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Data Mining in Python

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...

By Qiaozhu Mei on Coursera

About This Course

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 range of real-world data sets, including grocery store, restaurant reviews, business operations, social media posts, and more. You will learn how to formally describe real-world information with general data representations (e.g., itemsets, vectors, matrices, sequences, and more). You will then learn how to formulate data in the wild with one or more of these representations. This course will teach you how to characterize and explain your data by looking for patterns and similarities, which are basic building blocks for advanced analysis and machine learning models. This is the first course in “More Applied Data Science with Python,” a four-course series focused on helping you apply advanced data science techniques using Python. It is recommended that all learners complete the Applied Data Science with Python specialization prior to beginning this course.

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Frequently Asked Questions

How much does Data Mining in Python cost?

Visit the Data Mining in Python course page for current pricing and available discounts.

Who teaches Data Mining in Python?

Data Mining in Python is taught by Qiaozhu Mei, University of Michigan.

What skill level is Data Mining in Python for?

This course is designed for advanced learners.

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Students0
Duration5 hours
LevelAdvanced
Languageen
PlatformCoursera
InstructorQiaozhu Mei