Introduction to Python Functions
Master Python functions from basics to advanced concepts, including parameters, return values, and nested functions. Perfect for data science beginners.
Master Python functions from basics to advanced concepts, including parameters, return values, and nested functions. Perfect for data science beginners.
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.
4.8
(43 ratings)
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What you'll learn
Use predefined functions in Python and Python packages
Define custom Python functions for specific tasks
Work with function parameters and return values
Implement nested and recursive functions
Create hierarchical function structures
Skills you'll gain
This course includes:
3 Hours PreRecorded video
11 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 Python functions, essential for data science programming. Starting with basic function definitions, it progresses through parameters, return values, and nested functions. The curriculum combines theoretical concepts with practical applications, featuring interactive labs and hands-on assignments. Students learn to create reusable and adaptive programs through function implementation, preparing them for real-world data science projects.
Hello, functions!
Module 1 · 5 Hours to complete
Functions with Parameters
Module 2 · 5 Hours to complete
Functions with Return Values
Module 3 · 3 Hours to complete
Functions in Functions
Module 4 · 5 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.
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4.8 course rating
43 ratings
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