Об этом курсе
4.3
Оценки: 84
Рецензии: 10
The analytical process does not end with models than can predict with accuracy or prescribe the best solution to business problems. Developing these models and gaining insights from data do not necessarily lead to successful implementations. This depends on the ability to communicate results to those who make decisions. Presenting findings to decision makers who are not familiar with the language of analytics presents a challenge. In this course you will learn how to communicate analytics results to stakeholders who do not understand the details of analytics but want evidence of analysis and data. You will be able to choose the right vehicles to present quantitative information, including those based on principles of data visualization. You will also learn how to develop and deliver data-analytics stories that provide context, insight, and interpretation....
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Approx. 7 hours to complete

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Только онлайн-курсы

Начните сейчас и учитесь по собственному графику.
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Гибкие сроки

Назначьте сроки сдачи в соответствии со своим графиком.
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Approx. 7 hours to complete

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Программа курса: что вы изучите

Week
1
Clock
1 ч. на завершение

Introduction to the Course

In this module we’ll briefly review the Information-Action Value Chain we introduced in Course 1. Then we’ll see how analytical techniques are applied in business problems, first by looking at some “classic” business problems that have been around for a long time, then by looking at some “emergent” business problems that have resulted from more recent advances in technology....
Reading
4 видео (всего 35 мин.), 1 тест
Video4 видео
1. Information Action Value Chain Redux5мин
2. Analytics in Classic Business Problems11мин
3. Analytics in Emergent Business Problems13мин
Quiz1 практическое упражнение
Week 1 Quiz20мин
Week
2
Clock
1 ч. на завершение

Best Practices in Data Visualization

In this module we’ll learn about a variety of visualizations used to illustrate and communicate data. We will start with the different vehicles used to present quantitative information. We will then look at a set of examples of data visualizations and discuss what makes them effective or ineffective. Finally, we discuss Excel charts and why most of them should be avoided. After completing this module, you will be able to better understand the characteristics of good data visualization and avoid common mistakes when creating your own graphs. ...
Reading
7 видео (всего 28 мин.), 1 тест
Video7 видео
Vehicles to Present Quantitative Information4мин
Data Visualization Examples3мин
Graphs in Excel and ASP5мин
Graphical Excellence4мин
Techniques to Display Multiple Variables4мин
Excel Charts to Avoid2мин
Quiz1 практическое упражнение
Week 2 Quiz30мин
Week
3
Clock
2 ч. на завершение

Interpreting, Telling, and Selling

In this module we’ll cover a number of topics around interpreting data, gathering additional data, and pitching our recommendations based on our analysis. First, we’ll discuss ways in which we misinterpret or misrepresent data and how to avoid them, such as mistaking correlation with causation, allowing cognitive biases to influence how we see data, and visualizing data in misleading ways. We’ll also learn how experimentation can help us obtain more data, including compromises we may need to make in measurement. Finally, we’ll discuss how we communicate our results and recommendations, with a focus on knowing our audience, telling compelling stories, and creating clear and effective communication materials. ...
Reading
7 видео (всего 62 мин.), 1 тест
Video7 видео
Common Cognitive Biases10мин
Misleading With Data8мин
Market Experiments: When the action is the question7мин
Know thy Audience11мин
Telling compelling stories6мин
Making It Real9мин
Quiz1 практическое упражнение
Week 3 Quiz38мин
Week
4
Clock
2 ч. на завершение

Acting on Data

In our final module we’ll walk through two case studies and illustrate the ideas we’ve covered in the course and in the specialization as a whole. The first case shows how experimentation can be used to create data, sometimes with surprising results. The second case presents a comprehensive analysis that illustrates the entire analytic lifecycle, and shows how different methods and both quantitative and qualitative analysis can be brought together to solve one strategically important analytical problem....
Reading
4 видео (всего 40 мин.), 2 тестов
Video4 видео
Case Study 2: Multidimensional Analysis for Customer Acquisition - Part 15мин
Case Study 2: Multidimensional Analysis for Customer Acquisition - Part 211мин
Case Study 2: Multidimensional Analysis for Customer Acquisition - Part 310мин
Quiz2 практического упражнения
Week 4 Quiz16мин
Final Course Assignmentмин
4.3
Briefcase

83%

получил значимые преимущества в карьере благодаря этому курсу

Лучшие рецензии

автор: SKMar 1st 2018

I really enjoyed the materials presented in this course. I wish recommendations on reference books were provided in any of these courses.

автор: AKMar 18th 2018

Very good course, Case based learning and examples explaing use of analaytics clarifed the course a lot.

Преподавателя

Manuel Laguna

Professor
Leeds School of Business

Dan Zhang

Professor
Leeds School of Business

David Torgerson

Instructor

О University of Colorado Boulder

CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies....

О специализации ''Advanced Business Analytics'

The Advanced Business Analytics Specialization brings together academic professionals and experienced practitioners to share real world data analytics skills you can use to grow your business, increase profits, and create maximum value for your shareholders. Learners gain practical skills in extracting and manipulating data using SQL code, executing statistical methods for descriptive, predictive, and prescriptive analysis, and effectively interpreting and presenting analytic results. The problems faced by decision makers in today’s competitive business environment are complex. Achieve a clear competitive advantage by using data to explain the performance of a business, evaluate different courses of action, and employ a structured approach to business problem-solving. Check out a one-minute video about this specialization to learn more!...
Advanced Business Analytics

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