More Applied Data Science with Python
Description
In our increasingly interconnected world, we’re collecting more raw data than ever. In “More Applied Data Science with Python,” you’ll learn how to extract and analyze complex data sets using Python. Practice using real-world data sets, like health data and comment sections, to develop visual representations and identify key patterns amongst populations. You’ll also learn to manage missing and messy data using advanced manipulation methods. Throughout this course series, you’ll build a foundation for advanced analytics and machine learning with the help of Scikit-Learn and NLP libraries by applying methods for data mining, clustering, topic modeling, network modeling, and information extraction. Upon completing the series, you'll have gained advanced data analysis skills that will help you gain insights into the datasets you're exploring.
Learners should have intermediate Python programming skills before enrolling in the Specialization. It is encouraged that you complete Applied Data Science with Python prior to beginning this Specialization.
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Subjects
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Language
English
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Duration
14 weeks
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Status
Available
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U-M Credit Eligible
No
Instructors
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Kevyn Collins-Thompson
Associate Professor
School of Information
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Qiaozhu Mei
Professor
School of Information
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Daniel Romero
Associate Professor
School of Information
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V.G. Vinod Vydiswaran
Associate Professor
School of Information
Courses (4)
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Learn moreData Mining in Python
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4 weeks
In “Data Mining in Python,” you will learn how to extract useful knowledge from large-scale datasets. This course introduces basic concepts and general tasks for data mining. You will explore a wide r -
Learn moreApplied Unsupervised Learning in Python
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4 weeks
In “Applied Unsupervised Learning in Python,” you will learn how to use algorithms to find interesting structure in datasets. You will practice applying, interpreting, and refining unsupervised machin -
Learn moreNetwork Modeling and Analysis in Python
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3 weeks
In “Network Modeling and Analysis in Python,” you will learn how different types of network analysis can be used to make sense of complex systems. You’ll learn how algorithms can be used to better und -
Learn moreApplied Information Extraction in Python
3 weeks
In “Applied Information Extraction in Python,” you will learn how to extract useful information from free-text data, which is a type of string data created when people type. Examples of free-text data
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