University of Michigan
Understanding Data: Navigating Statistics, Science, and AI Specialization
University of Michigan

Understanding Data: Navigating Statistics, Science, and AI Specialization

Navigate the World of Data with Confidence. Gain essential skills in data analysis, scientific reasoning, and AI for informed decision-making

Taught in English

Elle O'Brien

Instructor: Elle O'Brien

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Specialization - 3 course series

Get in-depth knowledge of a subject

4.9

(5 reviews)

Beginner level

Recommended experience

3 months at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Assess the credibility and limitations of claims involving statistics and scientific research

  • Understand the fundamentals of machine learning and navigate conversations about AI with confidence

  • Interpret and evaluate statements about data to make informed decisions in your personal and professional life

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Recently updated!

May 2024

Specialization - 3 course series

Get in-depth knowledge of a subject

4.9

(5 reviews)

Beginner level

Recommended experience

3 months at 10 hours a week
Flexible schedule
Learn at your own pace

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  • Develop a deep understanding of key concepts
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Specialization - 3 course series

How to Describe Data

Course 19 hours

What you'll learn

  • Learn the fundamentals of data interpretation, collection, and summarization

  • Learn the capabilities and limitations of data and discuss criteria for determining which statistics are reliable

  • Learn to interpret and evaluate the effectiveness of data visualizations

Skills you'll gain

Category: Probability And Statistics
Category: Data Literacy
Category: Data Analysis

What you'll learn

  • Learn the rationale and limitations of significance testing within scientific inquiry, including crafting hypotheses and interpreting p-values

  • Learn how scientific experiments are proposed, designed, reviewed, and published

  • Identify common biases and mistranslations in science research reporting and the challenges of conveying science research to the public effectively

  • Assess the credibility of claims about research and recognize the role of replicability and generalizability in scientific progress

Skills you'll gain

Category: Probability And Statistics
Category: Data Analysis
Category: Data Literacy

What you'll learn

  • Learn key concepts and terminology in artificial intelligence (AI), including machine learning, generative AI, and deep learning

  • Learn the core components of machine learning systems, including data, models, and evaluation techniques

  • Recognize why AI systems can fail and identify the kinds of work required to make useful technology

  • Identify common pitfalls in conversations about AI and recognize conflicts of interest when interpreting claims about AI systems

Skills you'll gain

Category: Artificial Intelligence
Category: Data Analysis
Category: Data Literacy
Category: Machine Learning

Instructor

Elle O'Brien
University of Michigan
6 Courses1,206 learners

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