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This course introduces the notion of universality, whereby a large zoo of seemingly disparate systems can be described by the same theory. It introduces a powerful and widely applicable concept known as renormalization group which explains where this universality comes from. It introduces some paradigmatic frameworks underpinning condensed matter physics, including band structure and the quasiparticle concept. This course introduces two pillars of modern condensed matter physics. The first two modules introduce the renormalization group, which is the central paradigm of modern statistical physics, and has wide applicability across physics and beyond. The third and fourth modules introduce band theory, which is central to solid state physics, and uses it to explain metals and insulators.

We know the fundamental equations governing the motion of every atom in our brain and every electron in our computers - the motion of each and every atomic and subatomic particle on planet Earth can, in principle , be calculated from well understood physical laws. And yet, the natural world (and the behavior of humans and computers alike) continues to surprise us. This is because when large numbers of objects interact together, they can exhibit qualitatively new emergent phenomena , which are not obviously contained in the equations governing the motion of a single atom or electron. Condensed matter physics is the study of such emergent phenomena. Condensed matter physics is the largest subdiscipline of modern physics. It has generated a wealth of deep concepts that govern our fundamental understanding of the modern world, and which also underpin much of our modern technological society. This specialization provides an introduction to the key concepts underpinning modern condensed matter. These concepts apply widely, and enable a powerful and widely applicable understanding of emergent phenomena in complex systems. This specialization is aimed at individuals who are curious about what condensed matter physics is all about, and at individuals seeking ways of understanding the complex emergent phenomena using simple but powerful conceptual tools. Extensive prior knowledge of physics is not required. Applied learning project Students will practice applying key concepts from condensed matter physics to understanding paradigmatic phenomena in the natural world, such as magnetism and superconductivity. They will also explore applications of these concepts to other collective phenomena in the world around us, across a range of settings not limited to physics. Collapse

Computing systems and technologies have a fundamental impact on the lives of most people in the world, including how we communicate, access information, socialize, and receive health care. This course is the third of three that examines ethical issues in the design and implementation of computing systems and technologies, and reflects on the broader impact of computing on our society. It covers medical applications, the use of robotics, autonomous vehicles, and the future of work. This course can be taken for academic credit as part of CU Boulder's Master of Science in Computer Science program on Coursera. These fully accredited degrees offer targeted courses, short 8-week sessions, and tuition-based programs. Admission is based on three prerequisite courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder

Computing systems and technologies have a fundamental impact on the lives of most people in the world, including how we communicate, access information, socialize, and receive health care. This course is the second of three that examines the ethical issues in the design and implementation of computing systems and technologies, and reflects on the broader impact of computing on our society. It covers algorithmic bias in machine learning methods, professional ethics, and issues in the technologist's workplace. This course may be taken for academic credit toward CU Boulder's Master of Science in Computer Science program on Coursera. These fully accredited degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on three prerequisite courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder

Computing systems and technologies impact the lives of most people in the world and will do so even more in the future. This impact includes how we obtain information, how we communicate, how we obtain essential services such as health care and transportation, and much more. Computing also impacts our society in fundamental ways, including the impact of automation on the availability and types of employment, and how we organize and manage our society. This specialization examines some of the ethical issues in the design and implementation of current and future computing systems and technologies, and reflects on the broad impact of computing on our society. It draws on a wide range of sources and experiences, including recent events, media articles, and research, as well as the experiences of computing professionals. The course examines a wide range of applications of computing in areas such as algorithmic bias in artificial intelligence and machine learning, social media, security and privacy, healthcare, robotics and autonomous systems, the gender and race of the computing workforce, and the future of work. The primary goal of the course is to help students identify and resolve ethical situations that may arise in their careers and lives. This includes introducing students to a wide range of examples of ethical issues in computing, as well as an introduction to ethical frameworks that can be applied to analyze ethical issues. Applied learning project Throughout the specialization, students will work with articles published in computer ethics journals. These assignments will require students to carefully analyze articles, critically evaluate ethical principles, and reflect on the broader implications for society, technology, and individual decision making.

This introductory course provides a comprehensive examination of generative AI, including transformers, ChatGPT for text generation, and generative adversarial networks (GANs), a diffusion model for image generation. By the end of this course, you will have a basic understanding of these generative AI models, their underlying theories, and practical considerations. You will have built a solid foundation and be ready to delve into more advanced topics in the next course.

In this course, you'll explore modeling of dynamic systems and feedback control. The course begins with an introduction of control theory and the application of Laplace transforms in solving differential equations, providing a strong foundation in linearity, time-invariance, and dynamic system modeling. The following week will delve into the laws governing the modeling of dynamic systems, with a focus on deriving differential equations from fundamental principles like Newton's laws and Kirchhoff's laws, as well as mastering the representation of systems as transfer functions in the Laplace domain. The third week delves deeper into Laplace transforms, emphasizing initial/final value theorems, block diagram manipulation, and dynamic response analysis. Moving into the fourth week, you'll learn to analyze system performance using transient step response specifications, enabling you to assess and optimize system behavior effectively. Finally, in the fifth week, you'll explore Bounded-Input Bounded-Output (BIBO) stability and Routh's stability criterion, gaining the skills to assess, analyze, and design stable systems. By the course's end, you'll be well-equipped to navigate the intricacies of control systems and dynamic modeling.

This course gives an introduction to the biology and biochemistry necessary to understand genetic circuits. It starts by providing an engineering viewpoint on genetic circuit design and a review of cells and their structure. The second module introduces genetic parts and the importance of standards followed by a discussion of genetic devices used within circuit design. The last two modules cover experimental techniques and construction methods and principles applied during the design process.   This course can also be taken for academic credit as ECEA 5934, part of CU Boulder's Master of Science in Electrical Engineering.

This course continues our data structures and algorithms specialization by focusing on the use of linear and integer programming formulations for solving algorithmic problems that seek optimal solutions to problems arising from domains such as resource allocation, scheduling, task assignment, and variants of the traveling salesperson problem . Next, we will study algorithms for NP-hard problems whose solutions are guaranteed to be within some approximation factor of the best possible solutions. Such algorithms are often quite efficient and provide useful bounds on the optimal solutions. The learning will be supported by instructor provided notes, readings from textbooks and assignments. Assignments will include conceptual multiple-choice questions as well as problem solving assignments that will involve programming and testing algorithms. This course can be taken for academic credit as part of CU Boulder's Masters of Science in Computer Science (MS-CS) degrees offered on the Coursera platform. This fully accredited graduate degree offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder

This third course in the product development specialization discusses the business side of product development. The course begins with an overview of marketing and pricing strategies, and how the company's price their products today. Learners are then introduced to the project's financial business case, defining key financial metrics such as NPV, IRR and Payback Period. The course then shows how to make an effective presentation these to the executive office for funding. The course concludes with a discussion of sustainability and how to design innovative products for a circular economy. Throughout the course, the students are challenged to continue developing their own product idea, one they have followed throughout the specialization. This course can be taken for academic credit as part of CU Boulder's Master of Engineering in Engineering Management (ME-EM) degree offered on the Coursera platform. The ME-EM is designed to help engineers, scientists, and technical professionals move into leadership and management roles in the engineering and technical sectors. With performance-based admissions and no application process, the ME-EM is ideal for individuals with a broad range of undergraduate education and/or professional experience. Learn more about the ME-EM program at https://www.coursera.org/degrees/me-engineering-management-boulder.

Welcome to "Integrated and Strategic Communication Campaigns", the first course of the specialization, Strategic Communication Campaigns. Ever wanted to "get the word out" or create "buzz" for your organization? This course will leave you knowing how to deliver the right message to the right audience at the right time via the right channel. You will get started by understanding the best practices for communication campaigns and learning the basics around how to tell the story that represents your brand well. You will then be able to take that story to the right channels so that it gets told internally and externally from an organizational point of view. In the final week, you will take a closer look at communication campaigns from other brands to understand how paid, earned, shared, and owned media are used. By the end of this course, you will have encountered multiple examples and strategies for strategic communication campaigns that will have you feeling more confident about creating one on your own!

Welcome to "Understanding Campaign Components", the second course of the specialization, Strategic Communication Campaigns. In this course, you will learn how to design and develop a strategic communication campaign from start to finish. You will learn how to identify a brand's communication problem and create a solution by using strategic communication methods. You will then create your very own communication campaign, by employing tactics that take a brand's target audience, reputation, and available resources into consideration. In the third week you will put all the campaign components together, from conducting research to measuring assigned key performance indicators, which allow you to implement a holistic strategy that works for the given situation. In the final week, we will talk about how to monitor your campaign after implementation in order to create long-term success for your brand or organization and you will submit your final campaign plan for peers to review. This course could benefit anyone who needs to reach an audience with intentional messaging, and can increase your skillset in the areas of marketing, advertising or public relations.