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AI Workflow: Data Analysis and Hypothesis Testing

AI Workflow: Data Analysis and Hypothesis Testing

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9.1/10 (Our Score)
Product is rated as #10 in category Artificial Intelligence

This is the second course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. In this course you will begin your work for a hypothetical streaming media company by doing exploratory data analysis (EDA). Best practices for data visualization, handling missing data, and hypothesis testing will be introduced to you as part of your work. You will learn techniques of estimation with probability distributions and extending these estimates to apply null hypothesis significance tests. You will apply what you learn through two hands on case studies: data visualization and multiple testing using a simple pipeline. By the end of this course you should be able to: 1. List several best practices concerning EDA and data visualization 2. Create a simple dashboard in Watson Studio 3. Describe strategies for dealing with missing data 4. Explain the difference between imputation and multiple imputation 5. Employ common distributions to answer questions about event probabilities 6. Explain the investigative role of hypothesis testing in EDA 7. Apply several methods for dealing with multiple testing Who should take …

Instructor Details

Mark J. Grover is a member of the IBM Data & AI Learning team and specializes in creating and delivering online content. He comes to IBM from Cape Fear Community College in Wilmington, NC where he was a full time professor of computer technology. He was one of the coordinators for their Information Security program and taught courses in Computer Security, Network Administration, System Administration, and Microsoft Office. He was the lead Cisco instructor and faculty advisor to the school’s annual Cisco Netriders networking competition. During his tenure, he was recognized as a Cisco Instructor of Excellence – Expert level and was nominated for US Professor of the Year. Prior to teaching, Mark owned and operated a computer sales and service company for over 13 years. He then transitioned to a position working at the University of North Carolina Wilmington providing enterprise computer support, where he achieved the highest award for a staff member: The Award for Excellence in Innovation. Mark brings over 25 years of information technology experience to IBM. His passion includes camping, hiking, mountain biking, and spending time with his family. He is happily married and has two kids.

Specification: AI Workflow: Data Analysis and Hypothesis Testing

Duration 5 hours
Year 2020
Level Expert
Certificate Yes
Quizzes Yes

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AI Workflow: Data Analysis and Hypothesis Testing
AI Workflow: Data Analysis and Hypothesis Testing

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