Introduction to Python Fundamentals
Learn Python programming basics including variables, data types, and flow control. Perfect for complete beginners.
Learn Python programming basics including variables, data types, and flow control. Perfect for complete 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.
4.7
(131 ratings)
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What you'll learn
Understand basic programming concepts and Python syntax
Work with variables and different data types
Implement input/output operations
Use conditional statements and flow control
Create simple interactive Python programs
Master fundamental programming logic
Skills you'll gain
This course includes:
2.8 Hours PreRecorded video
22 quizzes, 4 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This beginner-friendly course introduces fundamental Python programming concepts at a comfortable pace. Students learn essential programming basics including variables, data types, and flow control structures. The curriculum covers both theoretical concepts and practical applications, with hands-on coding exercises and interactive assignments. Special emphasis is placed on building a strong foundation in programming logic and syntax through step-by-step instruction and practice.
Hello, Python
Module 1 · 4 Hours to complete
Variables and Operations
Module 2 · 5 Hours to complete
Flow Control - Branching
Module 3 · 5 Hours to complete
Flow Control - Repetition
Module 4 · 4 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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4.7 course rating
131 ratings
Frequently asked questions
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