This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.
Introduction to Data Science in Python
Introduction to Data Science in Python
This course is part of Applied Data Science with Python Specialization
Instructor: Christopher Brooks
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27,283 reviews
Intermediate level
Some related experience required
Flexible schedule
3 weeks at 10 hours a week
Learn at your own pace
92%
Most learners liked this course
What you'll learn
Understand techniques such as lambdas and manipulating csv files
Describe common Python functionality and features used for data science
Query DataFrame structures for cleaning and processing
Explain distributions, sampling, and t-tests
Skills you'll gain
- Data Science
- Statistical Analysis
- Data Cleansing
- Data Manipulation
- Data Import/Export
- Scripting Languages
- Pivot Tables And Charts
- Data Wrangling
- Data Transformation
- Programming Principles
- Data Analysis
- Probability & Statistics
- Statistical Methods
- Data-Driven Decision-Making
- Data Processing
- Data Preprocessing
- Text Mining
Tools you'll learn
Details to know
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Assessments
9 assignments
Taught in English
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This course is part of the Applied Data Science with Python Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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Showing 3 of 27283
ME
Reviewed on Jul 26, 2020
Quizzes were very challenging and interesting. I learned alot. The main drawback in this course is that the materials are insufficient to answer the assignments.And some questions were not so clear.
TG
Reviewed on Apr 13, 2020
Awesome course! I haven't done any course like this. Explanations were very clear and deep, which is very helpful to learn the content. Thanks a lot to the professor and the University of Michigan.
AM
Reviewed on Sep 24, 2017
This course is extremely challenging for me I was practicing data wrangling with R which is not a lot different in concepts but it gets very tricky especially with indexing.Thanks for the Experience!
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