Courses

Observe the thought process of a computer science professor as he codes a project from scratch in this 13-hour video. Follow along as Radu Mariescu-Istodor, a PhD in computer science, demonstrates real-time problem-solving and decision-making while building an interactive avatar system. Learn about canvas setup, procedural drawing, image processing, particle systems, linear algebra, and real-time face tracking. Watch as Radu tackles challenges like head rotation, dynamic hair simulation, and facial feature recognition without referencing external resources. Gain insights into code refactoring, debugging techniques, and the iterative nature of software development. This comprehensive coding session covers everything from initial planning to final testing, providing a unique opportunity to understand the mindset and approach of an experienced computer scientist.

Explore a comprehensive 14-hour course on nutrition, health science, and pharmacognosy. Learn to plan and evaluate nutritional quality of diets, understand the principles of healthy living, and delve into the world of herbal medicine. Discover the scope of pharmacognosy, classification of crude drugs, and methods for evaluating herbal medicines. Examine the achievements and challenges of women in science, and study human anatomy and physiology, including the circulatory, respiratory, digestive, and skeletal systems. Investigate the effects of exercise on various body systems and gain a deeper understanding of cell and tissue biology.

Explore urban data science applications in this comprehensive lecture by Professor Cecilia Mascolo from the University of Cambridge. Delve into human mobility modeling, mobile and sensor systems, and spatio-temporal data analysis. Learn about innovative research on interpreting and inferring mobile and wearable sensor data efficiently on devices, while respecting fine-grained spatial and temporal granularity. Discover how this interdisciplinary field impacts urban planning, mobile health, and organizational analytics. Examine concepts such as co-location coefficient, geographic and mobility features of areas, and urban growth patterns. Investigate the impact of new places on urban development, data-driven policy making, and the effects on London boroughs. Analyze geo-social interconnected networks, place social brokerage, and the relationship between diversity and deprivation. Explore taxi price comparisons, app adoption patterns, and user complaints. Gain insights into urban mobility models, including Samuel A. Stouffer's work, the importance of density, and rank universality. Conclude with a simulation demonstrating a new model for urban mobility, providing a comprehensive overview of cutting-edge urban data science applications.

This course is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well as training and application of neural networks applied on real-world medical scenarios. We cover deep learning (DL) methods, healthcare data and applications using DL methods. The courses include activities such as video lectures, self guided programming labs, homework assignments (both written and programming), and a large project. The first phase of the course will include video lectures on different DL and health applications topics, self-guided labs and multiple homework assignments. In this phase, you will build up your knowledge and experience in developing practical deep learning models on healthcare data. The second phase of the course will be a large project that can lead to a technical report and functioning demo of the deep learning models for addressing some specific healthcare problems. We expect the best projects can potentially lead to scientific publications.

In this capstone course, you will demonstrate your independence by applying the knowledge and skills acquired from the previous four courses to a real-world health data science challenge. Unlike earlier modules with structured guidance, this project provides minimal instructions, encouraging you to think critically and work autonomously. A hackathon style learning example will enable you to work closely with your peers throughout the journey. You will compile a portfolio showcasing your ability to translate research questions into analytical workflows, conduct rigorous data analysis, and develop computational solutions. This approach mirrors real-world health data science scenarios, preparing you to navigate complex challenges with confidence and expertise.

This course introduces important topics related to health in daily-life including the effect of environment, nutrition, and genetics on health, healthy aging, and mental and physical well-being. Biotechnology innovations and lifestyle modifications that can impact human health will be presented with the underlying scientific basis provided. The course will be taught from a health science perspective. Students will also participate in educational activities related to health sciences that illustrate and enforce the concepts learned in class. These will include a virtual laboratory tours, virtual visits to restaurants, and exercise videos. The course content includes instructional videos which have been designed specifically for this course. After the course, students should be able to understand how factors affect their health, design interventions and lifestyle modifications to improve their health and well-being, and finally to have tools to be able to implement changes that will lead to a longer and healthier life.

This course introduces important topics related to health in daily-life including the effect of environment, nutrition, and genetics on health, healthy aging, and mental and physical well-being. Biotechnology innovations and lifestyle modifications that can impact human health will be presented with the underlying scientific basis provided. The course will be taught from a health science perspective. Students will also participate in educational activities related to health sciences that illustrate and enforce the concepts learned in class. These will include a virtual laboratory tours, virtual visits to restaurants, and exercise videos. The course content includes instructional videos which have been designed specifically for this course. After the course, students should be able to understand how factors affect their health, design interventions and lifestyle modifications to improve their health and well-being, and finally to have tools to be able to implement changes that will lead to a longer and healthier life.

Improve your ability to take and pass the CSET: Health Science exam by exploring the study resources in this entertaining CSET: Health Science course. Review fun lessons to strengthen your knowledge and take practice quizzes and exams to check your comprehension before exam day.

Explore a comprehensive two-day workshop focused on leveraging graph technology in healthcare and life sciences. Dive into the power of connecting complex data for improved target discovery, drug safety evaluation, and clinical decision-making. Learn how to map common data models, build web applications, and analyze multi-omics data using Neo4j. Discover real-world case studies on pneumonia therapy response, cancer research, and bacterial genome analysis. Gain insights into advanced machine learning techniques, knowledge reconstruction platforms, and clinical proteomics frameworks. Engage with experts in the field and participate in panel discussions to deepen your understanding of graph databases in healthcare and life sciences applications.

Find out how you can use Python programming in the context of health care and health science.

Explore the challenges and opportunities of applying machine learning beyond the tech industry in this 58-minute lecture by Professor David Dunson from Duke University. Delve into the fundamental differences between tech applications and those in science and policy-making, examining why popular algorithms like deep learning may fail in other domains. Learn about the potential pitfalls of naively applying off-the-shelf ML algorithms in criminal justice, neuroscience, policy-making, and healthcare. Discover the importance of developing targeted methods that address selection bias, uncertainty quantification, limited training data, and complex observations. Focus on two specific problems: removing sensitive variable influence for fair predictive algorithms and creating interpretable models of human traits based on brain connection structure. Gain insights into Bayesian statistical theory, dimensionality reduction, and nonparametric approaches for high-dimensional and complex data across various disciplines.

Explore mental health challenges and strategies in planetary science through this recorded professional development seminar. Gain insights from Dr. David Trang's survey results highlighting issues faced by the planetary science community. Learn practical techniques for cultivating gratitude and appreciation towards oneself, colleagues, and the broader scientific field. Access downloadable slides and chat entries to supplement the 70-minute presentation, which was part of the Lunar and Planetary Institute's Professional Development Seminar Series recorded on September 17, 2024.

Explore five common misconceptions about human health in this informative 13-minute video from SciShow hosted by Stefan Chin. Debunk popular myths including whether soy consumption affects masculinity and if sunscreen is harmful to your health. Learn the scientific facts behind these widespread misunderstandings and discover what research actually reveals about these topics. The video provides evidence-based explanations to counter misinformation, helping viewers separate health science facts from fiction. Perfect for anyone interested in understanding the truth behind popular health claims that circulate in media and conversation.

In Data Science for Health Research, learn to organize and visualize health data using statistical analysis in programs like R. Explore how to translate data, interpret statistical models, and predict outcomes to help make data-informed decisions within the public health field.

Fundamentals of pharmacology for nursing and health science students and professionals. What you'll learn: Understand foundational pharmacology concepts essential for safe and effective medication administration in clinical practice.Identify how medications influence physiological and pathophysiological processes across different body systems.Explain considerations and implications of medication use and administration across the lifespan.Identify the classifications and actions of antimicrobial and anti-infective medications.Identify the classifications and actions of autonomic nervous system medications.Identify the classifications and actions of respiratory medications.Identify the classifications and actions of cardiovascular and renal system medications.Identify the classifications and actions of medications regulating gastrointestinal elimination.Identify the classifications and actions of medications used to regulate the central nervous system (CNS), mood, and cognition.Identify the classifications and actions of endocrine system medications.Identify the classifications and actions of medications related to pain and mobility. This course is tailored to meet the needs of nursing students, nursing professionals, allied health professionals, and students in the health sciences, including those preparing for the NCLEX, as well as pre-pharmacy and pre-medical students. Whether you’re just beginning your healthcare journey or looking to deepen your understanding of medications, this course offers a comprehensive yet accessible approach to pharmacology. We’ll cover high-yield, essential concepts like pharmacokinetics, pharmacodynamics, and safe medication administration, while exploring how these principles relate to the body's systems, including the nervous, cardiovascular, respiratory, gastrointestinal, and endocrine systems. You’ll also gain a deeper understanding of medications used for common disease states. This course is designed to help you make critical connections between physiology, pathophysiology, and the therapeutic use of medications. To support your learning, we've included a range of study tools, including detailed articles, cheat sheets, quizzes, and links to additional resources. These materials are crafted to help you solidify your knowledge and provide quick references for key pharmacological concepts. Our focus on real-world clinical scenarios and critical thinking will prepare you to excel in your studies, clinical practice, and on exams like the NCLEX. Join us to build a strong foundation in pharmacology and elevate your healthcare expertise!

Master the fundamental components of advanced literature searching in the health sciences. Informationist Mark MacEachern and a team of fellow health sciences informationists at the University of Michigan designed this course for anyone responsible for constructing literature searches as part of their research. This course will specifically help professionals and researchers in the health sciences improve the overall quality and reporting of their literature searches. After completing the course, you will better understand the importance of literature searches in health sciences work, the components of effective searches, and best practices to sufficiently report the search process. All learners who rely heavily on past research in their project work – regardless of their experience or current competence – will benefit from this practical learning experience.

Tackle three challenging integrals using first-year calculus integration techniques in this 24-minute video. Learn how to apply double integration by parts, u-substitutions, conjugates, and trigonometric substitutions to solve complex problems. Follow along as Dr. Trefor Bazett demonstrates step-by-step solutions, offering insights into recognizing and overcoming disguised integration challenges. Gain valuable practice in advanced integration methods and improve your problem-solving skills for calculus exams and real-world applications.

Amy Kilbourne, PhD, MPH Associate Chair for Research Professor of Learning Health Sciences Director, Quality Enhancement Research Initiative (QUERI) U.S. Department of Veterans Affairs Faculty, U-M Institute for Healthcare Policy and Innovation (IHPI)

This course explores key concepts and methods in Health Economics and Health Technology Assessment (HTA) and is intended for learners who have a foundation in data science, clinical science, regulatory and are new to this field and would like to understand basic principles used by payers for their reimbursement decisions.

Want to be one of the first to discover the emerging area of implementation science? Develop problem-solving and analytical skills reflecting the trans-disciplinary nature of global health.