
AI Systems Engineer
An AI Systems Engineer designs, develops, and maintains AI systems. This course may be useful in providing a foundational understanding of Generative AI, as well as its potential risks and benefits. An understanding of AI can help inform decisions about system design and maintenance.

Reading list

We've selected eight 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 User Awareness and Education for Generative AI .
Explores the ethical implications of AI and provides a framework for developing AI systems that are fair, transparent, and accountable. It valuable resource for learners who want to understand the ethical challenges of AI and how to address them.
Provides a practical guide to building and deploying deep learning models with Fastai and PyTorch. It covers topics such as data preprocessing, model training, and model evaluation. It valuable resource for learners who want to gain hands-on experience with deep learning.
Discusses the future of AI, focusing on the potential for AI to solve some of the world's biggest problems. It also discusses the ethical challenges that need to be addressed as AI continues to develop.
Explores the potential of AI to revolutionize various industries and aspects of our lives. It also discusses the ethical challenges that need to be addressed as AI continues to develop.
Explores the potential risks and benefits of superintelligence, a hypothetical type of AI that is far more intelligent than humans. It discusses the importance of research on AI safety and the development of strategies to mitigate the risks of superintelligence.
Provides a non-technical introduction to the field of AI. It covers topics such as the history of AI, the different types of AI, and the potential applications of AI in various industries.

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