Programming for Data Science
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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.
Skills you'll gain
Tools you'll learn
Details to know
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There are 3 modules in this course
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.
This module introduces Python and Jupyter Notebook, as well as the concepts of variables, assignment and basic mathematical operators.
What's included
5 videos9 readings1 assignment1 discussion prompt1 ungraded lab
5 videos•Total 20 minutes
- Welcome to Programming for Data Science•2 minutes
- Learning to program•3 minutes
- Introduction to Python•4 minutes
- Introduction to Jupyter Notebook•6 minutes
- Python as a Calculator•6 minutes
9 readings•Total 36 minutes
- About this Course•2 minutes
- How to study on this course•4 minutes
- Our sustainability commitment for your course•10 minutes
- Program Development Environments•5 minutes
- Setting up Anaconda•3 minutes
- Variables and assignment•3 minutes
- Operators, functions and methods•5 minutes
- The math module•3 minutes
- Module 1 Summary•1 minute
1 assignment•Total 15 minutes
- Variable Assignment and Mathematical Operators•15 minutes
1 discussion prompt•Total 15 minutes
- Module 1 Reflection•15 minutes
1 ungraded lab•Total 10 minutes
- A first look at Jupyter Notebook•10 minutes
This module introduces the fundamental data types in Python, namely numbers, strings, Booleans and None. It also introduces structured data types, including lists, tuples, sets, dictionaries and classes.
What's included
2 videos18 readings1 assignment1 discussion prompt1 ungraded lab
2 videos•Total 7 minutes
- Overview of Basic data Types in Python•5 minutes
- Introduction to Structured data Types in Python•2 minutes
18 readings•Total 75 minutes
- Int, Float and Complex•5 minutes
- Mathematical Operators•8 minutes
- Numerical Comparisons•2 minutes
- Methods for int and float•2 minutes
- Introduction to Strings•4 minutes
- Indices and Slices•2 minutes
- String Comparisons and Methods•5 minutes
- f-strings•15 minutes
- Booleans•1 minute
- Comparisons•2 minutes
- Boolean Operators•10 minutes
- NoneType•1 minute
- Lists, Tuples and Sets•10 minutes
- Dictionaries•2 minutes
- Classes and Objects•1 minute
- Variable Types•2 minutes
- From Binary Digits to Complex Data Types•2 minutes
- Module 2 Summary•1 minute
1 assignment•Total 15 minutes
- Basic and Structured Data Types•15 minutes
1 discussion prompt•Total 15 minutes
- Module 2 Reflection•15 minutes
1 ungraded lab•Total 60 minutes
- Module 2 Exercise Solutions•60 minutes
What's included
2 videos16 readings1 assignment1 discussion prompt1 ungraded lab
2 videos•Total 4 minutes
- Introduction to Control Structures•2 minutes
- Introduction to Functions•2 minutes
16 readings•Total 114 minutes
- The If Statement•10 minutes
- The Elif Statement•10 minutes
- The Else Statement•10 minutes
- Nested Conditionals•10 minutes
- For Loops•10 minutes
- While Loops•10 minutes
- Nested Loops•10 minutes
- List Comprehension•5 minutes
- Defining a Function•2 minutes
- Calling a Function•3 minutes
- Exiting a Function•15 minutes
- Parameters•5 minutes
- Side Effects•1 minute
- Docstrings and Function Annotations•2 minutes
- Module 3 Summary•1 minute
- Future Steps•10 minutes
1 assignment•Total 60 minutes
- Conditionals, loops and functions•60 minutes
1 discussion prompt•Total 15 minutes
- Module 3 Reflection•15 minutes
1 ungraded lab•Total 60 minutes
- Module 3 Exercise Solutions•60 minutes
Prepare for a degree
Taking this course by University of Leeds may provide you with a preview of the topics, materials and instructors in a related degree program which can help you decide if the topic or university is right for you.
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Reviewed on Nov 13, 2023
Concise and good introductory course for anyone that might not be too familiar with Python. Quite easy for non-beginners, but that wasn't the target demographic anyway.
Reviewed on Oct 2, 2024
Good "taster" course... no technical/grading issues, very polished.
Frequently asked questions
This course is a taster to MSc Data Science (Statics) on Coursera. Completion of the course will not give you credit towards this programme. The course can be completed independently by any learners interested in programming and learning the basics of Python.
Yes, you will need to install Python on your computer in order to write programs.
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
More questions
Financial aid available,