About this course

Want to study for an MBA but unsure of the basic data analysis still required? This online course prepares you for studying in an MBA program and in business generally.

Data analysis appears throughout any rigorous MBA program and in today’s business environment understanding the fundamentals of collecting, presenting, describing and making inferences from data sets is essential for success.

The goal of this course is to teach you fundamental data analysis skills so you are prepared for your MBA study and able to focus your efforts on core MBA curriculum, rather than continually playing catch-up with the underlying statistical knowledge needed.

We also hope that learning these data analysis skills will equip you with the ability to understand, to a greater degree, the data you encounter in your working lives and in the world around you – an essential life-skill in today’s data driven environment

This course assumes no prior knowledge of data analysis. Concepts are explained as clearly as possible and regular activities give you the opportunity to practice your skills and improve your confidence.

What you’ll learn

  • Presenting and summarising your data
  • Decision making under uncertainty
  • Data-based decision making
  • Modelling for decision making

Syllabus

Topic 1 – Presenting and summarising your data
Topic 2 – Decision making under uncertainty
Topic 3 – Data-based decision making
Topic 4 – Modelling for decision making

Meet your instructors

David Lefevre

David is the Director of the EdTech Lab at Imperial College Business School. He is also the course leader on the Business School’s Pre-study module in Maths. David holds an MSc in Computing Science and a PhD in the field of instructional systems from Imperial College London and, perhaps most importantly, a BSc in Mathematics from the University of East Anglia (UEA). David and his EdTech Lab team launched the Global Online MBA program in 2015 and have received awards along the way including a Gold award at the IMS Learning Impact awards in 2010 and an Effective Practice Award at the Sloan-C Blended Learning Conference in 2011.

Catarina Sismeiro

Dr. Catarina Sismeiro is an Associate Professor at Imperial College Business School where she teaches on the Full-Time and Executive MBA programs. Catarina’s research has been published in The Journal of Marketing Research, Management Science, and The International Journal of Research in Marketing and has won several awards. Previously she was an Assistant Professor at Marshall Business School, University of Southern California. She holds a PhD in Management from the Anderson School, UCLA, and a Licenciatura in Management from Faculdade de Economia do Porto (Portugal).

About MIT horizon

MIT Horizon is an expansive content library built to help you explore emerging technologies. Through easy-to-understand lessons, you’ll be guided through the complexities of the latest technologies and simplified expert-level concepts. Designed for both technical and non-technical learners, you can examine bite-size content that can lead to maximum career outcomes.

For a limited time, gain access to the complete MIT Horizon library.

Register today for exclusive entry.

About this course

Want to know how to avoid bad decisions with data?

Making good decisions with data can give you a distinct competitive advantage in business. This statistics and data analysis course will help you understand the fundamental concepts of sound statistical thinking that can be applied in surprisingly wide contexts, sometimes even before there is any data! Key concepts like understanding variation, perceiving relative risk of alternative decisions, and pinpointing sources of variation will be highlighted.

These big picture ideas have motivated the development of quantitative models, but in most traditional statistics courses, these concepts get lost behind a wall of little techniques and computations. In this course we keep the focus on the ideas that really matter, and we illustrate them with lively, practical, accessible examples.

We will explore questions like: How are traditional statistical methods still relevant in modern analytics applications? How can we avoid common fallacies and misconceptions when approaching quantitative problems? How do we apply statistical methods in predictive applications? How do we gain a better understanding of customer engagement through analytics?

This course will be is relevant for anyone eager to have a framework for good decision-making. It will be good preparation for students with a bachelor’s degree contemplating graduate study in a business field.

Opportunities in analytics are abundant at the moment. Specific techniques or software packages may be helpful in landing first jobs, but those techniques and packages may soon be replaced by something newer and trendier. Understanding the ways in which quantitative models really work, however, is a management level skill that is unlikely to go out of style.

What you’ll learn

  • Variability in the real world and implications for decision making
  • Data types and data quality with appropriate visualizations
  • Apply data analysis to managerial decisions, especially in start-ups
  • Making effective decisions from no data to big data (what should we collect and then what do we do with all this data?)

Meet your instructors

Rick Cleary

Professor Rick Cleary is a statistician and mathematician with research and consulting interests in a variety of fields including sports, biomechanics, and statistical approaches to fraud detection and audit risk. Prior to coming to Babson College in 2013, Professor Cleary taught at St. Michael’s College in Vermont, Cornell University, Bentley University, and Harvard University. He has held many leadership positions in the Mathematical Association of America, including six years on the Executive Committee as Associate Treasurer and a term as chair of the Joint Data Committee. He is currently on the Nominations Committee and the Polya lecturer selection committee. Professor Cleary enjoys working with mathematics teachers at all levels to improve statistics education and he gives frequent talks and workshops on ways to encourage statistical thinking.

Nathan Karst

Dr. Nathan Karst received his B.S. in electrical and computer engineering from Franklin W. Olin College of Engineering in 2007 and his doctorate in applied mathematics from Cornell. He is an avid teacher and researcher, having won the Dean’s Award for Excellence in Undergraduate Teaching in 2014 and the Dean’s Award for Excellence in Scholarship in 2015. Most recently, his research has focused on the role of nonlinear dynamics in microvascular networks and event-scale streamflow recession variability.

Davit Khachatryan

Dr. Davit Khachatryan is an Assistant Professor of Statistics and Analytics at Babson College. He is an applied statistician with research interests in analyzing intellectual property data to study the formation and diffusion of knowledge in emerging industries. Davit’s current and former research has produced publications in academic, peer-reviewed journals such as Journal of the Royal Statistical Society (Series C), The American Statistician, IEEE Transactions on Engineering Management (forthcoming), and Quality and Reliability Engineering International. Prior to joining Babson College, Davit was a Senior Associate at the National Economics and Statistics practice of Pricewaterhouse Coopers (PwC). In the latter role he consulted in the area of predictive modeling and advanced data analytics, helping clients from financial, healthcare, and government sectors with building automatic predictive models and enhancing business intelligence solutions. Davit has earned his B.S. in Applied Mathematics and Informatics from Yerevan State University, M.S. in Statistics and Ph.D. in Management Science from the University of Massachusetts, Amherst.

George Recck

Mr. Recck has taught at Babson College since 1984. He currently serves as the Chair of the Business Analytics/Statistics Education special interest group for the American Statistical Association (ASA). Mr. Recck is also the founder of Total Information, Inc., an consulting firm specializing in providing information service to small businesses.

Babak Zafari

†Dr. Zafari is an Assistant Professor of Analytics and Statistics in the Math & Science Division. His area of interests are Predictive Modeling and Data Mining Methods for Business Applications, Bayesian Statistics, Healthcare Fraud Analytics and Online Auctions. Prior to joining Babson College, he was a Visiting Assistant Professor at The George Washington University School of Business teaching courses in Data Analysis and Decisions, Business Analytics and Data Mining. He was also a senior statistician consultant at Integrity Management Services where he was responsible for developing statistical models for fraud detection in Medicare and Medicaid programs. He received his B.S. in Applied Mathematics from Sharif University of Technology, M.S. in Operations Research/Computer Science from Bowling Green State University and Ph.D. in Decision Sciences from The George Washington University School of Business.

About MIT horizon

MIT Horizon is an expansive content library built to help you explore emerging technologies. Through easy-to-understand lessons, you’ll be guided through the complexities of the latest technologies and simplified expert-level concepts. Designed for both technical and non-technical learners, you can examine bite-size content that can lead to maximum career outcomes.

For a limited time, gain access to the complete MIT Horizon library.

Register today for exclusive entry.

About This Course:

Perhaps the most popular data science methodologies come from machine learning. What distinguishes machine learning from other computer guided decision processes is that it builds prediction algorithms using data. Some of the most popular products that use machine learning include the handwriting readers implemented by the postal service, speech recognition, movie recommendation systems, and spam detectors.

In this course, part of our Professional Certificate Program in Data Science, you will learn popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system.

You will learn about training data, and how to use a set of data to discover potentially predictive relationships. As you build the movie recommendation system, you will learn how to train algorithms using training data so you can predict the outcome for future datasets. You will also learn about overtraining and techniques to avoid it such as cross-validation. All of these skills are fundamental to machine learning.

What You’ll Learn:

  • The basics of machine learning
  • How to perform cross-validation to avoid overtraining
  • Several popular machine learning algorithms
  • How to build a recommendation system
  • What is regularization and why it is useful?

Frequently Asked Questions:

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Who can take this course?

Unfortunately, learners from one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. EdX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.

Meet Your Instructor:

Ansaf Salleb-Aouissi

Ansaf is a Lecturer in discipline of the Computer Science Department at the School of Engineering and Applied Science at Columbia University. She received her her BS in Computer Science in 1996 from the University of Science and Technology (USTHB), Algeria. She earned her masters and Ph.D. degrees in Computer Science from the University of Orleans (France) in 1999 and 2003 respectively.

About MIT Horizon:

MIT Horizon is an expansive content library built to help you explore emerging technologies. Through easy-to-understand lessons, you’ll be guided through the complexities of the latest technologies and simplified expert-level concepts. Designed for both technical and non-technical learners, you can examine bite-size content that can lead to maximum career outcomes.

For a limited time, gain access to the complete MIT Horizon library.

Register today for exclusive entry.

Program overview

The power sector is at a critical juncture. We urgently need to reduce the fossil fuel intensity of our power generation mix and, in many countries, power sector reform can bring other benefits, such as improvements in health and economic growth. In this program, leading academics from Imperial College London, alongside NREL and experts from industry, will explain why and how to clean up the power sector in your country, illustrated with current, real-life case studies and practical advice. Key global figures from the public and private sector add their own personal and professional perspectives to this course.

The Clean Power Program includes best-practice power sector reform policies from the perspectives of legislators, policymakers, the energy sector, investors and civil society. The first course will explain the way that clean power fits into a wider set of political priorities, such as health, technology, energy security, economic growth and the environment, in any country or region. In the second course, the policy landscape for the power sector is described in detail, demonstrating how policies can help stimulate the growth of clean power. The third course outlines the challenges and solutions to integrating different types of power sources into one stable, reliable system.

This program will equip you with the knowledge and tools to create a pro-renewables and investor-ready policy environment in your own region. In a world committed to meeting the climate change goals in the Paris Agreement, you will be well-informed to apply solutions in your own context.Established ten years ago as an Institute of Imperial College London, the Grantham Institute is a world-leading authority on climate change and environmental issues. The Grantham Institute will bring industry and public sector experts from around the world to share their practical and recent experience.

What you will learn

  • How to balance different political priorities to deliver clean power policies
  • What benefits clean power implementation can bring to different countries around the world and, specifically, what they bring in your context
  • What makes a successful, renewables-friendly policy environment
  • How to attract finance for your clean power projects
  • How to deliver secure and affordable clean power
  • How to integrate a high volume of variable renewables into a grid successfully

Program Class List

Meet Your Instructors

Jo Haigh

Professor at Imperial College London
Professor Joanna Haigh has been Co-Director of the Grantham Institute at Imperial College since 2014. For the previous five years she was Head of the Department of Physics. Jo's scientific interests include radiative transfer in the atmosphere, climate modelling, radiative forcing of climate change and the influence of solar irradiance variability on climate. She has published widely on these topics in the scientific literature and contributed to numerous items to the written and broadcast popular media. She is a Fellow of the Royal Society and of the Institute of Physics and an Honorary Fellow of Somerville College Oxford. She has been President of the Royal Meteorological Society, Editor of Quarterly Journal of the Royal Meteorological Society and of the Journal of Atmospheric Sciences, a Lead Author on the Intergovernmental Panel on Climate Change and acted on many UK and international panels.

Kris Murray

Dr at Imperial College London
Kris is an ecologist with interests in global change, conservation and health, working on problems where these key themes are interconnected, including: human health - climate, environmental and social change impacts on infectious disease burdens and distributions, disease emergence, zoonoses, biosecurity risks, health economics; and climate change - influence on ecosystems, biodiversity and health risks In particular, Kris focuses on problems that characterise the impacts of global change, that could also be leveraged for mitigating human impacts and promoting better stewardship of the natural world.

Shane Tomlinson

Mr at Imperial College London
Shane Tomlinson, a Director of E3G, leads work on political economy mapping and overseeing the UK programme. He previously served as the Director of Development at E3G working across the organisation on strategy development, fundraising and the creation of systems for change. Prior to joining E3G Shane was a Senior Research Fellow at Chatham House where he published research on the future of the EU Energy Union, Brexit, stranded assets and the future of the international climate regime. He has also worked as a Policy Adviser in the Prime Minister’s Strategy Unit working on energy policy, sustainable consumption and production issues and the design and launch of the Extractives Industry Transparency Initiative (EITI) at the World Summit on Sustainable Development. Shane holds an MPA from the Woodrow Wilson School at Princeton University, an MSc in Economic History from the London School of Economics and a BSc in Economics and Economic History from the University of Bristol.

Richard Green

Professor at Imperial College London
Richard Green has been studying the economics and regulation of the electricity industry for nearly 30 years. The main focus of his recent work has been on the impact of low-carbon generation (nuclear and renewables) and energy storage on the electricity market, and the business and policy implications of this. He has written extensively on market power in wholesale electricity markets and has also worked on transmission pricing. He has been a professor at Imperial College Business School since 2011. He was previously Professor of Energy Economics and Director of the Institute for Energy Research and Policy at the University of Birmingham, and Professor of Economics at the University of Hull. He started his career at the Department of Applied Economics and Fitzwilliam College, Cambridge. He has spent time on secondment to the Office of Electricity Regulation and has held visiting appointments at the World Bank, the University of California Energy Institute and the Massachusetts Institute of Technology.

Clementine Chambon

Dr at Imperial College London
Clementine Chambon is a researcher in renewable energy technologies for rural electrification. Her interests lie in optimising design and delivery models for decentralised energy systems to reach the most energy-deprived communities in the world. Her current project examines biomass gasification and its application for rural electrification in LED countries. This spans topics such as electricity demand estimation, technological performance of biogasifiers, integration with other generation technologies as part of a hybrid system, and analysing their impact in terms of cost and CO2 mitigation potential. The research findings are directly commercialised through Oorja Development Solutions, a mission-driven company active in deploying solar mini-grids and community solar irrigation systems to provide clean energy access to off- and weak-grid communities in rural India.

Jeff Hardy

Dr at Imperial College London
Dr Jeffrey Hardy is a Senior Research Fellow at the Grantham Institute - Climate Change and the Environment at Imperial College London, where he researches energy market transformation, innovative business models. He is also a Non-Executive Director of Public Power Solutions, a wholly-owned company of Swindon Borough Council specialising in renewable power and waste solutions. Previously he was Head of Sustainable Energy Futures at the GB energy regulator, Ofgem and Head of Science for Work Group III of the Intergovernmental Panel on Climate Change. He’s also worked at the Department of Business, Energy and Industrial Strategy, the UK Energy Research Centre, the Royal Society of Chemistry, the Green Chemistry Group at the University of York and at Sellafield as research chemist in a nuclear laboratory.

Ajay Gambhir

Dr at Imperial College London
Ajay Gambhir is a Senior Research Fellow at the Imperial College London Grantham Institute for Climate Change and the Environment. His research addresses how society can transition to a low-carbon economy, considering the technologies and measures required to do so. He uses energy systems models at sub-national, national, regional and global scales to map out potential low-carbon transition pathways, with a particular focus on the processes that drive down low-carbon technology costs, thereby making their deployment more cost-effective. Ajay has been at Imperial College since 2010, during which time he has been the scientific lead on a number of low-carbon pathways studies for the UK government as part of its AVOIDing dangerous climate change programme. He has also led and participated in ESRC and EPSRC studies on manufacturing innovation for the production of low-cost solar PV modules, energy storage innovation, and rural electrification using solar PV and batteries. Currently he is focusing on the political economy of low-carbon pathways and how to design policies to support an equitable transition. Before joining Imperial College, Ajay was the Team Leader for EU and International Climate Change Economics at the UK Government’s Department of Energy and Climate Change. He has also worked in the UK’s Office for Climate Change, as part of the civil service team that prepared the initial draft of the Climate Change Act 2008, the world’s first climate legislation. He has also worked in the UK Committee on Climate Change, which he helped design and set up as part of his work on the Climate Change Act.

About This Course:

Do you want to learn how to design? Using the Delft Design Approach, you will learn how to use a number of key design methods to create meaningful products and services.

This course is an introduction to the Delft Design Approach offering a model and a set of signature methods from Delft to teach you how to get from understanding the user in context to defining a meaningful design challenge and – in the end – deliver a great design! The course challenges you to experience the design process yourself and reflect on your work with the help of students and excellent teaching staff from Delft, and industrial experts.

No previous knowledge of design methods is required, yet some experience with designing (something) is helpful.

This course has been awarded with the 2015 Open Education Award for Excellence in the category ‘Open MOOC’ by the Open Education Consortium.

 

What You’ll Learn:

  • How to study users in their own environment;
  • How to translate user insights into a design challenge that will spark creativity;
  • How to create a meaningful design to meet your challenge;
  • How to design and to structure your projects with the support of design thinking, a model and several methods;
  • How to evaluate and present your design.
 

Syllabus:

This course is self-paced and structured along 6 steps. Most steps can be done in about a week, except for step 5 which might take two weeks). The course is then structured as follows:

Step 1: Understanding meaning in design
​•How do the things around us attain their meaning?
​•How and why do we design meaningful things?

Step 2: Understanding the context of use
• How and why do we gain empathic understanding of the users we design for?
• How do we derive insights to inspire the design process?

Step 3: Defining a design challenge
• How do we identify the key design problem when we look at the user’s current situation?
• How do we define a meaningful design challenge that will drive the creative phases of design?

Step 4: Generating ideas
• How do we generate ideas?
• How do we filter promising ideas?

Step 5: Developing concepts (Optional EXTRA: Prototyping Concept)
• What is a design concept and how do we develop a concept?
• What role does sketching have in developing concepts?
• How do we evaluate concepts and decide between them?

Step 6: Testing with user & final presentation (Optional EXTRA: Testing Prototype of Concept)
• How do we test key qualities of a concept?
• How do we present a concept?

Meet Your Instructors:

Annemiek van Boeijen

Annemiek is assistant professor in industrial design and design aesthetics at the Delft University of Technology. She conducts research on the role of culture in design processes. She is co-editor of the Delft Design Guide. She received her MSc. and PhD from Delft University of Technology.
Jaap J.J. Daalhuizen

Jaap J.J. Daalhuizen

Jaap was assistant professor at the Delft University of Technology. He now works at the Technical University of Denmark. He conducts research in design methodology and design thinking. He is co-editor of the Delft Design Guide. He received his MSc. and PhD from Delft University of Technology.

Learner testimonials

” The Delft Design course taught me how to fully understand the end-users and their needs and how to meet them through product development.”

Joseph,the Philippines

” The Delft Design course taught me how to fully understand the end-users and their needs and how to meet them through product development.”

Joseph,the Philippines

About this course

If you want to be the technology specialist who can procure and gain insight into cutting edge systems to help save lives and cut disaster losses, this Professional Certificate provides the foundational knowledge you need.

It is designed for recreational hobbyists, certified remote pilots, commercial operators, and public safety and government users.

This course covers unmanned aerial systems (UAS) to include drones and autonomous aerial vehicles, sensors, communications, ground control, navigation and other payloads that rely on complex algorithms that can be applied for protecting and saving lives and property.

In this edX Professional Certificate, you will learn the importance of autonomous systems and drone technologies that bring speed, efficiency and affordable solutions to disaster response and management. Topics include the use of drones by emergency managers, first responders, and search and rescue personnel responding to natural and manmade disasters.

No previous knowledge of drones or flight experience is required. Join as you start your drone journey.

Taught by highly experienced instructors and practitioners in military and civil UAS operations, practical applications, systems design, and emergency management planning, this course will provide the novice, subject-matter expert analyst, planner and operational associate with the technical understanding for infusing drone solutions into emergency management and planning.

Additionally, those who have a curiosity or general interest in drones, be it casual or in-depth, will benefit from this course to gain insight into emergency management, homeland security, and intelligence applications

What you’ll learn

  • Classification of disaster types according to hazard origin – natural, such as storms and flooding, earthquakes, tsunamis, volcanic eruption, flooding, wildfires, drought, epidemics; human-induced, such as criminal, terrorist, active shooter and accidental such as oil spills, train derailment; and humanitarian disasters such as famine and refugee/migration crises.
  • Tasks and applications – forecasting, command and control, disaster relief operations, structural analysis, rescue and recovery, and logistics.
  • Customer sets – governments (local, state, and national levels), NGOs, private contractors, defense, information technology, transportation, aeronautical, engineering and construction, agriculture, entrepreneurs, etc.
  • Examination of drone technologies used in emergency preparedness and response including platforms and missions, power, propulsion, payloads, emergency response communication system that use Unmanned Aerial Vehicles (UAVs); satellite communication (SATCOM) datalinks; and remote sensing.
  • How to develop technology implementation solutions based on a crisis scenario.
  • Critical infrastructure applications such as monitoring dams, highways, floods, food and agriculture, finance, national parks and monuments etc.
  • Future technology implications such as artificial intelligence, algorithms, 5-G technology, accelerated integration of multiple data sources, counter-UAS capabilities, weaponized hobbyist drones, and docking stations and tethers.

Syllabus

Week 1: Introduction to hazards, disasters and drone applications

Week 2: Global natural disasters and drone applications I

Week 3: Global natural disasters and drone applications II

Week 4: Man-made disasters and drone applications I

Week 5: Man-made disasters and drone applications II

Week 6: Future drone applications

Meet your instructor

Brian Powers, M.A.

Brian Powers is an associate professor and chair of the Intelligence Management Program at UMGC. Prior to joining UMGC, he served for 26 years in the United States Air Force as an intelligence officer serving in various operational and staff assignments at the Pentagon in the Air Staff, Joint Staff, and Undersecretary of Defense for Intelligence (USD(I); and three overseas Combatant Commands in the Europe, Middle East and Pacific regions. He has also worked 13 years in the private sector as an intelligence planner in strategy and policy at the National Geospatial-Intelligence Agency and Defense Intelligence Agency, and as a program director and educator. He holds a master’s degree in Business and Organizational Security from Webster University, a master’s degree in National Security Affairs from the U.S. Naval Postgraduate School, a master’s degree in International Relations from Creighton University.

About this course

Build professional VR apps using Unity 3D, a powerful cross-platform 3D engine that provides a user-friendly development environment. In this course, part of the Virtual Reality Professional Certificate program, you will learn how to build a VR engine from the ground up, so you fully understand the entire rendering pipeline from 3D model to pixels in the VR display. We will also cover motion prediction, 3D stereo, lens distortion, time warp and other optimizations for a fluid, realistic VR experience.

You will also learn how to implement the most important VR interaction concepts such as selection, manipulation, travel, wayfinding, menus, and text input in Unity.

Unity is a GUI based programming environment, in which much of the programming can be done through dialog windows. It also supports scripts written in C#, which as we will show will allow for more complex VR functionality.

What you learn about VR programming in this course will help you write VR games, architectural walkthroughs, engineering simulations, 3D data viewers, medical training applications, and many more.

What you’ll learn

  • Develop professional VR apps using Unity 3D
  • Run Unity 3D applications in VR on a smartphone
  • Create a 3D environment from scratch in game engines
  • Select and manipulate objects with various input types
  • Move around a 3D world using unique locomotion methods
  • Create intuitive 3D menus to control applications
  • Design unique methods of 3D interaction
  • Input alphanumeric information, such as text and numbers, in VR
  • Build tools to help users navigate 3D environments
  • Learn key usability goals and pitfalls for Virtual Reality

Syllabus

  • Week 1: VR and Game Engines
  • Week 2: Physics and Gaze Interaction
  • Week 3: 3D UI and Locomotion
  • Week 4: 3D User Interaction
  • Week 5: Wayfinding and VR Input
  • Week 6: Testing and Special Topics

Meet your instructor

Jurgen P. Schulze

Research Scientist and Adjunct Professor of Computer Science at UC San Diego Jurgen teaches computer graphics and virtual reality at UC San Diego. His research interests include applications for virtual and augmented reality systems, 3D human-computer interaction, and medical data visualization. He holds an M.S. degree from the University of Massachusetts and a Ph.D. from the University of Stuttgart, Germany. He spent two years as a post-doctoral researcher in the Computer Science Department at Brown University.

About this course

Virtual reality is changing the way we interact with the world. But how does it work, what hardware is involved, and how is software written for it?

In this course, part of the Virtual Reality Professional Certificate program, we will explore the foundations of user-friendly virtual reality app development for consumers, as well as enterprise solutions. Both hardware and software aspects will be discussed. You will learn to evaluate devices necessary for virtual reality applications, what their differences are, how you write interactive applications for virtual reality, and we will discuss the most frequent problems you are going to need to solve to write virtual reality software.

In this course, you will explore the basics of virtual reality software through copying and modifying JavaScript to explore tradeoffs in VR application design. Extensive programming experience is not required.

By the end of this course, you will understand what is important for successful virtual reality software and learn how to write simple virtual reality programs themselves with WebVR.

This course is taught by an instructor with almost two decades of experience in virtual reality who leads the Immersive Visualization Laboratory at UC San Diego.

What you’ll learn

  • Types of virtual reality devices and their strengths and weaknesses
  • How virtual reality applications differ from other interactive software programs
  • What makes a virtual reality application successful
  • What to avoid when writing virtual reality software
  • Basic VR programming using WebVR

Syllabus

  • Week 1: VR definition and display systems
  • Week 2: 3D Tracking and Input Devices
  • Week 3: How to interact with the VR environment
  • Week 4: How to move around in VR
  • Week 5: 3D Menus and Text Input
  • Week 6: VR app design

Meet your instructor

Jurgen P. Schulze

Research Scientist and Adjunct Professor of Computer Science at UC San Diego Jurgen teaches computer graphics and virtual reality at UC San Diego. His research interests include applications for virtual and augmented reality systems, 3D human-computer interaction, and medical data visualization. He holds an M.S. degree from the University of Massachusetts and a Ph.D. from the University of Stuttgart, Germany. He spent two years as a post-doctoral researcher in the Computer Science Department at Brown University.

About this course

Today, computer graphics is a central part of our lives, in movies, games, computer-aided design, virtual simulators, visualization and even imaging products and cameras. This course teaches the basics of computer graphics that apply to all of these domains.

Students will learn to create computer-generated images of 3D scenes, including flybys of objects, make a real-time scene viewer, and create very realistic images with raytracing. We will start with a simple example of viewing a teapot from anywhere in space, understanding the basic mathematics of virtual camera placement. Next, you will learn how to use real-time graphics programming languages like OpenGL and GLSL to create your own scene viewer, enabling you to fly around and manipulate 3D scenes. Finally, we will teach you to create highly realistic images with reflections and shadows using raytracing.CSE167x teaches the foundations of computer graphics.

This course runs for 6 weeks and consists of four segments. Each segment includes an individual programming assignment:

  1. Overview and Basic Math (Homework 0: 10% of grade)
  2. Transformations (Homework 1: 20% of grade)
  3. OpenGL and Lighting (Homework 2: 35% of grade)
  4. Raytracing (Homework 3: 35% of grade)

This term, students who earn a total score of 50% or greater will have passed the course and may obtain a certificate from UC San DiegoX.

What you’ll learn

Understand the concepts of 3D graphics
  • Write and develop programs that create images of a 3D scene with lighting
  • Learn the basics of graphics programming with OpenGL and GLSL

FAQ

What is the format of the class?

The class will consist of lecture videos, brief exercises, and homework assignments. Each of the four segments of the course will have 2-3 lectures. Each lecture includes 3-5 lecture videos, which last between 10 and 20 minutes. There will be a brief exercise after each lecture video to help you test your understanding of the material.

Your score will be determined entirely by programming assignments for which you will receive immediate autograder feedback. You may submit your assignment to the autograder multiple times; only your last submission will count.

Programming projects are to be implemented individually without copying code from other students, largely identical online resources, or previous instances of the class. However, short of posting or sharing actual explicit code, you are encouraged to collaborate and discuss problems in the discussion forums.

Will the text of the lectures be available?

Yes. All of our lectures will have transcripts synced to the videos.

Do I need to watch the lectures live?

No. You can watch the lectures at your leisure. You can “work ahead” if you want to move faster than the due dates. Conversely, you can progress at a slower pace. Please note that certificates will only be awarded to students who obtain the requisite score by turning in assignments by the established deadlines.

How much does it cost to take the course?

Nothing: the course is free. If you expect to be doing a lot of graphics programming in the future, we would recommend the OpenGL and GLSL programming guides, but it is by no means required to purchase them. There are many free online resources for these topics, and we will be posting links to them.

What computer system do I need for the course?

The course material involves C++/OpenGL/GLSL programming that is portable. We provide skeleton code for all major platforms (Windows, Mac OS, Linux). This is a modern course involving programmable shaders, but any machine built in the last few years should be adequate. We provide many compilation hints and tips, and Homework 0 is to ensure you can compile and work with the autograder. You do need some kind of C++ development environment; we provide several resources to get you started for Homework 0. In the highly unlikely event you cannot get your machine to work, you will hopefully have adequate time to find another system.

Will I learn Maya/DirectX/3D Studio Max etc.?

This is a course on the foundations of computer graphics and covers concepts, not the intricacies of a particular software package. That said, you will be able to write complex interactive and offline 3D graphics programs at the end of the course in C++, OpenGL and GLSL.

Can I contact the Instructor or Teaching Assistants?

Yes, but not directly. The discussion forums are the appropriate venue for questions about the course. The instructors will monitor the discussion forums and try to respond to the most important questions; in many cases response from other students and peers will be adequate and faster.

I have a disability (visual/hearing etc.) Can I take the course?

In most cases, yes. We provide transcripts for all lectures. Many leading computer graphics researchers have had visual impairments like color-blindness. However, this being a computer graphics course that relies on visual image comparisons, we probably cannot provide adequate support for those who are legally blind.

I have a busy schedule this fall. Can I still take the course?

The course does require about 12 hours per week of work, and the assignments (where you are given two weeks) require the time. Certificates of achievement require a passing score. Of course, you are welcome to just go through the lectures or attempt some of the assignments if you are not interested in a certificate; we hope to provide something for everyone.

 

Meet your instructors

Ravi Ramamoorthi

Ravi Ramamoorthi is a Professor at the University of California, San Diego. He has taught computer graphics more than 10 times at Stanford, Columbia and UC Berkeley, and has been honored with a number of awards for his research, including the ACM SIGGRAPH Significant New Researcher Award and by the White House with the PECASE (Presidential Early Career Award for Scientists and Engineers). He was a finalist for the inaugural edX Prize for Exceptional Contributions in Online Teaching and Learning.

About this course

Marketing innovative products and services occurs in an ever-changing environment, and requires rapid decision making with incomplete information. These innovations are introduced at increasingly frequent intervals, and there are high mortality rates for products and services, and the businesses themselves.

Our course provides a practical, how-to guide for navigating these marketing challenges to bring innovative new products and services to market. With learning modules on product strategy, go-to-market strategies, and growth strategies, you will build your skills in understanding and applying the latest marketing strategies and tactics. We’ll explore how to develop an informed marketing plan that aligns with customer needs based on real market research.

Learn the latest strategies for customer discovery, interviews and focus groups, product design, product development, content marketing, social media marketing, and marketing campaign management. The course will provide a balance between conceptual discussions based on readings of concepts and practices, and applied, hands-on analysis with real projects.

What you’ll learn

  • Learn the fundamentals of product strategy with attention to product vision, user journey mapping, business modeling, SMART objectives, customer profiling, customers jobs, customer pains, customer gains, competition, and differentiators.
  • Understand go to market strategies with an exploration of buyer journey, pricing, channel strategy, positioning, branding, and product-market fit.
  • Develop insights on growth strategies as we explore inbound vs outbound marketing, types of media, pull marketing, push marketing, social media marketing, social media channels and content, budgeting, timing, content calendars, customer activation, landing pages, customer retention, email campaigns, and minimum viable products (MVPs).

Syllabus

Module 1: Product Strategy

We’ll begin with introducing why it’s important to build a business case for your innovation. Key topics will include business model, value propositions, customer profiles, value maps, product-market fit, and industry analysis.

Module 2: Go To Market Strategies

Once the product strategy is established, we’ll consider go-to-market strategies. This begins with setting your marketing objectives. We’ll discuss pricing strategies, channel strategies, positioning, and messaging strategies. We’ll also introduce the minimum viable product (MVP) experience.

Module 3: Growth Strategies

In our growth strategies segment, we’ll examine marketing optimization strategies. Creating and managing your social media marketing activities and search engine optimization (SEO) are key to this step. Branding and sales will also be explored.

Module 4: Next Steps

In the final segment, we’ll discuss why new ventures fail, and how effective marketing impacts the success of a venture. We’ll discuss what is means to make the decision to Pivot, Persevere, or Pass? We’ll also discuss types of pivots, and how these influence the ongoing success of companies.

Meet your instructor

Lola Koiki

Lola Koiki is a senior product manager at Capital One with responsibility for leading the development, launch, and commercialization of Emerging Payments, which encompasses U.S. Real-Time Payments, Payment Infrastructure Modernization, and Payments Innovation. She is currently leading Capital One’s effort to join the first new payments clearing system in the United States in over 40 years, while developing an enterprise-wide consistent strategy for faster payment capabilities across the company. In addition to her work at Capital One, she is a partner at PoyntFour, a Product Management and Delivery Consultancy based in the DC area, with a focus on pre-seed to series startups and mid-size government agencies looking to build high efficiency teams. She is also a Lecturer with the University of Maryland’s Maryland Technology Enterprise Institute. In her time at University of Maryland, she has taught over 500 undergraduate students, many of which have gone on to launch new ventures or work in start-ups. She is a graduate of Carnegie Mellon University, with a Masters in Information Systems Management. She holds a BS in Marketing and Supply Chain Management from the University of Maryland. She currently lives in Washington DC and volunteers with organizations in the area, such as The Neighborhood Well, a non-profit focused on helping the unstably housed in the DC Area, and Acts1038, a non-profit focused on education and career development for immigrants to the United States.

Learner testimonials

“The instruction and startup coaching that I received when a student at the University of Maryland were invaluable to the launch and growth of Squarespace. The skills taught in this course are a fantastic introduction to many of the fundamentals one needs when starting a business.”

Anthony Casalena, Founder and CEO of Squarespace

“The instruction and startup coaching that I received when a student at the University of Maryland were invaluable to the launch and growth of Squarespace. The skills taught in this course are a fantastic introduction to many of the fundamentals one needs when starting a business.”

Anthony Casalena, Founder and CEO of Squarespace