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Mastering Data Analysis in Excel
by Jana Schaich Borg , Daniel Egger- 4.2
Approx. 21 hours to complete
Important: The focus of this course is on math - specifically, data-analysis concepts and methods - not on Excel for its own sake. We use Excel to do our calculations, and all math formulas are given as Excel Spreadsheets, but we do not attempt to cover Excel Macros, Visual Basic, Pivot Tables, or other intermediate-to-advanced Excel functionality....
Essential Design Principles for Tableau
by Govind Acharya , Hunter Whitney- 4.5
Approx. 13 hours to complete
In this course, you will analyze and apply essential design principles to your Tableau visualizations. This course assumes you understand the tools within Tableau and have some knowledge of the fundamental concepts of data visualization. You will evaluate pre-attentive attributes and why they are important in visualizations. Getting Started in Effective and Ineffective Visuals...
IBM Data Analyst Capstone Project
by Ramesh Sannareddy , Rav Ahuja- 4.6
Approx. 13 hours to complete
In this course you will apply various Data Analytics skills and techniques that you have learned as part of the previous courses in the IBM Data Analyst Professional Certificate. The project will culminate with a presentation of your data analysis report, with an executive summary for the various stakeholders in the organization....
Data Visualization with Advanced Excel
by Alex Mannella- 4.8
Approx. 15 hours to complete
In this course, you will get hands-on instruction of advanced Excel 2013 functions. You’ll learn to use PowerPivot to build databases and data models. In the second half of the course, will cover how to visualize data, tell a story and explore data by reviewing core principles of data visualization and dashboarding....
Math behind Moneyball
by Professor Wayne Winston- 4.5
Approx. 65 hours to complete
Learn how probability, math, and statistics can be used to help baseball, football and basketball teams improve, player and lineup selection as well as in game strategy. Before you start. . . All you will learn Suggested Textbooks (Not Required) Module 1 1. 1 Introduction 1. 2 Pythagorean Theorem 1. 3 Ten runs = One win...
Building a Data Science Team
by Jeff Leek, PhD , Brian Caffo, PhD , Roger D. Peng, PhD- 4.5
Approx. 6 hours to complete
Data science is a team sport. As a data science executive it is your job to recruit, organize, and manage the team to success. This is a focused course designed to rapidly get you up to speed on the process of building and managing a data science team. After completing this course you will know....
Introduction to Data Analytics for Business
by David Torgerson- 4.7
Approx. 12 hours to complete
This course will expose you to the data analytics practices executed in the business world. We will explore such key areas as the analytical process, how data is created, stored, accessed, and how the organization works with data and creates the environment in which analytics can flourish. Data and Analysis in the Real World...
Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions
by Sharad Borle- 4.7
Approx. 21 hours to complete
The ability to understand and apply Business Statistics is becoming increasingly important in the industry. A good understanding of Business Statistics is a requirement to make correct and relevant interpretations of data. Lack of knowledge could lead to erroneous decisions which could potentially have negative consequences for a firm. This course is designed to introduce you to Business Statistics....
Data Science for Business Innovation
by Marco Brambilla , Emanuele Della Valle- 4.2
Approx. 7 hours to complete
The course is a compendium of the must-have expertise in data science for executive and middle-management to foster data-driven innovation. It consists of introductory lectures spanning big data, machine learning, data valorization and communication. Topics cover the essential concepts and intuitions on data needs, data analysis, machine learning methods, respective pros and cons, and practical applicability issues....
Digital Marketing Analytics in Practice
by Kevin Hartman- 4.5
Approx. 20 hours to complete
Successfully marketing brands today requires a well-balanced blend of art and science. This course introduces students to the science of web analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide the foundation needed to apply data analytics to real-world challenges marketers confront daily....