Become Data Literate, no prior experience required. This hands-on Data Analysis: A Practical Approach for Absolute Beginners course gives you an overview of what a Data Analyst needs to know and deliver, and is meant to inspire you with all the possibilities that Data unlocks for the world.
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.
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
- Basic excel proficiency
- 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
Sr. Content Developer
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.
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).
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.
Start learning Data Analysis: A Practical Approach for Absolute Beginners
You can enroll now for the Data Analysis: A Practical Approach for Absolute Beginners course at our DataChangers Academy ! Do you want to learn more? Then check out our other Data Analysis Track Courses .