Python Packages for Data Science
Master essential Python packages like NumPy, Pandas, Matplotlib, and Seaborn for data analysis and visualization.
Master essential Python packages like NumPy, Pandas, Matplotlib, and Seaborn for data analysis and visualization.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Expressway to Data Science: Python Programming Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.4
(44 ratings)
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What you'll learn
Master data manipulation with NumPy and Pandas
Create effective visualizations using Matplotlib
Enhance data presentation with Seaborn
Apply Python packages to real data science tasks
Develop practical data analysis skills
Skills you'll gain
This course includes:
2.73 Hours PreRecorded video
8 quizzes, 4 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course focuses on essential Python packages used in data science. Students learn to manipulate data using NumPy and Pandas, create visualizations with Matplotlib and Seaborn, and develop practical skills through hands-on exercises. The curriculum is designed for learners with basic Python knowledge who want to advance their data science capabilities through popular packages and practical applications.
Hello, packages!
Module 1 · 4 Hours to complete
Data Manipulation: Numpy and Pandas
Module 2 · 8 Hours to complete
Data Visualization: Matplotlib
Module 3 · 3 Hours to complete
Data Visualization: Seaborn
Module 4 · 3 Hours to complete
Fee Structure
Instructor
Teaching Assistant Professor
Dr. Di Wu is a Teaching Assistant Professor at the University of Colorado Boulder, specializing in data science and computer science. His primary research interests include temporal databases, the semantic web, knowledge representation, and data science, with a focus on extending the Resource Description Framework (RDF) for temporal dimensions. Before joining CU Boulder, he taught various courses such as algorithms and data structures, programming languages, and database management. Dr. Wu aims to develop an inclusive and engaging pedagogy in data science education over the next five years, emphasizing experiential learning in both in-person and online formats. He is involved in teaching courses related to data science and programming, including specializations in Python programming for data scientists.
Testimonials
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4.4 course rating
44 ratings
Frequently asked questions
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