OIDD1010 - Introduction To Oidd (Course Syllabus)
OIDD 101 explores a variety of common quantitative modeling problems that arise frequently in business settings, and discusses how they can be formally modeled and solved with a combination of business insight and computer-based tools. The key topics covered include capacity management, service operations, inventory control, structured decision making, constrained optimization and simulation. This course teaches how to model complex business situations and how to master tools to improve business performance. The goal is to provide a set of foundational skills useful for future coursework atWharton as well as providing an overview of problems and techniques that characterize disciplines that comprise Operations and Information Management.
OIDD1050 - Analytics in Excel Vba (Course Syllabus)
This course introduces the construction and use of data analysis tools that are commonly used for business analysis. The course builds on the spreadsheet and analytical skills developed in OIDD1010, providing a much more extensive treatment of spreadsheet application development (using Excel Visual Basic for Applications). In addition, we will cover best practices in programming and analytics generally which can carry over to other tools and languages. Time permitting, we will do an introduction to some advanced analytical methods that show up in complex data analysis tasks and provide a foundation for further study. In prior years, this course was a 1 cu offering combining the content described here with the content of what is now OIDD3150: Databases for Analytics (0.5 cu). Students seeking this experience can take this course along with OIDD3150 either sequentially or concurrently.
OIDD2000 - Grit Lab (Course Syllabus)
At the heart of this course are cutting-edge scientific discoveries about passion and perseverance for long-term goals. As in any other undergraduate course, you will learn things you didn't know before. But unlike most courses, Grit Lab requires you to apply what you've learned in your daily life, to reflect, and then to teach what you've learned to younger students. The ultimate aim of Grit Lab is to empower you to achieve your personal, long-term goals--so that you can help other people achieve the goals that are meaningful to them. LEARN -> EXPERIMENT -> REFLECT -> TEACH. The first half of this course is about passion. During this eight-week period, you'll identify a project that piques your interest and resonates with your values. This can be a new project or, just as likely, a sport, hobby, musical instrument, or academic field you're already pursuing. The second half of this course is about perseverance. During this eight-week period, your aim is to develop resilience, a challenge-seeking orientation, and the habits of practice that improve skill in any domain. By the end of Grit Lab, you will understand and apply, both for your benefit and the benefit of younger students, key findings in the emerging science on grit.
OIDD2010 - Tech Mgmt, Info & D Econ (Course Syllabus)
OIDD2010 introduces students to two critically important and tightly linked concepts. The first is online business model innovation, including key opportunities to exploit information-based strategies in businesses as diverse as Capital One and Uber (newly vulnerable markets) and Amazon and Airbnb (online channel conflict). The second is computer-based simulation modeling to assess the viability of an online innovation, the strategies for its launch, and its economic value.
OIDD2100 - Online Business Models (Course Syllabus)
This course provides a broad-based introduction to the management of information technology focusing on three interrelated themes: technology, organization, and strategy. The goal of this course is to equip students with the knowledge and tools to utilize information systems to pursue a firm's strategic and organizational goals. The course has no prerequisites other than a general interest in the applications of information technology.
OIDD2150 - Intro To Analyt & D Econ (Course Syllabus)
Over the past decade, there has been a dramatic rise in the use of technology skills and data analytic thinking to solve business problems in many domains, including finance, HR, policy, transport, and strategy. As a result, the modern "analytic leader" increasingly requires the use of technology, statistics, and data skills to facilitate business analysis. This includes knowing how to effectively frame data-driven questions and use a new generation of technology tools that are becoming available to acquire, analyze, interpret, and communicate insights derived from data. Students in this hands-on course will engage with weekly labs that introduce them to new technologies, techniques, and data-driven business challenges.
OIDD2200 - Operations Management Analytic (Course Syllabus)
This course introduces basic concepts of operations management and application of the same in business practice today. We will examine the theoretical foundations of operations management and how these principles or models can be employed in both tactical and strategic decision making. Topics covered in detail are forecasting techniques, planning under deterministic and uncertain demand, operations planning and scheduling, queuing theory, service operations management, newsvendor models, risk pooling strategies in firms, capacity and revenue management, and supply chain coordination. We will conclude by discussing how supply chains evolve under technological change.
OIDD2210 - Optimization and Analytics (Course Syllabus)
Understanding how to use data and business analytics can be the key differential for a company's success or failure. This course is designed to introduce fundamental quantitative decision-making tools for a broad range of managerial decision problems. Topics covered include linear, nonlinear, and discrete optimization, dynamic programming, and simulation. Students will apply these quantitative models in applications of portfolio management, electricity auctions, revenue management for airlines, manufacturing, advertising budget allocation, and healthcare scheduling operations. Emphasis in this course is placed on mathematical modeling of real world problems and implementation of decision making tools.
OIDD2220 - Internet Law Priv Cyber (Course Syllabus)
This course examines the complex and often novel legal issues surrounding the development and current state of the Internet, information privacy, and cybersecurity. Topics include federal- and state-level regulation and enforcement of Internet and privacy legal concepts, data breaches, online privacy protections, how to legally manage a borderless Internet, and the liability of intermediaries such as network operators, social media services, and search engines.
OIDD2340 - M&T First Year Seminar (Course Syllabus)
The objective of this seminar course is to help students understand the intersection of management and technology and how it is being translated in practice. It is designed to lay the foundation for an integrated productive learning program at Penn as students adjust to their new educational environment. The seminar is structured to accomplish this through faculty and alumni speakers from different sectors. Enrollment is limited to the freshman students and the few transfer students admitted to the M&T program only.
OIDD2360 - Scal Ops in Tech Venture (Course Syllabus)
This course helps students learn to make strategic scaling decisions that are grounded in operational reality. Students will study how to build and evaluate the "operation systems" of the firm to maximize value with the focus on scaling the firm's operations. This involves tailoring the firm's operational competencies, assets, and processes to a specific business strategy. The course will approach the challenge of scaling operations and operations strategy by taking a holistic view that incorporates competitive strategy, financial evaluation, and the customer experience.
OIDD2380 - M&T Global Immersive Week (Course Syllabus)
The M&T Global Immersive week is designed to provide the students in the program with firsthand experience to a global technology hub to further enhance learnings from both Penn Engineering and Wharton. With the number of technology startups in countries like Israel, India, China, especially the unicorns, the world will soon catch up with United States, if it has not already. Hence, the learnings of our future leaders should include a thorough understanding of the driving forces of the technology landscape in countries with a thriving startup culture. Each year M&T students across four years will go on a weeklong trip to a specific country chosen for that year in the first week of January. The global module will incorporate class lectures, workshops, guest lectures and visits to tech focused companies to meet local business founders and executives. Class will comprise of a group of up to 15 students chosen through an application process. The experiential learning provides the students an opportunity to learn from the leaders while immersing themselves in another culture and building relationships with the alumni in that area.
OIDD2450 - Analytics & Digital Econ (Course Syllabus)
Students who take this course will engage with the world of data science using tools such as Tableau and R that are becoming increasingly popular in industry. The first half of the course is designed for students with limited experience with data projects, and while familiarity with R, via courses such as STAT 4050 or STAT 4700, will be ideal preparation, students with other programming exposure can pick up the required skills via review sessions and self-instruction. The second half of the course extends students' experience to industry applications of text mining and machine learning and requires students to work with more unstructured data. Each week of the course will be devoted to analysis of a data set from a particular industry (e.g. HR, sports, fashion, real estate, music, education, politics, restaurants, non-profit work), which we will use to answer business questions by applying analytic techniques. The course is very hands-on, and students will be expected to become proficient at applying data to business decisions and at effectively analyzing large data sets to inform decisions about business problems.
OIDD2550 - A.I., Business, and Society (Course Syllabus)
The progression of AI-based technologies promises to transform many aspects of business, labor, and even society. The goal of this course is to provide students with an understanding of the capabilities of modern AI technologies, with an emphasis on being able to critically assess where they can provide business and societal value, and where they may create new challenges. This course is intended to provide a framework for people who may have to confront the legal, ethical, and economic challenges that are likely to arise around AI. A goal of the course is to ensure that students who complete the course are comfortable enough in the inner-workings of these technologies to think critically across many AI contexts as well as different domains ranging from public policy, to criminal justice, to health inspections, HR, and marketing. The course is oriented around hands-on labs, exams, discussions, and presentations. Labs will reinforce your learning of how AI works, and how it is being used to solve business problems. A coding background is not required, but students should be willing to engage with code to a limited degree in order to complete the labs. During labs, students will combine data and algorithms to provide a foundation for understanding the deep challenges that AI brings to organizations. The class is particularly suitable for students who will be searching for jobs in the business of technology, such as product management and business analytics, as well as those interested in the larger social implications of AI technologies.
OIDD2610 - Risk Analy & Env Mgmt (Course Syllabus)
This course will introduce students to concepts in risk governance. We will delve into the three pillars of risk analysis: risk assessment, risk management, and risk communication. The course will spend time on risk financing, including insurance markets. There will be particular emphasis on climate risks, although the course will also discuss several other examples, including pandemics, biodiversity loss, and systemic risks, among others. The course will cover how people perceive risks and the impact this has on risk communication and management. We will explore public policy surrounding risk management and how the public and private sectors can successfully work together to build resilience, particularly to changing risks.
OIDD2630 - Environ. & Energy Econ (Course Syllabus)
This course examines environmental and energy issues from an economist's perspective. Over the last several decades, energy markets have become some of the most dynamic markets of the world economy, as they experienced a shift from heavy regulation to market-driven incentives. First, we look at scarcity pricing and market power in electricity and gasoline markets. We then study oil and gas markets, with an emphasis on optimal extraction and pricing, and geopolitical risks that investors in hydrocarbon resources face. We then shift gears to the sources of environmental problems, and how policy makers can intervene to solve some of these problems. We talk about the economic rationale for a broad range of possible policies: environmental taxes, subsidies, performance standards and cap-and-trade. In doing so, we discuss fundamental concepts in environmental economics, such as externalities, valuation of the environment and the challenge of designing international agreements. At the end of the course, there will be special attention for the economics and finance of renewable energy and policies to foster its growth. Finally, we discuss the transportation sector, and analyze heavily debated policies such as fuel-economy standards and subsidies for green vehicles. Prerequisites: An introductory microeconomics course (ECON1, or another course approved by the instructor) will be sufficient in most cases; BEPP 250 or an equivalent intermediate microeconomics course is recommended.
OIDD2900 - Decision Processes (Course Syllabus)
This course is an intensive introduction to various scientific perspectives on the processes through which people make decisions. Perspectives covered include cognitive psychology of human problem-solving, judgment and choice, theories of rational judgment and decision, and the mathematical theory of games. Much of the material is technically rigorous. Prior or current enrollment in STAT 101 or the equivalent, although not required, is strongly recommended.
Prerequisites: STAT 1010
OIDD2910 - Negotiations (Course Syllabus)
This course examines the art and science of negotiation, with additional emphasis on conflict resolution. Students will engage in a number of simulated negotiations ranging from simple one-issue transactions to multi-party joint ventures. Through these exercises and associated readings, students explore the basic theoretical models of bargaining and have an opportunity to test and improve their negotiation skills.
OIDD2920 - Advanced Negotiation (Course Syllabus)
This course is designed to teach negotiation principles and to enable students to develop their negotiation skills. This course assumes familiarity with the basic negotiation concepts covered in the prerequisite for this course: Negotiations. In this course, we extend the study and practice of negotiations and we develop a deeper understanding for how specific aspects of the negotiation process (e.g., emotions, deadlines, trust violations) impact outcomes. Through course lectures, readings, and case exercises, students will develop a rich framework for thinking about the negotiation process and acquire tools for guiding the negotiation process.
Prerequisites: LGST 2060 OR OIDD 2910 OR MGMT 2910
OIDD2930 - People Analytics (Course Syllabus)
This course examines the use of data to understand and improve how people are managed in organizations. People really are organizations' most important asset, providing the critical link in converting strategy and capital into value. Yet throughout most of our history, most organizations have relied on long-standing traditions, hear-say, political expedience, prejudice and gut instinct to make decisions about how those people should be managed. Recent years have seen a growing movement to bring more science to how we manage people. In some cases, that means ensuring that whatever practices and approaches we adopt are backed up by solid evidence as to their effectiveness. Often, organizations will seek to go further, analyzing their own data to identify problems and learn what is working and what is not in their own context. This course applies the insights of the people analytics movement to help students become better managers and more critical analysts within their organizations. The course aims to develop students in three specific ways. First, it will provide students with an up-to-the-minute grounding in current evidence about managing people, providing a knowledge base that can ensure that their future management is guided by best practices. Second, we will develop the skills and understanding necessary to be thoughtful, critical consumers of evidence on people management, allowing them to make the most of the analysis available to them as they make people decisions. Third, we will provide guidance and practice in conducting people analytics, preparing students to gather data of their own, and making them more skilled analysts. We will pursue these goals through a mixture of lecture, case discussion, and hands on exploration of a variety of data sets.
OIDD2990 - Judg & Dec Making Res Im (Course Syllabus)
This class provides a high-level introduction to the field of judgment and decision making (JDM) and in-depth exposure to the process of doing research in this area. Throughout the semester you will gain hands-on experience with several different JDM research projects. You will be paired with a PhD student or faculty mentor who is working on a variety of different research studies. Each week you will be given assignments that are central to one or more of these studies, and you will be given detailed descriptions of the research projects you are contributing to and how your assignments relate to the successful completion of these projects. To complement your hands-on research experience, throughout the semester you will be assigned readings from the book Nudge by Thaler and Sunstein, which summarizes key recent ideas in the JDM literature. You will also meet as a group for an hour once every three weeks with the class's faculty supervisor and all of his or her PhD students to discuss the projects you are working on, to discuss the class readings, and to discuss your own research ideas stimulated by getting involved in various projects. Date and time to be mutually agreed upon by supervising faculty and students. the 1CU version of this course will involve approx. 10 hours of research immersion per week and a 10-page paper. The 0.5 CU version of this course will involve approx 5 hours of research immersion per week and a 5-page final paper. Please contact Professor Joseph Simmons if you are interested in enrolling in the course: jsimmo@wharton.upenn.edu
OIDD3140 - Enabling Technologies (Course Syllabus)
Conducting business in a networked economy invariably involves interplay with technology. The purpose of this course is to improve understanding of technology (what it can or cannot enable), the business drivers of technology-related decisions in firms, and to stimulate thought on new applications for commerce (including disruptive technologies). The class provides a comprehensive overview of various emerging technology enablers and culminates in discussion of potential business impact of these technologies in the near future. No prior technical background is assumed and hence every effort is made to build most of the lectures from the basics. However, the Fall semester class will assume basic understanding of statistics and will focus more on big data analytics. Some assignments in the fall will involve data analytics using Python or R.
OIDD3150 - Databases For Analytics (Course Syllabus)
Relational databases are the primary way in which business data is stored and processed. This course focuses on the analysis of data in databases and the development of databases to support analytical tasks. Over the course of the semester, students will learn the database language SQL and use this language to perform analytical tasks on existing and self-created databases. In addition, we will cover database scripting languages and extensions. The course is intended as students with little or no database background and does not presume prior computer science or coding experience. This course is nearly all hands-on coding. Students interested in more conceptual discussions of technology should consider other OIDD offerings.
OIDD3190 - Advanced Decision Sys (Course Syllabus)
This course is taught with the more descriptive title of "Agents, Games, and Evolution." It explores applications and fundamentals of strategic behavior. Strategic, or game-theoretic, topics arise throughout the social sciences. The topics include--and we discuss--trust, cooperation, market-related phenomena (including price equilibria and distribution of wealth), norms, conventions, commitment, coalition formation, and negotiation. They also include such applied matters as design of logistics systems, auctions, and markets generally (for example, markets for electric power generation). In addressing these topics we focus on the practical problem of finding effective strategies for agents in strategic situations (or games). Our method of exploration will be experimental: we review and discuss experiments, principally computational experiments, on the behavior of boundedly rational agents in strategic (or game-theoretic) situations. Course work includes readings, discussions in class (organized as a seminar), examinations, and a course project on a topic chosen by the participants.
OIDD3210 - Intro To Mgmt Science (Course Syllabus)
Understanding how to use data and business analytics can be the key differential for a company's success or failure. This course is designed to introduce fundamental quantitative decision-making tools for a broad range of managerial decision problems. Topics covered include linear, nonlinear, and discrete optimization, dynamic programming, and simulation. Students will apply these quantitative models in applications of portfolio management, electricity auctions, revenue management for airlines, manufacturing, advertising budget allocation, and healthcare scheduling operations. Emphasis in this course is placed on mathematical modeling of real world problems and implementation of decision making tools.
OIDD3250 - Comp Simulation Models (Course Syllabus)
This course focuses on agent-based computational models in the social sciences, especially in economic, in commercial and in strategic (game-theoretic) contexts. This relatively recent and now rapidly-developing form of computer simulation seeks to explain and predict complex social phenomena "from the ground up", through interactions of comparatively simple agents. The course reviews experimental and theoretical results, and exposes the students to modern development environments for this form of simulation. Students have the opportunity to design and implement agent-based simulations. Programming, however, is not required. This course aims to integrate various topics in agent-based simulation, while developing an appreciation of the problems that are particularly characteristic of this form of simulation so that students will understand its promise and potential.
OIDD3530 - Math Mdlng Appl in Fnce (Course Syllabus)
Quantitative methods have become fundamental tools in the analysis and planning of financial operations. There are many reasons for this development: the emergence of a whole range of new complex financial instruments, innovations in securitization, the increased globalization of the financial markets, the proliferation of information technology and the rise of high-frequency traders, etc. In this course, models for hedging, asset allocation, and multi-period portfolio planning are developed, implemented, and tested. In addition, pricing models for options, bonds, mortgage-backed securities, and other derivatives are studied. The models typically require the tools of statistics, optimization, and/or simulation, and they are implemented in spreadsheets or a high-level modeling environment, MATLAB. This course is quantitative and will require extensive computer use. The course is intended for students who have strong interest in finance. The objective is to provide students the necessary practical tools they will require should they choose to join the financial services industry, particularly in roles such as: derivatives, quantitative trading, portfolio management, structuring, financial engineering, risk management, etc. Prospective students should be comfortable with quantitative methods such as basic statistics and the methodologies (mathematical programming and simulation) in OIDD6120 Business Analytics and OIDD3210 Management Science (or equivalent). Students should seek permission from the instructor if the background requirements are not met.
Prerequisites: OIDD 3210
OIDD3800 - Operations Analytics Practicum (Course Syllabus)
This course focuses on the management of operations at manufacturing and service facilities located in Israel that are used either by domestic corporations or by multinational companies. The emphasis is on the evolving patterns of operations strategies adopted by firms for producing products, sourcing manufacturing, distributing products, delivering services and managing product design as well as on programs for enhancing quality, productivity and flexibility and managing technology. We will focus on formulation and execution of such strategies for established Israeli multinationals with world class operations and innovative strategies as well as start-ups and smaller companies that are scaling their global supply chain infrastructure to support growth. The course will consist of a set of site visits in Israel during Winter Break that will provide the opportunity to observe company processes directly and in-class sessions which include lectures, case discussions and management speakers who will describe their companies' current strategy. NOTE: THIS COURSE REQUIRES YOU TO SUBMIT AN APPLICATION FOR ADMISSION. Enrollment will be limited. Please contact Stacie Anderson at staciea@wharton.upenn.edu for more information. Application available at https://global.upenn.edu/pennabroad/pgs OIDD 1010 is recommended but not required.
OIDD3970 - Retail Supp Chain Mgmt (Course Syllabus)
This course is highly recommended for students with an interest in pursuing careers in: (1) retailing and retail supply chains; (2) businesses like banking, consulting, information technology, that provides services to retail firms; (3) manufacturing companies (e.g. P&G) that sell their products through retail firms. Retailing is a huge industry that has consistently been an incubator for new business concepts. This course will examine how retailers understand their customers' preferences and respond with appropriate products through effective supply chain management. Supply chain management is vitally important for retailers and has been noted as the source of success for many retailers such as Wal-mart and Home Depot, and as an inhibitor of success for e-tailers as they struggle with delivery reliability. See M. L. Fisher, A. Raman and A. McClelland, "Rocket Science Retailing is Coming - Are You Ready?," Harvard Business Review, July/August 2000 for related research.
OIDD3990 - Supervised Study (Course Syllabus)
This course number is currently used for several course types including independent studies, experimental courses and Management & Technology Freshman Seminar. Instructor permission required to enroll in any independent study. Wharton Undergraduate students must also receive approval from the Undergraduate Division to register for independent studies. Section 002 is the Management and Technology Freshman Seminar; instruction permission is not required for this section and is only open to M&T students. For Fall 2020, Section 004 is a new course titled AI, Business, and Society. The course provides a overview of AI and its role in business transformation. The purpose of this course is to improve understanding of AI, discuss the many ways in which AI is being used in the industry, and provide a strategic framework for how to bring AI to the center of digital transformation efforts. In terms of AI overview, we will go over a brief technical overview for students who are not actively immersed in AI (topic covered include Big Data, data warehousing, data-mining, different forms of machine learning, etc). In terms of business applications, we will consider applications of AI in media, Finance, retail, and other industries. Finally, we will consider how AI can be used as a source of competitive advantage. We will conclude with a discussion of ethical challenges and a governance framework for AI. No prior technical background is assumed but some interest in (and exposure to) technology is helpful. Every effort is made to build most of the lectures from the basics.
OIDD4110 - How To Make Things (Course Syllabus)
The course centers around a sequence of three projects that each culminate in the design and fabrication of functional objects. A 2D Design, 3D Design, and final "Micro-Manufacturing" project will introduce students to a wide variety of design, engineering, and fabrication skills made possible by the new Studios @ Tangen Hall. The micro-manufacturing final project will task interdisciplinary student teams to create a "micro-business" where they will design and utilize 3D printed molding and casting techniques to create a small-scale run of functional products. These products will then be showcased in an end of semester exposition, where the teams will merchandise and market their products to the Penn community. This exposition will also be a wonderful inaugural use of the student and alumni retail space on the 1st floor of Tangen Hall and serve as a great university-wide event to show case the work of SEAS students. Requires proficiency in solid modeling software (e.g., SolidWorks, Maya, Rhino), practice with design process, and hands-on fabrication experience.
OIDD4150 - Product Design (Course Syllabus)
This course provides tools and methods for creating new products. The course is intended for students with a strong career interest in new product development, entrepreneurship, and/or technology development. The course follows an overall product design methodology, including the identification of customer needs, generation of product concepts, prototyping, and design-for-manufacturing. Weekly student assignments are focused on the design of a new product and culminate in the creation of a prototype, which is launched at an end-of-semester public Design Fair. The course project is a physical good - but most of the tools and methods apply to services and software products. The course is open to any Penn sophomore, junior, senior or graduate student. The course follows a studio format, in which students meet for three hours each week with Professor Marcovitz for lectures and hands-on making, and students will complete 90 minutes of asynchronous, self-paced content from Professor Ulrich on their own time each week. Professor Ulrich gives one in-person lecture during the semester and attends the Design Fair, but is not present at the weekly studio sessions.
OIDD4180 - India Startup Ecosystem (Course Syllabus)
The objective of OIDD/MGMT 418 and the Wharton India Fellows program is to introduce Penn juniors to the entrepreneurship and innovation ecosystem in India through a course covering topics in entrepreneurship, innovation, venture capital and technology in India and then matching students to a specific short-term project with a Bangalore-based early-stage startup or rapidly scaling company. Students will complete preliminary work on the project assignment during the course, and then travel as a group to Bangalore with the instructor for a two week immersion in the company to which they have been assigned for their entrepreneurship project. Penn Wharton Entrepreneurship will cover airfare and lodging expenses for students selected as Wharton India Fellows for the duration of the 2 week immersion in India. For more information: https://entrepreneurship.wharton.upenn.edu/wharton-india-fellows/
OIDD4690 - Info Strat & Econ (Course Syllabus)
This course is devoted to the study of the strategic use of information and the related role of information technology, and designed for students who want to manage and compete in technology-intensive businesses. The topics of the course vary year to year, but generally include current issues in selling digital products, intermediation and disintermediation, competing in online markets, emerging technologies, managing artificial intelligence and data science for business, and technology project management. Heavy emphasis is placed on utilizing information economics to analyze businesses in information-intensive industries. Technology skills are not required, although a background in information technology management, strategic management or managerial economics is helpful. The course is designed to complement OIDD 2100, OIDD 2150, OIDD 2450, and OIDD 255X.
OIDD4770 - Intro To Python Data Sci (Course Syllabus)
The goal of this course is to introduce the Python programming language within the context of the closely related areas of statistics and data science. Students will develop a solid grasp of Python programming basics, as they are exposed to the entire data science workflow, starting from interacting with SQL databases to query and retrieve data, through data wrangling, reshaping, summarizing, analyzing and ultimately reporting their results. Competency in Python is a critical skill for students interested in data science. Prerequisites: No prior programming experience is expected, but statistics, through the level of multiple regression is required. This requirement may be fulfilled with Undergraduate courses such as Stat 1020, Stat 1120.
OIDD4810 - Conv Optim Stat Data Sci (Course Syllabus)
Convex optimization has become a real pillar of modern data science and has transformed algorithm designs. A wide spectrum of problems in statistics, machine learning, and engineering can be formulated as optimization tasks that exhibit favorable convexity properties, which admit standardized and efficient solutions. This course aims to introduce the elements of convex optimization, concentrating on modeling aspects and algorithms that are useful in data science applications. Topics include convex sets, convex functions, linear and quadratic programs, semidefinite programming, optimality conditions and duality theory. We will visit important applications in statistics and machine learning to demonstrate the wide applicability of convex optimization. We will also cover effective optimization algorithms like gradient descent and Newton's method. Prerequisites: Basic linear algebra (Math 3120, 3130, 3140 or equivalent), basic calculus (Math 2400 or equivalent), basic probability (STAT 4300 or equivalent), and knowledge of a programming language like MATLAB or Python to conduct simulation exercises.
OIDD4900 - Sci of Behavior Change (Course Syllabus)
The objective of this 14-week discussion-based seminar for advanced undergraduates is to expose students to cutting-edge research from psychology and economics on the most effective strategies for changing behavior sustainably and for the better (e.g., promoting healthier eating and exercise, encouraging better study habits, and increasing savings rates). The weekly readings cover classic and current research in this area. The target audience for this course is advanced undergraduate students interested in behavioral science research and particularly those hoping to learn about using social science to change behavior for good. Although there are no pre-requisites for this class, it is well-suited to students who have taken (and enjoyed) courses like OIDD 2900: Decision Processes, PPE 2030/PSYC 2650: Behavioral Economics and Psychology, and MKTG 2660: Marketing for Social Impact and are interested in taking a deeper dive into the academic research related to promoting behavior change for good. Instructor permission is required to enroll in this course. Please complete the application if interested in registering for this seminar: http://bit.ly/bcfg-class-2020. The application deadline is July 31, 2020. Prerequisite: Permission of instructor required.
OIDD5110 - How To Make Things (Course Syllabus)
The course centers around a sequence of three projects that each culminate in the design and fabrication of functional objects. A 2D Design, 3D Design, and final "Micro-Manufacturing" project will introduce students to a wide variety of design, engineering, and fabrication skills made possible by the new Studios @ Tangen Hall. The micro-manufacturing final project will task interdisciplinary student teams to create a "micro-business" where they will design and utilize 3D printed molding and casting techniques to create a small-scale run of functional products. These products will then be showcased in an end of semester exposition, where the teams will merchandise and market their products to the Penn community. This exposition will also be a wonderful inaugural use of the student and alumni retail space on the 1st floor of Tangen Hall and serve as a great university-wide event to show case the work of SEAS students. Requires proficiency in solid modeling software (e.g., SolidWorks, Maya, Rhino), practice with design process, and hands-on fabrication experience.
OIDD5150 - Product Design (Course Syllabus)
This course provides tools and methods for creating new products. The course is intended for students with a strong career interest in new product development, entrepreneurship, and/or technology development. The course follows an overall product design methodology, including the identification of customer needs, generation of product concepts, prototyping, and design-for-manufacturing. Weekly student assignments are focused on the design of a new product and culminate in the creation of a prototype, which is launched at an end-of-semester public Design Fair. The course project is a physical good - but most of the tools and methods apply to services and software products. The course is open to any Penn sophomore, junior, senior or graduate student. The course follows a studio format, in which students meet for three hours each week with Professor Marcovitz for lectures and hands-on making, and students will complete 90 minutes of asynchronous, self-paced content from Professor Ulrich on their own time each week. Professor Ulrich gives one in-person lecture during the semester and attends the Design Fair, but is not present at the weekly studio sessions.
OIDD5250 - Thinking with Models (Course Syllabus)
Models are lenses. They are instruments with which we view, interpret, and give meaning to data. In this course, students will be exposed to and do work in all phases of the modeling life-cycle, including model design and specification, model construction (including data gathering and testing), extraction of information from models during post-solution analysis, and creation of studies that use modeling results to support conclusions for scientific or decision making purposes. In addition, the course will cover critical assessments of fielded models and studies using them. The course will focus broadly on models pertaining to energy and sustainability. This is not only an inherently interesting and important area, but it is very much a public one. In consequence, models, data, and studies using them are publicly and profusely available, as is excellent journalism, which facilitates introductions to specific topics. The course covers selected topics in energy and sustainability. Essential background will be presented as needed, but the course is not a comprehensive overview of energy and sustainability. Modeling in the area of energy and sustainability analytics is rife with uncertainty, and yet decisions must be made. Uncertainty, and how to deal with it in model-based decision making, is an overarching theme of the course. We will focus on energy and sustainability, but that area is hardly unique in being beset with deep and vexing uncertainties. The lessons we learn will generalize. The overall aim of the course is to teach facility with modeling and to use real-world data, models, and studies in doing so. In addition, students with interests in investment or policy analysis in the energy sphere will find the course's subject area focus useful. OIDD 325 is not a prerequisite for this course, but it's helpful if you have already taken it.
OIDD5810 - Conv Optim Stat Data Sci (Course Syllabus)
Convex optimization has become a real pillar of modern data science and has transformed algorithm designs. A wide spectrum of problems in statistics, machine learning, and engineering can be formulated as optimization tasks that exhibit favorable convexity properties, which admit standardized and efficient solutions. This course aims to introduce the elements of convex optimization, concentrating on modeling aspects and algorithms that are useful in data science applications. Topics include convex sets, convex functions, linear and quadratic programs, semidefinite programming, optimality conditions and duality theory. We will visit important applications in statistics and machine learning to demonstrate the wide applicability of convex optimization. We will also cover effective optimization algorithms like gradient descent and Newton's method. Prerequisites: Basic linear algebra, basic calculus, basic probability, and knowledge of a programming language like MATLAB or Python to conduct simulation exercises.