Python Programming Fundamentals

Python Programming Fundamentals

This course is part of Programming for Python Data Science: Principles to Practice Specialization

Instructors: Andrew D. Hilton

Access provided by Samsung Semiconductor, Inc

21,563 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

67 reviews

Beginner level

No prior experience required

Flexible schedule

3 weeks at 10 hours a week

Learn at your own pace

88%

Most learners liked this course

4 modules

Gain insight into a topic and learn the fundamentals.

67 reviews

Beginner level

No prior experience required

Flexible schedule

3 weeks at 10 hours a week

Learn at your own pace

88%

Most learners liked this course

What you'll learn

Create algorithms and programs using a logical Seven Step framework.
Create useful test cases and efficiently debug Python code.
Apply Python basics (conditionals, loops, mathematical operators, data types) to build a Python program from scratch to solve a data science problem.

Skills you'll gain

Tools you'll learn

Python Programming

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

13 assignments¹

AI Graded see disclaimer

Taught in English

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This course is part of the Programming for Python Data Science: Principles to Practice Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 4 modules in this course

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.

This module, you will learn best practices for developing code in any language by beginning with an algorithm: a stepwise approach to solving a problem. You’ll then apply the concepts by developing your own algorithms and properly identifying when to use specific data types in Python.

What's included

9 videos12 readings4 assignments

9 videos Total 37 minutes

Introduction to Python Programming Fundamentals 4 minutes
Stepping Through an Algorithm 4 minutes
Testing an Algorithm for a Numerical Sequence 3 minutes
A Pattern of Squares 5 minutes
Testing a Pattern of Squares 2 minutes
Drawing a Rectangle 4 minutes
Closest Point 5 minutes
Generalizing Closest Point 5 minutes
Everything is a Number 6 minutes

12 readings Total 120 minutes

Plan First, Then Code 10 minutes
Overview of the 7 Steps 10 minutes
Algorithms 10 minutes
Report a problem with the course 10 minutes
Step 1: Work an Example Yourself 10 minutes
Step 2: Write Down What You Just Did 10 minutes
Step 3: Generalize Your Steps 10 minutes
Step 4: Test Your Algorithm 10 minutes
Intro to a Pattern of Squares 10 minutes
About the Duke AI-graded Questions Pilot 10 minutes
Give us your feedback on the AI-graded Questions tool 10 minutes
Non-Numbers 10 minutes

4 assignments Total 105 minutes

Algorithms Quiz 30 minutes
Algorithm Design 30 minutes
Algorithm for Counting Even Integers 30 minutes
Numbers and Types Quiz 15 minutes

This Module, you will learn how to take the logical process of algorithm design and translate an algorithm into functional Python code. You will apply this by correctly identifying proper Python syntax for a given algorithm, and then subsequently by creating your own Python program for a given algorithm.

What's included

13 videos8 readings5 assignments4 programming assignments

13 videos Total 58 minutes

Semantics: What Does Code Mean? 2 minutes
Variables and Expressions 4 minutes
Functions 5 minutes
Printing 4 minutes
Conditional Statements 4 minutes
Loops 5 minutes
Revisiting Intersection of Two Rectangles 5 minutes
Planning isPrime 4 minutes
Generalizing isPrime 5 minutes
Translating isPrime to Code 4 minutes
Tuples 7 minutes
Why VS Code 4 minutes
Intro Lab 6 minutes

8 readings Total 95 minutes

First Four Steps Revisited 20 minutes
Translating Algorithms to Code 10 minutes
Ending Blocks with Pass 10 minutes
Top Down Design and Composability 10 minutes
Stars Example 10 minutes
Introduction to VS Code 15 minutes
How to Reset Lab Files 10 minutes
Retirement Calculations 10 minutes

5 assignments Total 150 minutes

Reading Code Assignments 30 minutes
Read Function 1 30 minutes
Reviewing the First four Steps of Algorithm Design 30 minutes
Translating an Algorithm to Code 30 minutes
Understanding Retirement 30 minutes

4 programming assignments Total 180 minutes

Max 25 minutes
Triangle 35 minutes
Retirement 100 minutes
Intro To Coursera Lab Programming Assignments 20 minutes

This module, you will learn different approaches to testing Python code, and methods for debugging code. You will apply this by conducting a code review, identifying opportunities to use asserts to debug code, and generating your own test cases.

What's included

6 videos8 readings3 assignments

6 videos Total 27 minutes

Testing Means Finding Bugs 2 minutes
Test-Driven Approaches 7 minutes
Test-Driven Development 2 minutes
Code Review 3 minutes
Debugging: The Scientific Method 6 minutes
Debugging: Hypotheses 7 minutes

8 readings Total 85 minutes

Black Box Testing 10 minutes
White Box Testing 10 minutes
Creating Test Cases 10 minutes
Asserts 10 minutes
Code Review 10 minutes
Introduction to Debugging Tools 10 minutes
Principles and Tools for Debugging 15 minutes
Debugging Python in VS Code 10 minutes

3 assignments Total 90 minutes

Tests Prime 30 minutes
Tests countMostCommon 30 minutes
Testing Code 30 minutes

This module, you will learn how to filter and perform operations (logical and mathematical) across a given dataset, and how to create modular code that can be used in discrete pieces. You will apply this by writing your own functions to identify a list item with a given property, and writing a program to calculate a set of conclusions from a given dataset.