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
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Introduction to Data Science in Python
This course is part of Applied Data Science with Python Specialization
Instructor: Christopher Brooks
860,083 already enrolled
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Gain insight into a topic and learn the fundamentals.
27,281 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
- Scripting Languages
- Data Science
- Data Import/Export
- Data Processing
- Data Transformation
- Statistical Methods
- Data Manipulation
- Data-Driven Decision-Making
- Statistical Analysis
- Data Wrangling
- Data Cleansing
- Pivot Tables And Charts
- Text Mining
- Data Preprocessing
- Probability & Statistics
- Data Analysis
- Programming Principles
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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(3,904 ratings)15 Courses963,644 learners
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Showing 3 of 27281
KL
Reviewed on Mar 11, 2018
A very nice introduction to libraries/skills used by data scientists. The auto-grader was extremely annoying though. Also, I felt that some of the questions on the assignments were a bit ambiguous.
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.
DR
Reviewed on Aug 24, 2017
The course is good but the oral explanations are at times very tiresome. A more constructive approach in which the explanations are followed by step-by-step examples whould be far better.Best regards
