Data Analysis About the Course You have probably heard that this is the era of “Big Data”. Stories about companies or scientists using data to recommend movies, discover who is pregnant based on credit card receipts, or confirm the existence of the Higgs Boson regularly appear in Forbes, the Economist, the Wall Street Journal, and The New York Times. But how does one turn data into this type of insight? The answer is data analysis and applied statistics. Data analysis is the process of finding the right data to answer your question, understanding the processes underlying the data, discovering the important patterns in the data, and then communicating your results to have the biggest possible impact. This course is an applied statistics course focusing on data analysis. Recommended Background Some familiarity with the R statistical programming language ( and proficiency in writing in English will be useful. Course Format
Introduction to Sociology About the Course We live in a world that is changing very quickly. Sociology gives us the tools to understand our own lives and those quite remote from us. We will strive to understand how interaction in micro-level contexts affects larger social processes and how such macro-level processes influence our day to day lives. Course Syllabus Week 1: The Sociological Imagination Week 2: Three Sociological Questions Week 3: Methods of Sociological Research Week 4: Us and Them Week 5: Isolation, Groups, and Networks Week 6: Cities Week 7: Social Interaction and Everyday Life Recommended Background None; all are welcome. Suggested Readings All assigned readings are open source materials which can be found through the web. and Introduction to Sociology (Eighth Edition) (both with Anthony Giddens, Richard P. Course Format Each week, there will be two sessions. Does Princeton award credentials or reports regarding my work in this course?
social defined networking About the Course This course introduces software defined networking, an emerging paradigm in computer networking that allows a logically centralized software program to control the behavior of an entire network. Separating a network's control logic from the underlying physical routers and switches that forward traffic allows network operators to write high-level control programs that specify the behavior of an entire network, in contrast to conventional networks, whereby network operators must codify functionality in terms of low-level device configuration. Logically centralized network control makes it possible for operators to specify more complex tasks that involve integrating many disjoint network functions (e.g., security, resource control, prioritization) into a single control framework, allowing network operators to create more sophisticated policies, and making network configurations easier to configure, manage, troubleshoot, and debug. Course Syllabus Module 3: Control Plane Prof.
Design: Creation of Artifacts in Society About the Course This is a course aimed at making you a better designer. The course marries theory and practice, as both are valuable in improving design performance. Lectures and readings will lay out the fundamental concepts that underpin design as a human activity. Weekly design challenges test your ability to apply those ideas to solve real problems. Student Testimonials from Earlier Sessions of the Course:"An amazing course - a joy to take. "When I signed up for this course I didn't know what to expect; the experience was so good and rewarding. See examples of student projects: here Recommended Background No specific background is required. Suggested Readings To get a feel for the style of the instructor and the material in the course, this book is a good place to start: Ulrich, K.T. 2010. The free digital book is available at Design: Creation of Artifacts in Society. Other highly recommended reading is the textbook: Product Design and Development by Karl T. Course Format
social network analysis About the Course Everything is connected: people, information, events and places, all the more so with the advent of online social media. A practical way of making sense of the tangle of connections is to analyze them as networks. In this course you will learn about the structure and evolution of networks, drawing on knowledge from disciplines as diverse as sociology, mathematics, computer science, economics, and physics. Online interactive demonstrations and hands-on analysis of real-world data sets will focus on a range of tasks: from identifying important nodes in the network, to detecting communities, to tracing information diffusion and opinion formation. Course Syllabus Week 1: What are networks and what use is it to study them? Concepts: nodes, edges, adjacency matrix, one and two-mode networks, node degree Activity: Upload a social network (e.g. your Facebook social network into Gephi and visualize it ). Week 2: Random network models: Erdos-Renyi and Barabasi-Albert Week 4: Community
Organizational Analysis About the Course Best MBA Mooc in 2013 as per review in the Financial Times! "The best [MBA Mooc] was Organizational Analysis taught by Stanford's Dan McFarland" - Philip D. Broughton MBA It is hard to imagine living in modern society without participating in or interacting with organizations. Each case is full of details and complexity. Through this self-paced course you will come to see that there is nothing more practical than a good theory. Join your future classmates and course alumni on Facebook! Course Syllabus Module 1: Introduction Module 2: Decisions by rational and rule-based procedures Module 3: Decisions by dominant coalitions Module 4: Decisions in organized anarchies Module 5: Developing organizational learning and intelligence Module 6: Developing an organizational culture Module 7: Managing resource dependencies Module 8: Network forms of organization Module 9: Institutions and organizational legitimacy Module 10: Summary Suggested Readings Course Format
Malicious Software and its Underground Economy: Two Sides to Every Story Cybercrime has become both more widespread and harder to battle. Researchers and anecdotal experience show that the cybercrime scene is becoming increasingly organized and consolidated, with strong links also to traditional criminal networks. Modern attacks are indeed stealthy and often profit oriented. Malicious software (malware) is the traditional way in which cybercriminals infect user and enterprise hosts to gain access to their private, financial, and intellectual property data. Once stolen, such information can enable more sophisticated attacks, generate illegal revenue, and allow for cyber-espionage. By mixing a practical, hands-on approach with the theory and techniques behind the scene, the course discusses the current academic and underground research in the field, trying to answer the foremost question about malware and underground economy, namely, "Should we care?".
Model Thinking This course will consist of twenty sections. As the course proceeds, I will fill in the descriptions of the topics and put in readings. Section 1: Introduction: Why Model? In these lectures, I describe some of the reasons why a person would want to take a modeling course. To be an intelligent citizen of the worldTo be a clearer thinkerTo understand and use dataTo better decide, strategize, and design There are two readings for this section. The Model Thinker: Prologue, Introduction and Chapter 1 Why Model? Section 2: Sorting and Peer Effects We now jump directly into some models. In this second section, I show a computational version of Schelling's Segregation Model using NetLogo. NetLogo The Schelling Model that I use can be found by clicking on the "File" tab, then going to "Models Library". The readings for this section include some brief notes on Schelling's model and then the academic papers of Granovetter and Miller and Page. Notes on Schelling Granovetter Model Miller and Page Model
Introduction to Sustainability About the Course This course introduces the academic approach of Sustainability and explores how today’s human societies can endure in the face of global change, ecosystem degradation and resource limitations. The course focuses on key knowledge areas of sustainability theory and practice, including population, ecosystems, global change, energy, agriculture, water, environmental economics and policy, ethics, and cultural history. This subject is of vital importance, seeking as it does to uncover the principles of the long-term welfare of all the peoples of the planet. As sustainability is a cross-disciplinary field of study, this foundation requires intellectual breadth: as I describe it in the class text, understanding our motivations requires the humanities, measuring the challenges of sustainability requires knowledge of the sciences (both natural and social), and building solutions requires technical insight into systems (such as provided by engineering, planning, and management).