Learn to leverage AI tools like ChatGPT for data analysis, from acquisition to visualization, in this practical course.
Learn to leverage AI tools like ChatGPT for data analysis, from acquisition to visualization, in this practical course.
Discover how AI is revolutionizing data analysis in this beginner-friendly course. Learn to harness generative AI tools like ChatGPT to streamline your data analysis workflow, from data acquisition and cleaning to advanced visualization. This practical introduction covers fundamental concepts of data management, analysis techniques, and visualization strategies, all enhanced by AI capabilities. You'll gain hands-on experience with real-world datasets and learn to use Jupyter notebooks for your projects. The course culminates in setting up a GitHub repository, preparing you for continued learning and collaboration in the data science community.
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What you'll learn
Understand the fundamentals of data analysis and its importance in today's AI-driven world
Learn to use generative AI tools like ChatGPT for data acquisition and analysis ideas
Gain practical skills in data cleaning, organization, and preprocessing using AI assistance
Develop proficiency in performing basic statistical analyses with AI support
Create effective data visualizations using AI-powered tools and techniques
Understand the principles of version control and learn to use GitHub for data projects
Skills you'll gain
This course includes:
0.5 Hours PreRecorded video
3 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 3 modules in this course
This course provides a practical introduction to AI-powered data analysis, focusing on leveraging generative AI tools like ChatGPT to enhance data analysis skills. Learners will explore the fundamentals of data management, analysis techniques, and visualization strategies, all while using AI to streamline their workflow. The curriculum covers data acquisition, cleaning, analysis, and visualization, with hands-on experience using real-world datasets and Jupyter notebooks. By the end of the course, students will be equipped to use AI tools effectively for data analysis projects and will have set up a GitHub repository for continued learning and collaboration.
Laying the Groundwork: Data Foundations
Module 1 · 1 Hours to complete
Building Skills: Essential Practice
Module 2 · 1 Hours to complete
Finishing Touches: Supporting Skills & Next Steps
Module 3 · 1 Hours to complete
Fee Structure
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Instructor
Innovator in Human Variation and Biometric Technology
Dr. Tina Lasisi is an Assistant Professor in the Department of Anthropology at the University of Michigan, where she specializes in measuring human traits such as skin color, hair texture, and facial morphology to explore their genetic and evolutionary origins. Her research focuses on developing novel laboratory methods and automated image analysis programs that significantly impact fields like dermatology, forensics, and biometric technologies, including facial recognition. Dr. Lasisi is affiliated with various departments and programs, including Ecology and Evolutionary Biology and the Center for Computational Medicine & Bioinformatics.Recognized by Science News as one of "10 Scientists to Watch" and by Popular Science’s "Brilliant 10," Dr. Lasisi is also committed to science communication, collaborating with platforms like PBS and Science Friday to enhance public understanding of human biological diversity. She teaches courses such as "AI-Powered Data Analysis: A Practical Introduction," integrating her expertise in genetics with modern data analysis techniques.
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