A Brief History of Humankind About the Course About 2 million years ago our human ancestors were insignificant animals living in a corner of Africa. Their impact on the world was no greater than that of gorillas, zebras, or chickens. Today humans are spread all over the world, and they are the most important animal around. This course will explain how we humans have conquered planet Earth, and how we have changed our environment, our societies, and our own bodies and minds. · We rule the world because we are the only animal that can believe in things that exist purely in our own imagination, such as gods, states, money and human rights. · Humans are ecological serial killers – even with stone-age tools, our ancestors wiped out half the planet's large terrestrial mammals well before the advent of agriculture. · The Agricultural Revolution was history’s biggest fraud – wheat domesticated Sapiens rather than the other way around. · Money is the most universal and pluralistic system of mutual trust ever devised. Part IV.
How to learn math About This Course You can now register for the current offering of this course. If you are interested in Jo Boaler's "How to Learn Math: For Students" course, the course is available here: How to Learn Math: For Students This course offers important new research ideas on learning, the brain, and math that can transform students’ experiences with math. The course is primarily for teachers and parents and others who may help students with math. It consists of short videos interspersed with various thinking tasks—such as reflecting on videos, designing lessons, discussing ideas with peers in the class—to promote active engagement. This course first ran last summer (June - Sep 2013) but will soon be re-opening and will run for an extended time, probably April-October. An accompanying student intervention course will be offered in similar months in the 2013-14 school year (May/June) and through the summer. Concepts 1. 2. 3. 4. 5. 6. 7. 8. Prerequisites There are no prerequisites for this course.
Introductory Human Physiology The goal of this course is to provide an introduction to human physiology. The students learn to recognize and explain the basic concepts that govern each organ and organ system and their integration to maintain homeostasis, as well as some clinical aspects of failure of these systems. The organ systems covered include: nervous, muscle, cardiovascular, respiratory, endocrine, male and female reproductive, gastrointestinal, and urinary. This human physiology course is targeted to undergraduate and graduate students with an elementary background in biology. Subtitles for all video lectures available in: English and Portuguese (provided by the Lemann Foundation) An high school background in biology. As a student enrolled in this course, you will have free access to selected chapters and content for the duration of the course. Other than course lecture notes, there are no outside readings/textbooks required. Introductory Human Physiology is a 12-week course.
Probabilistic Graphical Models About the Course What are Probabilistic Graphical Models? Uncertainty is unavoidable in real-world applications: we can almost never predict with certainty what will happen in the future, and even in the present and the past, many important aspects of the world are not observed with certainty. In this class, you will learn the basics of the PGM representation and how to construct them, using both human knowledge and machine learning techniques; you will also learn algorithms for using a PGM to reach conclusions about the world from limited and noisy evidence, and for making good decisions under uncertainty. Course Syllabus Topics covered include: There will be short weekly review quizzes and programming assignments (Octave/Matlab) focusing on case studies and applications of PGMs to real-world problems: To prepare for the class in advance, you may consider reading through the following sections of the textbook (discount code DKPGM12) by Daphne and Nir Friedman: Introduction and Overview.
Nutrition for Health Promotion and Disease Prevention Module 1: Introduction to Nutrition Science If you are what you eat, you should probably know something about how to eat! In this introductory module, you will learn about the field of nutrition science, the basics of nutrition research and some important terms that will set the stage for the remainder of the class. This module ends with a global look at meal planning guides and tools and provides you with an opportunity to determine your own individual nutrient needs. Module 2: Heart Disease Heart disease is the number one cause of death around the world. Module 3: Diabetes Globally, it is estimated that 438 million people – or roughly 8% of the world’s population – will have diabetes by 2030. Module 4: Cancer Diet and cancer are certainly linked; but the degree to which food intake impacts the development and progression of cancer is still not entirely understood. Module 5: Obesity and Weight Management Global statistics for obesity did not exist 50 years ago. Yes. Yes.
Coding the Matrix: Linear Algebra through Computer Science Applications About the Course When you take a digital photo with your phone or transform the image in Photoshop, when you play a video game or watch a movie with digital effects, when you do a web search or make a phone call, you are using technologies that build upon linear algebra. Linear algebra provides concepts that are crucial to many areas of computer science, including graphics, image processing, cryptography, machine learning, computer vision, optimization, graph algorithms, quantum computation, computational biology, information retrieval and web search. Linear algebra in turn is built on two basic elements, the matrix and the vector. In this class, you will learn the concepts and methods of linear algebra, and how to use them to think about problems arising in computer science. Recommended Background You should be an experienced programmer. You are not expected to have any background in linear algebra. Suggested Readings Coding the Matrix is an optional companion textbook.
Nutrition and Physical Activity for Health About the Course Over 65 percent of adults and over 30 percent of children meet the classification of being overweight or obese, and with this excess weight comes numerous health conditions that include heart disease, diabetes, cancer, musculoskeletal disorders, and even impairments in cognitive function. Because in most cases the core cause of obesity and its related health conditions is a poor quality of diet and lack of sufficient physical activity, it is no surprise that to reverse this health problem a foundation of proper nutrition and sufficient physical activity is imperative. This course is designed to provide a foundation of nutritional knowledge to develop a sustainable pattern of healthy eating. Ultimately, this information can only be of value if individuals understand how to engage in these healthy behaviors within their daily lives when they are faced with challenges and barriers. Course Syllabus There are no required textbooks for this course. Week 1: Recommended Background
Algorithms: Design and Analysis, Part 1 About the Course In this course you will learn several fundamental principles of algorithm design. You'll learn the divide-and-conquer design paradigm, with applications to fast sorting, searching, and multiplication. You'll learn several blazingly fast primitives for computing on graphs, such as how to compute connectivity information and shortest paths. Course Syllabus Week 1: Introduction. Week 2: Running time analysis of divide-and-conquer algorithms. Week 3: More on randomized algorithms and probability. Week 4: Graph primitives. Week 5: Dijkstra's shortest-path algorithm. Week 6: Further data structures. Recommended Background How to program in at least one programming language (like C, Java, or Python); and familiarity with proofs, including proofs by induction and by contradiction. Suggested Readings No specific textbook is required for the course. Course Format The class will consist of lecture videos, generally between 10 and 15 minutes in length.