About this course: 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.

Who is this class for: This course is for anyone wanting to learn how to use Julia for data analysis. This includes data scientists, engineers, mathematical modelling and students looking for new tools to work with data. Recommended Background A knowledge of high school mathematics is a basic requirement. While the class is designed for students with limited programming experience, some beginner programmers may find the class quite fast-paced. We recommend you work through the material slower, never forgetting that the only way to learn a language is to use it. We use Jupyter notebooks for the course and we encourage you to experiment with the notebooks we have created. For those of you who have done programming and want to get a taste of this language, you should be able to move through the material fast.

Created by: University of Cape Town

Taught by: Juan H Klopper, Dr
Department of Surgery
Taught by: Henri Laurie, Dr
Department of Mathematics and Applied Mathematics

Level	Beginner
Commitment	4 weeks of study, 3-4 hours per week
Language	English
How To Pass	Pass all graded assignments to complete the course.
User Ratings	4.6 stars Average User Rating 4.6See what learners said

Syllabus

WEEK 1

Welcome to the course

A warm welcome to Julia Scientific Programming. Over the next four weeks, we will provide you with an introduction to what Julia can offer. We have created a course which we hope will allow you to learn the basics of the language, and stimulate your imagination about how you can use Julia in your own context. This course is all about you exploring Julia - we can only demonstrate some of the capacity and encourage you to take the first steps. For those of you with a programming background, the course is intended to offer a jumpstart into using this language. If you are a novice or beginner programmer, you should follow along the simple coding but recognising that working through the material will not be sufficient to make you a proficient programmer in four weeks. You could see this as the ‘first date’ at the beginning of a long and beautiful new relationship. There is so much you will need to learn and discover. Good luck and we hope you enjoy the course! Best wishes, Henri and Juan

16 videos, 4 readings, 6 practice quizzes

Video: Introduction to Julia scientific programming
Reading: How this course works
Practice Quiz: Is this course right for me?
Reading: What to expect from Week 1
Discussion Prompt: Meet and greet
Video: Programming Languages and why Julia is special
Video: Getting Ready: JuliaBox Part 1
Reading: Using Jupyter Notebooks
Video: Getting Ready: JuliaBox Part 2
Video: The Julia REPL - Read, Evaluate and Print Loop
Practice Quiz: JuliaBox and the Julia REPL
Video: Arithmetic Expressions
Video: Logical expressions
Practice Quiz: Arithmetic and logical expressions in Julia
Video: Types: Julia Type System
Video: Arrays and Abstract types
Practice Quiz: Types and Arrays in Julia
Video: Functions I - built-in functions
Video: Functions II - user-defined functions
Practice Quiz: Julia functions
Video: Week 1: Getting Practice
Reading: Approach to assessment in course
Video: How to Install Julia on Mac OS X
Video: Installing Julia on Linux
Video: Installing Julia on Windows
Video: Opening notebooks in IJulia
Practice Quiz: What makes Julia special?

Graded: Week 1 Graded Quiz

WEEK 2

A context for exploring Julia: Working with data

In our case study we use Julia to store, plot, select and slice data from the Ebola epidemic. Taking real data, we explain how to work in Julia using arrays, and for loops to work with the structures. By the end of this module, you will be able to: create an array from data; learn to use the logical structures IF and FOR ; conduct basic array slicing, getting the incidence data and generating total number of cases; use Plots to generate graphs and plot data; and combine the Ebola data outputs to show a plot of disease incidence in several countries.

9 videos, 1 reading, 2 practice quizzes

Reading: What to expect from Week 2
Video: Introduction to Week 2
Video: The Ebola Epidemic of 2014
Video: Loading data
Video: Creating CSV files (Optional)
Video: "For" Loops and data format conversions
Practice Quiz: Data and Loops in Julia
Video: Simple Plots with the Plots Package
Video: Plotting Multiple Curves in a Single Diagram
Practice Quiz: Plots in Julia
Video: Week 2: Getting Practice
Video: How to do a Peer Graded Assignment
Peer Review: Creating a Notebook to describe a function (Optional)

Graded: Week 2 - Graded quiz

WEEK 3

Notebooks as Julia Programs

in this week, we demonstrate how it is possible to use Julia in the notebook environment to interpret a model and its fit to the data from the Ebola outbreak. For this, we apply the well-known SIR compartmental model in epidemiology. The SIR model labels three compartments, namely S = number susceptible, I =number infectious, and R =number recovered. By the end of this module, you will be able to: understand the SIR models; describe the basic parameters of an SIR model; plot the model-predicted curve and the data on the same diagram; adjust the parameters of the model so the model-predicted curve is close (or rather as close as you can make it) to the data.

16 videos, 1 reading, 2 practice quizzes

Reading: What to expect from Week 3
Video: Introduction to Week 3
Video: SIR Models of Disease Dynamics
Video: More on SIR Models
Practice Quiz: Making simple models
Video: Plotting Data
Video: Using the Data: A rough fit of the model parameters
Practice Quiz: Models
Video: Week 3 Getting practice
Video: Practicing fitting a circle to data
Video: Week 3 Wrap Up
Video: User Defined Types: Introduction
Video: User Defined Types: The Julia Type System & Declaring a Type
Video: User Defined Types: Creating Your Own Type
Video: User Defined Types: Conversion & Promotion & Parametrizing a Type
Video: User Defined Types: Equality of Values & Types & Defining Methods for User Types
Video: User Defined Types: More Complex Parameters
Video: User Defined Types: Screen Output of User Defined Types
Video: User Defined Types: Constraining Field Values

Graded: Plotting data and fitting a curve

Graded: User-defined types (Honors)

WEEK 4

Structuring data and functions in Julia

As a scientific computing language, Julia is well suited to the task of working with data. In this last module, we elaborate on the two most important concepts in Julia, arrays and functions. They are the fundamental building blocks of holding and manipulating data. You should see this week as offering you a chance to further explore concepts introduced in week one and two. You will also be introduced to more efficient ways of managing and visualizing your data. By the end of this module, you will be able to: 1. Apply and understand how to work with arrays 2. Practice Julia functions 3. Explore extension packages 4. be familiar with the Dataframes package 5. Plot a variety of data from the dataset, ready for publication.

35 videos, 3 readings, 3 practice quizzes

Reading: What to expect from week 4
Reading: Packages - Local installation of Julia vs. juliabox.com
Video: Collections: Introduction
Video: Collections: Creating Arrays
Video: Collections: Slicing & Modifying Arrays
Video: Collections: Comprehensions & Operations
Video: Collections: Additional - NA & Tuples
Video: Collections: Additional - Dictionaries
Video: Collections: Recap
Practice Quiz: Collections
Video: Functions: Introduction
Video: Functions: Single & Multiple expression functions
Video: Functions: Optional & Keyword Arguments
Video: Functions: Variable Number of Arguments
Video: Functions: Additional Passing Arrays as Arguments & Type Parameters
Video: Functions: Additional - Stabby Functions & Passing Functions as Arguments
Video: Functions: Recap
Practice Quiz: Functions
Video: Data Frames: Introduction
Video: Data Frames: Data Arrays & Data Frames
Video: Data Frames: Get to Know your Data
Video: Data Frames: Importing & Exporting
Video: Data Frames: Joins & Groups
Video: Data Frames: Sorting, Duplicates & NA
Video: Data Frames: Renaming Columns
Video: Data Frames: Recap
Video: Data: Introduction
Video: Data Vizualization: Randn & Distributions
Practice Quiz: DataFrames and Data Visualizations
Reading: Completing the course
Video: Data Vizualization: Comparison
Video: Data Vizualization: Plotly
Video: Data Vizualization: Recap
Video: Gadfly: Introduction
Video: Gadfly: Simple plotting & Adding Layers
Video: Gadfly: Using Themes
Video: Gadfly: Adding Titles and Axis Labels & Saving a Plot & Importing Data into a DataFrame
Video: Gadfly: Box Plots
Video: Gadfly: Density Plots & Histogram & Violin Plots
Video: Gadfly: QQ Plots & Scatter Plots & Vertical and Horizontal Lines
Video: Gadfly: More Examples

Graded: Working with Distributions and DataFrames

Graded: Working with data (Honors)

Graded: Gadfly (Honors)

FAQs

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Creators

University of Cape Town

The University of Cape Town is the oldest university in South Africa and is one of the leading research universities on the African continent. UCT has over 25 000 students, of whom 30% are postgraduate students. We offer degrees in six faculties: Commerce, Engineering & the Built Environment, Health Sciences, Humanities, Law, and Science. We pride ourself on our diverse student body, which reflects the many cultures and backgrounds of the region. We welcome international students and are currently home to thousands of international students from over 100 countries. UCT has a tradition of academic excellence that is respected world-wide and is privileged to have more than 30 A-rated researchers on our staff, all of whom are recognised as world leaders in their field. Our aim is to ensure that our research contributes to the public good through sharing knowledge for the benefit of society. Past students include five Nobel Laureates – Max Theiler, Alan Cormack, Sir Aaron Klug, Ralph Bunche and, most recently, J M Coetzee.

Pricing

	Audit	Purchase Course
Access to course materials	Available	Available
Access to graded materials	Not available	Available
Receive a final grade	Not available	Available
Earn a shareable Course Certificate	Not available	Available

Ratings and Reviews

Rated 4.6 out of 5 of 65 ratings

It was very exciting. I widen further, my computing horizons

Hope, that the university will launch in the near future, a more advanced course of "Julia Scientific Programming"

The course started out well wit goof balance between lectures and applications during the first three weeks. Towards the end it felt rushed with too much content crammed into the last week.

The best thorough course for the foundations in analysis in Julia. I have not found any easy and complete explanation of Julia basics than this course. I completed the books Julia for Data Science by Anshul Joshi and other by Zacharias Voulgaris but they did not have as a solid foundation as this course has provided. Those books show more complex examples which will be easier to solve and understand after taking this course than the foundation provided in those books. Worth every penny for beginners to learn and experts to improve or polish their knowledge in Julia. Best course for beginners/expert I have ever had in my programming career.

Amazing course, introduces the Julia Programming Language in a very intuitive way. Honor Assignments are a great bonus that give a more in-depth Julia experience. Highly recommended for anyone entering the Julia landscape.

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