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As generative AI advances, there is a growing need to learn how to use these powerful tools not only in our work, but in our everyday lives. Generative AI Essentials: Overview and Impact introduces students to large language models and generative AI tools like ChatGPT. In this course, you will learn the basic principles of generative AI, how to use AI ethically, its impact on authorship, and what regulation of generative AI might look like. This course brings together University of Michigan experts in communications technology, economics, artificial intelligence, natural language processing, architecture, and law to discuss the impact of generative AI on our current society and its implications for the future. This course is licensed under CC BY-SA 4.0, except for the course image.

Llama for Python Programmers is designed for programmers who want to leverage the Llama 2 large language model (LLM) and take advantage of the generative artificial intelligence (AI) revolution. In this course, you’ll learn how open-source LLMs can run on self-hosted hardware, made possible through techniques such as quantization by using the llama.cpp package. You’ll explore how Meta’s Llama 2 fits into the larger AI ecosystem, and how you can use it to develop Python-based LLM applications. Get hands-on skills using methods such as few-shot prompting and grammars to improve and constrain Llama 2 output, allowing you to get more robust data interchanges between Python application code and LLM inference. Lastly, gain insight into the different Llama 2 model variants, how they were trained, and how to interact with these models in Python. This course does not require a data science or statistics background. It is developed specifically for Python application developers who are interested in integrating generative AI, such as Llama 2, into their work.

Artificial intelligence (AI) and machine learning (ML) have the potential to increase diagnostic accuracy, decrease diagnostic errors, and improve patient outcomes. The Data Augmented, Technology Assisted Medical Decision Making (DATA-MD) course will teach you how to use AI to augment your diagnostic decision-making. The National Academy of Medicine (NAM) recommends ensuring that clinicians can effectively use technology - including AI - to improve the diagnostic process. To use these technologies effectively in your clinical practice, you will need to determine when use of AI is appropriate, interpret the outputs of AI, read medical literature about AI, and explain to patients the role that AI plays in their care. In this course, you’ll explore the ethical considerations and potential biases when making medical decisions informed by AI/ML-based technologies. DATA-MD is a one of a kind curriculum designed to provide an introduction to the use of AI in the diagnostic process. This course was created with the needs of medical students, residents, fellows, practicing physicians, advanced practice providers, and registered nurses in mind. Others, like educators, computer programmers, and data scientists, may also find value in the course. Continuing Medical Education Information: This activity is released for CME credit on 07/30/2024 and expires 06/31/2027. The University of Michigan Medical School is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. The University of Michigan Medical School designates this enduring material for a maximum of 3.5 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Dr. Cornelius James and Jessica Virzi, planner and co-planner for this educational activity, have no relevant financial relationship(s) with ineligible companies to disclose. Maggie Makar, Benjamin Li, and Nicholson Price, presenters of this educational activity, have no relevant financial relationship(s) with ineligible companies to disclose. Karandeep Singh, presenter for this educational activity, was a consultant for Flatiron Health. The relevant financial relationship listed for this individual has been mitigated. Cheri Breadon and Jessica Virzi are the coordinators for this activity. After this activity, participants will be able to - Use AI to augment your diagnostic clinical decision-making - Describe the strengths and limitations of AI/ML-based technology in the diagnostic process - Interpret statistical measures frequently used to evaluate the performance of ML models - Critically appraise studies that include AI/ML and determine the applicability of study results in clinical practice If you would like to earn CME credit for participating in this course, please review the information, including expected results, presenters, their disclosures, and CME credit at this website prior to beginning the activity: https://umich.cloud-cme.com/course/courseoverview?P=0&EID=61826

Creative Coding for Designers Using Python,marks the final installment in the comprehensive three-course specialization, aimed at significantly enhancing the programming capabilities of designers, artists, and visual thinkers through Python. As the advanced course in the series, Creative Coding for Designers Using Python adopts a project-based learning strategy to consolidate and apply the skills acquired from the first two courses. In this course, you’ll focus on dynamic simulations and procedural content generation, offering a deeper dive into Python's application in visual design and digital art. Designed for individuals who have grasped the basics of Python, including its syntax, data structures, and object-oriented programming principles, this course delves into sophisticated topics. Leveraging the Processing platform with Python, you’ll engage in interactive projects that transform theoretical knowledge into tangible outputs, bridging the gap between technical proficiency and artistic creativity. Creative Coding for Designers Using Python is structured as an educational journey that combines technology and art, equipping participants with the skills to explore advanced digital design techniques. This course offers the tools and conceptual understanding necessary for the innovative application of Python in creating digital art and design projects. This is the third and final course in a three-part series, Programming for Designers, aimed at equipping designers with essential computational design skills.

In Data Structures for Designers Using Python, you’ll delve into the critical concepts of data structures and object-oriented programming, tailored specifically for design and visual content creation applications. You’ll be introduced to object-oriented programming principles in Python, enabling you to model real-world scenarios and design problems using objects and classes. You will use the Processing platform to draw lines, rectangles, ellipses, and more through the program’s Python mode. Learn about vector math and how it can be manipulated to store, organize, and manage data efficiently in creative projects. These approaches to Python allow you to gain a deeper understanding of the programming language while enhancing your ability to conceptualize and implement sophisticated design solutions. This is the second course in a three-part series, Programming for Designers, aimed at equipping designers, including those in architecture, graphic design, industrial design, game design, and visual artists, with essential computational design skills.

Python Fundamentals for Designers is an introduction to programming using Python meant for students interested in how programming is applied to visual applications and design. The course introduces the foundations of programming through a visual and dynamic learning environment. You’ll cover the essential building blocks of Python programming, from basic syntax and data types to more advanced concepts like control structures, functions, and inputs/outputs. Learn to build shapes and designs while implementing data structures that allow room for more complexity and depth within your projects. By the end of the course, you’ll be able to create dynamic and organic visual effects using the Processing platform with Python. This is the first course in a three-part series, Programming for Designers, aimed at equipping designers with essential computational design skills.

Healthy sleep is essential to good physical and mental health. If you or someone you know has ever struggled with sleep, daytime alertness, or has recently been diagnosed with a sleep disorder, From Sleep Disorders to Sleep Health can be a helpful guide. In this course, you’ll explore the importance of sleep and the barriers that can prevent effective sleep. You will learn how sleep needs, functions, and vulnerabilities can differ dramatically across the human lifespan, from childhood to adulthood. Take a closer look at how specific sleep problems affect diverse populations as defined by gender, race, ethnicity, environment, or common health conditions. Finally, you’ll examine the main types of sleep disorders, from symptoms and testing to diagnosis and treatment. From Sleep Disorders to Sleep Health should appeal to anyone interested in sleep as one of the main pillars of health and wellness, providing insight into one of the most prominent aspects of our lives.

How to Describe Data examines the use of data in our everyday lives, giving you the ability to assess the usefulness and relevance of the information you encounter. In this course, learn about uncertainty’s role in measurements and how you can develop a critical eye toward evaluating statistical information in places like headlines, advertisements, and research. You’ll learn the fundamentals of discussing, evaluating, and presenting a wide range of data sets, as well as how data helps us make sense of the world. This is a broad overview of statistics and is designed for those with no previous experience in data analysis. With this course, you’ll be able to spot potentially misleading statistics and better interpret claims about data you encounter in the world. Course assessments focus on your understanding of concepts rather than solving math problems. This is the first course in Understanding Data: Navigating Statistics, Science, and AI Specialization, where you’ll gain a core foundation for statistical and data literacy and gain an understanding of the data we encounter in our everyday lives.

How Science Turns Data Into Knowledge teaches you how to evaluate scientific claims critically, address experimental limitations, and recognize the roles of trust and responsibility within research. During the course, you’ll explore the nuances of significance testing, scientific research methods, and science communication, emphasizing the importance of carefully interpreting statistical results. After learning about the scientific process, you’ll learn how science can make its way into the news cycle—and how critical context can be lost amidst the noise. By the end of the course, you’ll be able to think more critically about the media you consume and how you can view science news and information with a more nuanced perspective. This is the second course in Understanding Data: Navigating Statistics, Science, and AI Specialization, in which you’ll gain a core foundation for statistical and data literacy and gain an understanding of the data we encounter in our everyday lives.

While our world is becoming increasingly interconnected, people report increasing anxiety, depression, and loneliness. With “Mindfulness, Dignity, and the Art of Human Connection,” you’ll explore innovative mindfulness techniques that foster a more profound understanding of dignity within yourself and others. This course provides a comprehensive understanding of the holistic mindfulness perspective, which focuses on strengthening your relationships with the self, others, and nature. It covers mindfulness from three perspectives: Buddhist psychology, critical theory, and contemplative studies. This interdisciplinary approach allows you to not only learn major aspects of the Banyan Tree mindset framework but also provides an inclusive perspective that builds a greater sense of understanding for others with diverse experiences. The course explores current research on mindfulness and offers various contemplative activities such as meditation, art, poetry, photovoice, and journaling to practice mindfulness. By developing a vision for leading a dignified life, you’ll strengthen your grasp on how to integrate mindfulness practices into your daily life and better understand the world around you.

Leveraging Generative AI for Social Impact Organizations addresses the resource constraints that social impact organizations commonly face and how generative AI tools can help free up limited staff capacity from routine administrative tasks. Social impact organizations often find themselves overwhelmed by constantly responding to routine inquiries, managing data and documentation, and other core functions that limit their ability to fully devote time to core programs and service delivery. In this course, you’ll learn specific examples of how AI can improve efficiency in areas such as automatically answering frequently asked questions, transforming information requests into digestible reports, or writing, designing, and distributing communications materials. Gain insight into key opportunities to use AI to expand your organization’s capacity for mission-critical activities. The course also explores the limitations and ethical implications of using generative AI versus human judgment and the nuances of social programming interactions.

In Generative AI: Governance, Policy, and Emerging Regulation, you will discuss governance issues for generative artificial intelligence (AI) systems deployed within an organization and explore data management practices, transparency methods, risk and impact assessments, and governance approaches to ensure responsible development and deployment of generative AI. The course also provides an overview of the current generative AI policy and regulatory framework in the United States, the European Union, and the G7. By examining governance issues and the current regulatory landscape for AI, you will gain a deeper understanding of how to integrate, manage, and govern AI within your organization.