University of Leeds - Programming for Data Science
- Offered byCoursera
Programming for Data Science at Coursera Overview
Duration | 8 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Programming for Data Science at Coursera Highlights
- Earn a certificate from University of Leeds
- Add to your LinkedIn profile
- September 2023
- 3 quizzes
Programming for Data Science at Coursera Course details
- What you'll learn
- Open Jupyter Notebook and use it to run Python code.
- Identify Python operators, data types and containers.
- Program control structures in Python, such as if statements and for and while loops.
- Write Python functions that take input and return output.
- Explore the basics of programming and familiarise yourself with the Python language. After completing this course, you will be able to write Python programs in Jupyter Notebook and describe basic programming.
- In this course, you will learn everything you need to start your programming journey. You will discover the different data types available in Python and how to use them, learn how to apply conditional and looping control structures, and write your own functions.
- This course provides detailed descriptions of new concepts and background information for additional context. The quizzes available will help you to develop your understanding. You will also complete exercises using Jupyter Notebook on your computer. By using Jupyter Notebook, you will be able to combine your notes with useful examples so that you develop the resources you need to program independently in the future.
- This course is a taster of the Online MSc in Data Science (Statistics) but it can be completed by learners who want an introduction to programming and explore the basics of Python.
Programming for Data Science at Coursera Curriculum
First steps with Python
Welcome to Programming for Data Science
Learning to program
Introduction to Python
Introduction to Jupyter Notebook
Python as a Calculator
About this Course
How to study on this course
Program Development Environments
Setting up Anaconda
Variables and assignment
Operators, functions and methods
The math module
Module 1 Summary
Variable Assignment and Mathematical Operators
Module 1 Reflection
A first look at Jupyter Notebook
Data Types in Python
Overview of Basic data Types in Python
Introduction to Structured data Types in Python
Int, Float and Complex
Mathematical Operators
Numerical Comparisons
Methods for int and float
Introduction to Strings
Indices and Slices
String Comparisons and Methods
f-strings
Booleans
Comparisons
Boolean Operators
NoneType
Lists, Tuples and Sets
Dictionaries
Classes and Objects
Variable Types
From Binary Digits to Complex Data Types
Module 2 Summary
Basic and Structured Data Types
Module 2 Reflection
Module 2 Exercise Solutions
Control Structures and Functions
Introduction to Control Structures
Introduction to Functions
The If Statement
The Elif Statement
The Else Statement
Nested Conditionals
For Loops
While Loops
Nested Loops
List Comprehension
Defining a Function
Calling a Function
Exiting a Function
Parameters
Side Effects
Docstrings and Function Annotations
Module 3 Summary
Future Steps
Conditionals, loops and functions
Module 3 Reflection
Module 3 Exercise Solutions
Programming for Data Science at Coursera Admission Process
Important Dates
Other courses offered by Coursera
Student Forum
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