Online Course – Certified Data Professional Internship: Statistics, Science, and Certified AI Professional Training at the University of Michigan

Explore the world of data with confidence. Gain essential skills in data analysis, scientific reasoning, and artificial intelligence to make informed decisions.

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Professional Certificate

Beginners

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Chance and statistics
  • artificial intelligence
  • Data Science
  • Data Analytics
  • Data literacy

What you will learn in the course

Courses for which the course is suitable

  • Data Analyst
  • Business Intelligence Analyst
  • Market Research Analyst
  • Statistician
  • Data Scientist
  • Research Scientist
  • Policy Analyst
  • Operations Analyst
  • Quality Assurance Analyst
  • Communications Specialist

Internship – a three-part course series

Understanding data

Navigating Statistics, Data, and AI equips you with the knowledge to engage with data from a deeper perspective and increase your impact as a decision maker in an increasingly data-averse world. Throughout this three-course series, you’ll develop essential data literacy skills to navigate evidence about data, statistics, science, and AI—without the need for math or programming.

Skills you will acquire
  • Learn to evaluate statistics found in headlines, advertisements, and studies.
  • Improve your critical thinking skills.
  • Understand how scientific research can be misunderstood and misinterpreted.
  • To look critically at current narratives about data and artificial intelligence.

By the end of the course series, you will be able to engage with data from a more critical perspective, integrate data and statistics into documents, reports, or stories, and actively support your opinions with quality data and information.

Tangible Learning Project

During this internship, you will participate in practical projects to apply your data literacy skills to real-world situations, such as assessing the credibility of claims involving statistics. The emphasis is on applying data literacy to real-world problems through practical projects and case studies.

Details of the courses that make up the specialization

How to describe data

Course 1

  • • 9 hours
Course Details
What you’ll learn
  • Learn the basics of interpreting, collecting, and summarizing data
  • Learn the capabilities and limitations of data and discuss criteria for determining which statistics are considered reliable.
  • Learn to interpret and evaluate the effectiveness of data visualizations
Skills you will acquire
  • Category: Probability and Statistics
  • Category: Data Literacy
  • Category: Data Analysis

How science turns data into knowledge

Course 2

  • • 11 hours
Course Details
What you’ll learn
  • Learn the principles and limitations of significance testing within a scientific investigation, including formulating hypotheses and interpreting p-values
  • Learn how scientific experiments are proposed, designed, tested, and published
  • Identify common biases and errors in scientific research reports and challenges in effectively communicating them to the general public
  • Evaluate the reliability of research claims and recognize the role of replication and generalization in scientific progress
Skills you will acquire
  • Category: Probability and Statistics
  • Category: Data Analysis
  • Category: Data Literacy

Decoding Artificial Intelligence: A Deep Dive into Models and Predictions

Course 3

  • • 10 hours
Course Details
What you’ll learn
  • Learn key concepts and terms in the field of artificial intelligence (AI), including machine learning, generative AI, and deep learning.
  • Learn the key components of machine learning systems, including data, models, and evaluation techniques
  • Recognize why IT systems may fail and identify the types of work needed to create useful technology
  • Identify common pitfalls in conversations about BM and recognize conflicts of interest when interpreting claims about BM systems
Skills you will acquire
  • Category: Artificial Intelligence
  • Category: Data Analysis
  • Category: Data Literacy
  • Category: Machine Learning