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List of MOOCs offered by the Best Universities and Entities

 

Upcoming courses (for the next 30 days)

May 29th 2016

The success of every organization depends on attracting and retaining customers. Although the marketing concepts for doing so are well established, digital technology has empowered customers, while producing massive amounts of data, revolutionizing the processes through which organizations attract and retain customers. In this course, students will learn how to identify new opportunities to create value for empowered consumers, develop strategies that yield an advantage over rivals, and develop the data science skills to lead more effectively, allocate resources, and to confront this very challenging environment with confidence.

Average: 8.3 (7 votes)
May 29th 2016

This is an Exploratorium teacher professional development course taught by Teacher Institute staff, open to any science teacher (particularly middle or high school level) and science enthusiast. This is a hands-on workshop that explores topics and strategies teachers can use to help their students become active investigators of light.

Average: 10 (3 votes)
May 29th 2016

For three decades and longer we have heard educators and technologists making a case for the transformative power of technology in learning. However, despite the rhetoric, in many ways and at most institutional sites, education is still relatively untouched by technology. Even when technologies are introduced, the changes sometimes seem insignificant and the results seem disappointing. If the print textbook is replaced by an e-book, do the social relations of knowledge and learning necessarily change at all or for the better? If the pen-and-paper test is mechanized, does this change the nature of our assessment systems? Technology, in other words, need not necessarily bring significant change. Technology might not even represent a step forward in education.

Average: 1 (2 votes)
May 29th 2016

L'écotourisme est aujourd’hui un mot utilisé par nombreux acteurs dans différents contextes mais parfois avec certaines confusions d’usage. Ce Mooc, « l’écotourisme, imaginons-le ensemble », vise à vous aider à: distinguer et définir l'écotourisme parmi les autres formes de tourisme; cerner les enjeux de son intégration dans le développement territorial; analyser le cadrage d'un projet avec l'écotourisme.

No votes yet
May 29th 2016

A blank canvas is full of possibility. If you have an idea for a user experience, how do you turn it into a beautiful and effective user interface? This covers covers principles of visual design so that you can effectively organize and present information with your interfaces. You'll learn concrete strategies to create user interfaces, including key lessons in typography, information architecture, layout, color, and more. You’ll learn particular issues that arise in new device contexts, such as mobile and responsive interfaces.

Average: 5.2 (19 votes)
May 29th 2016

Explore data analysis and visualization in Excel, the cloud benefits of Power BI, and Power Pivot, pivot tables, and tools previously known as Power Query. Microsoft Excel is one of the most widely used solutions for analyzing and visualizing data. Beginning with Excel 2010, new tools were introduced to enable the analysis of more data, resulting in less time spent creating and maintaining the solutions and enabling a better understanding of what the data means. This better understanding is facilitated by improved visualizations and more sophisticated business logics.
Do you want to take your advanced Excel skills to the next level? Are you exploring new ways to get and transform your data and create visualization?

Average: 4 (4 votes)
May 30th 2016

Are you interested in predicting future outcomes using your data? This course helps you do just that! Machine learning is the process of developing, testing, and applying predictive algorithms to achieve this goal. Make sure to familiarize yourself with course 3 of this specialization before diving into these machine learning concepts. Building on Course 3, which introduces students to integral supervised machine learning concepts, this course will provide an overview of many additional concepts, techniques, and algorithms in machine learning, from basic classification to decision trees and clustering.

Average: 9 (2 votes)
May 30th 2016

In this course, you will develop and test hypotheses about your data. You will learn a variety of statistical tests, as well as strategies to know how to apply the appropriate one to your specific data and question. Using your choice of two powerful statistical software packages (SAS or Python), you will explore ANOVA, Chi-Square, and Pearson correlation analysis. This course will guide you through basic statistical principles to give you the tools to answer questions you have developed. Throughout the course, you will share your progress with others to gain valuable feedback and provide insight to other learners about their work.

No votes yet
May 30th 2016

Whether being used to customize advertising to millions of website visitors or streamline inventory ordering at a small restaurant, data is becoming more integral to success. Too often, we’re not sure how use data to find answers to the questions that will make us more successful in what we do. In this course, you will discover what data is and think about what questions you have that can be answered by the data – even if you’ve never thought about data before. Based on existing data, you will learn to develop a research question, describe the variables and their relationships, calculate basic statistics, and present your results clearly. By the end of the course, you will be able to use powerful data analysis tools – either SAS or Python – to manage and visualize your data, including how to deal with missing data, variable groups, and graphs. Throughout the course, you will share your progress with others to gain valuable feedback, while also learning how your peers use data to answer their own questions.

Average: 8.6 (5 votes)
May 30th 2016

The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem into pieces and solve them recursively; when it makes sense to proceed greedily; how dynamic programming is used in genomic studies. You will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second).

Average: 10 (2 votes)

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