UCT GSB - Julia Scientific Programming
- Offered byCoursera
Julia Scientific Programming at Coursera Overview
Duration | 18 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Julia Scientific Programming at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Beginner Level
- Approx. 18 hours to complete
- English Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Julia Scientific Programming at Coursera Course details
- This four-module course introduces users to Julia as a first language. Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing. This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics and many more. As open source software, you will always have it available throughout your working life. It can also be used from the command line, program files or a new type of interface known as a Jupyter notebook (which is freely available as a service from JuliaBox.com).
- Julia is designed to address the requirements of high-performance numerical and scientific computing while also being effective for general-purpose programming. You will be able to access all the available processors and memory, scrape data from anywhere on the web, and have it always accessible through any device you care to use as long as it has a browser. Join us to discover new computing possibilities. Let's get started on learning Julia.
- By the end of the course you will be able to:
- - Programme using the Julia language by practising through assignments
- - Write your own simple Julia programs from scratch
- - Understand the advantages and capacities of Julia as a computing language
- - Work in Jupyter notebooks using the Julia language
- - Use various Julia packages such as Plots, DataFrames and Stats
- The course is delivered through video lectures, on-screen demonstrations, quizzes and practical peer-reviewed projects designed to give you an opportunity to work with the packages.
Julia Scientific Programming at Coursera Curriculum
Welcome to the course
Introduction to Julia scientific programming
Julia version 1.0
Programming languages and why Julia is special
Getting Ready: Julia programming environments
The Julia REPL - Read, Evaluate and Print Loop
Arithmetical expressions
Logical expressions
Julia's Type System
Variables in Julia
Functions in Julia
User-defined functions - part 1
User-defined functions - part 2
Week 1: Getting Practice
Installing Juno using Julia
Installing Julia Pro
How this course works
What to expect from Week 1
Using Jupyter Notebooks
Logical expressions
Multiple Dispatch in Julia
Approach to assessment in course
Is this course right for me?
Julia REPL and the notebook
Arithmetical and logical expressions in Julia
Types and Arrays in Julia
Julia functions
Week 1 - Graded Quiz
What makes Julia special?
A context for exploring Julia: Working with data
Introduction to Week 2
The Ebola Epidemic of 2014
Loading data using Julia
Creating .csv from data tables
For Loops and Date-Time Formats
Simple plots with the Plots package
Multiple curves in a single diagram
Week 2: Getting Practice
How to do a Peer Graded Assignment
What to expect from Week 2
Data and Loops in Julia
Plots in Julia
Week 2 - Graded Quiz
Notebooks as Julia Programs
Introduction to Week 3
SIR Models of Disease Dynamics
The SIR model in Julia code
More on SIR Models
Plotting Data and an Approximately Fitted Line Simultaneously
Using the Data - fitting the model parameters
Week 3: Getting practice
Practicing fitting a circle to data
Week 3: Wrap Up
What to expect from Week 3
Making simple models
Models
Structuring data and functions in Julia
Using Julia for descriptive statistics
Installing packages for this lesson
Creating simulated data
Descriptive statistics
Creating a dataframe
Descriptive statistics
Visualizing data
Inferential statistics
Exporting data as a csv file
What to expect from Week 4
Package installation and troubleshooting in Julia
Week 4: Wrap-up
Honors material
Week 4 - Graded Quiz
Collections
Functions
Julia Scientific Programming at Coursera Admission Process
Important Dates
Other courses offered by Coursera
Student Forum
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