11 EFFICIENCY Introduction to Data Analysis using Excel for Absolute Beginners


SISC
Enrollment in this course is by invitation only

About This Course

Digital transformation and advanced technologies like AI and quantum computing are fueled by data. Every industry and profession needs data analysis, from a small business’s survey data to CERN’s 100’s of petabytes per experiment. Analyzing data is one of the most critical skills of the future.

This course, meant for people of all ages, will bring you from the very beginnings of data concepts and structures in context, all the way through analyzing data, telling data stories effectively, and understanding the environments in which data exists throughout our work and life. It will also start you on the path to becoming a data analyst. Throughout the course, we’ll reference additional courses and learning paths you can take to help you on your data career journey.

Please Note: Learners who successfully complete this course can earn a CloudSwyft digital certificate and skill badge - these are detailed, secure and blockchain authenticated credentials that profile the knowledge and skills you’ve acquired in this course.

What you'll learn

  • Understand data’s many contexts, origins and applications in life, work, and society
  • Understand introductory level data and mathematical concepts
  • Work with different types of data
  • Become data literate with the basic data analyst toolkit, including data storytelling
  • Apply summary statistics to analyze and understand data sets
  • Apply analytics methods to industry and business scenarios
  • Learn about data analyst career paths

prerequisites

  • Basic excel proficiency

Course Syllabus

  • Module 1: Our Data-Driven World
  • Module 2: Our First Data Walkthrough
  • Module 3: Our Data Structures
  • Module 4: Our Data Analysis Methods
  • Module 5: Our Data Analysis in Context
  • Module 6: Final and Challenge Labs

Course Staff

Ben Olsen

Ben Olsen

Sr. Content Developer
Microsoft

Ben is a Sr. Content Developer for Microsoft's Learning and Readiness team, and is an analytics professional and educator with over 8 years of industry and managerial experience. Prior to joining Microsoft, Ben ran and directed multiple consulting firms, where he also held critical analytics roles in companies as diverse as Juniper Networks, Costco, and T-Mobile. He has taught Data Visualization at The University of Washington, and recently founded Seattle Pacific University's Analytics Certificate Program.

Tom Carpenter

Tom Carpenter

Assistant Professor of Psychology, Data Science consultant
Seattle Pacific University

Dr. Tom Carpenter is Assistant Professor of Psychology at Seattle Pacific University, and is also a Data Science consultant. His areas of expertise include personality-social psychology, research methods, and statistics. His teaching focuses on introductory and advanced research methods and statistics in psychology as well as social and personality psychology. Dr. Carpenter’s research focuses on our hypocritical human nature: our propensity to ignore our overt preferences and standards and to transgress against ourselves and others. One line of research in this area focuses on implicit bias, the impulsive thoughts that can undermine our higher reasoning. Dr. Carpenter has developed new software methods for running the Implicit Association Test (IAT) using online survey software (read more here: www.iatgen.wordpress.com). A second line of research focuses on guilt, shame, and self-forgiveness, specifically focusing on the functions of ‘guilt-proneness’ and ‘shame-proneness’ as well as associations with the general ability to forgive the self. Finally, Dr. Carpenter has conducted research related to his area of teaching (statistics education).

Trevor Barnes

Trevor Barnes

Content Developer
Self-employed

Self-employed

Frequently Asked Questions

Do I need desktop Excel?

No. We will be using Excel Online for all applied portions of the course

Do I need a Windows computer to complete the course?

No. You can complete the labs using a computer running Windows, Mac OS X, or Linux.

  1. Course Number

    11EFFICIENCYDAT269x
  2. Classes Start

  3. Classes End

  4. Estimated Effort

    Total 12 to 24 hours