Duke University - Python Programming Fundamentals
- Offered byCoursera
Python Programming Fundamentals at Coursera Overview
Duration | 23 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Python Programming Fundamentals at Coursera Highlights
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Coursera Labs Includes hands on learning projects. Learn more about Coursera Labs External Link
- Beginner Level A solid understanding of algebra and the ability to recognize patterns.
- Approx. 23 hours to complete
- English Subtitles: English
Python Programming Fundamentals at Coursera Course details
- This introductory course is designed for beginners and individuals with limited programming experience who want to embark on their software development or data science journey using Python. Throughout the course, learners will gain a solid understanding of algorithmic thinking, Python syntax, code testing, debugging techniques, and modular code development--essential skills for a successful career in software engineering, development, or data science.
- By the end of this course, you will learn to:
- - Gain a stepwise approach to problem-solving using algorithms and programming logic.
- - Apply common functions, conditional statements, and loops to build Python scripts and programs.
- - Work with the VS Code programming environment to enhance coding proficiency.
- - Use testing and debugging strategies to ensure code reliability.
- - Perform logical and mathematical operations on datasets.
- In the final week of the course you will apply your new algorithm design and programming skills to a data analysis problem: analyzing heart rate data.
Python Programming Fundamentals at Coursera Curriculum
Algorithm Design
Introduction to Python Programming Fundamentals
Stepping Through an Algorithm
Testing an Algorithm for a Numerical Sequence
A Pattern of Squares
Testing a Pattern of Squares
Drawing a Rectangle
Closest Point
Generalizing Closest Point
Everything is a Number
Plan First, Then Code
Overview of the 7 Steps
Algorithms
Step 1: Work an Example Yourself
Step 2: Write Down What You Just Did
Step 3: Generalize Your Steps
Step 4: Test Your Algorithm
Intro to a Pattern of Squares
Non-Numbers
Algorithm Design
Algorithms Quiz
Numbers and Types Quiz
Translating Ideas into Code
Semantics: What Does Code Mean?
Variables and Expressions
Functions
Printing
Conditional Statements
Loops
Revisiting Intersection of Two Rectangles
Planning isPrime
Generalizing isPrime
Translating isPrime to Code
Tuples
Why VS Code
Intro Lab
First Four Steps Revisited
Translating Algorithms to Code
Ending Blocks with Pass
Top Down Design and Composability
Stars Example
Introduction to VS Code
How to Reset Lab Files
Retirement Calculations
Read Function 1
Reading Code Assignments
Reviewing the First four Steps of Algorithm Design
Translating an Algorithm to Code
Understanding Retirement
Validating Your Code
Testing Means Finding Bugs
Test-Driven Approaches
Test-Driven Development
Code Review
Debugging: The Scientific Method
Debugging: Hypotheses
Black Box Testing
White Box Testing
Creating Test Cases
Asserts
Code Review
Introduction to Debugging Tools
Principles and Tools for Debugging
Debugging Python in VS Code
Tests Prime
Tests countMostCommon
Testing Code
Diving Deeper with Lists
Lists: References to Mutable Objects
Lists: Iteration
Lists: Indexing and Slicing
Heart Rate Introduction
Heart Rate Peaks
Heart Rate Code
Heart Rate isPeakAt
Default Arguments Revisited
Heart Rate Example Introduction
Moving Averages
Subsequence Test Cases
Python Programming Fundamentals at Coursera Admission Process
Important Dates
Other courses offered by Coursera
Student Forum
Anything you would want to ask experts?