Coursera is an online education provider that offers online courses, popularly known as MOOCs or Massive Open Online Courses, from top universities around the world. Currently it has over 200 partners from 48 countries. These partners include Universities such as Stanford, Duke, Penn, Princeton, Michigan, Peking, and HEC Paris.


Speaking to Inform: Discussing Complex Ideas with Clear Explanations and Dynamic Slides

In the professional realm, most speeches and presentations we give are informative in scope. A scientist needs to explain her recent research findings. A financial officer needs to report on quarterly earnings to his company’s board. A technology professional needs to educate a consumer about a new product. Any time you need to convey ideas or demonstrate a process, you’re dealing with informative speaking.

Informative speaking is a fun puzzle. You need to think from the perspective of your audience to identify what they need to hear in order to understand the key ideas. How much does the audience already know? What are the most important elements to convey? How should one convey these ideas with appropriate breadth and depth given the time constraints of the speech? This demands a strategic approach to speech design that we’ll undertake in this class.

By the end of the course, you should be able to explain complex ideas vividly and accessibly, design clear and compelling presentation slides, convey your passion for a topic while maintaining your professional credibility, and speak dynamically from notes and/or a manuscript. Learners will record speeches, providing and receiving peer feedback.

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Assessment in Higher Education: Professional Development for Teachers

Are you a teacher in higher education wanting to get the best out of your students and assessments? This course will guide you through the different phases of preparing, creating and evaluating the assessments in your course.

After participating in this course, you will be able to:

  1. Design an assessment that is constructively aligned (content, level, methods) with the course objectives and activities
  2. Apply the quality criteria with respect to validity, reliability and transparency for construction of assessments and assessment items
  3. Analyze the assessment output and results, assess the quality of the assessment and make decisions about students’ grades accordingly
  4. Formulate future improvements for an assessment

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Process Mining: Data Science in Action

Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don't need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact.

In this course, you will learn about the pillars of computational thinking, how computer scientists develop and analyze algorithms, and how solutions can be realized on a computer using the Python programming language. By the end of the course, you will be able to develop an algorithm and express it to the computer by writing a simple Python program. This course will introduce you to people from diverse professions who use computational thinking to solve problems. You will engage with a unique community of analytical thinkers and be encouraged to consider how you can make a positive social impact through computational thinking.

The course is at an introductory level with various practical assignments.

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Computational Thinking for Problem Solving (online)

Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains.

Participants will learn various process discovery algorithms. These can be used to automatically learn process models from raw event data. Various other process analysis techniques that use event data will be presented. Moreover, the course will provide easy-to-use software, real-life data sets, and practical skills to directly apply the theory in a variety of application domains. This course starts with an overview of approaches and technologies that use event data to support decision making and business process (re)design. Then the course focuses on process mining as a bridge between data mining and business process modeling.

The course is at an introductory level with various practical assignments.

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