In this guide, I’ve selected the best free and paid online courses, resources, and tutorials to learn Julia based on Julia courses from the Class Central catalog. Most of the courses are free or free-to-audit, and two of them offer a free certificate upon completion with options for beginners and for more experienced programmers from JuliaAcademy with renowned lecturers.

Here are my top picks. Click on one to skip to the course details:

Course	Workload	In Brief
1. Julia Programming for Nervous Beginners (JuliaAcademy)	7–8 hours	Best introductory Julia course for complete beginners to programming with free certificate
2. Introduction to Julia (for programmers) (JuliaAcademy)	1–2 hours	Best Julia course for experienced programmers with free certificate
3. Julia Scientific Programming (Cape Town)	12–16 hours	Best Julia course for complete beginners with a focus on scientific programming
4. Julia for Beginners (julia for talented amateurs)	6 hours	Best YouTube-structured series for complete beginners in Julia
5. MIT 18.S191: Introduction to Computational Thinking (MIT)	24–36 hours	Best rigorous course on Julia with many examples of real-world applications
6. Learning Julia (LinkedIn Learning)	2–3 hours	Best concise Julia course for complete beginner
7. Julia on Exercism (Exercism)	N/A	Best for practicing learning Julia coding for all levels
8. Julia Programming For Data Science & Machine Learning: Julia (Udemy)	3–4 hours	Best for complete beginners in Julia with focus on data science
9.  Learn Julia in Three Small Projects (Manning)	12–18 hours	Best hands-on project-based Julia course
10. Julia: Getting Started (Pluralsight)	2–3 hours	Best concise Julia course for experienced programmers

What is Julia?

Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing and data science. It is designed to run as fast as C but easy to write as Python.

One of the ways Julia is easy to use is its dynamic type system. By allowing the option to implicitly or explicitly declare types, programmers can simplify or improve code performance.

The language also features multiple dispatch, which means methods with the same name can perform different functions based on the arguments provided, which is especially useful for mathematical code where operators change their behavior depending on the type.

Metaprogramming is easy in Julia. Similar to Lisp, code can be represented as a data structure in Julia itself, so a Julia program can process and modify its own code. Furthermore, it is simple to call libraries written in a different language like C or Python without the need of glue code.

Although Julia is a young programming language, researchers and professionals have already utilized it in a variety of fields where enormous amounts of data needs to be processed in a reasonable amount of time, like in physics, chemistry, astronomy, engineering, data science, bioinformatics, finance and many more. Plenty of Julia programming jobs are also available, and are being advertised on the Julia discourse community.

Best Courses Guides Methodology

I built this ranking following the now tried-and-tested methodology used in previous Best Courses Guides (you can find them all here). It involves a three-step process:

1. Research: I started by leveraging Class Central’s database with 80K+ online courses and 170K reviews. Then, I made a preliminary selection of the courses by rating, reviews, and bookmarks.
2. Evaluate: I read through reviews on Class Central, Reddit, and course providers to understand what other learners thought about each course and combined it with my own experience as a learner.
3. Select: Well-made courses were picked if they presented valuable and engaging content and they have to fit in a set of criteria and be ranked accordingly: comprehensive curriculum, selling price, release date, ratings and enrollments.

Course Ranking Statistics

Here are some aggregate stats about the ranking:

• The courses combined account for 50K enrollments.
• All of the courses with the exception of two are free, free-to-audit, or have a free trial.
• Around 200 people are following Class Central’s Julia Topic.
• All of the courses are beginner-level, with the exception of one.

1. Julia Programming for Nervous Beginners (JuliaAcademy)

My #1 pick for the best Julia course goes to Julia Programming for Nervous Beginners by JuliaAcademy.

If you have no programming experience or feel intimidated by computers, but are curious about learning to write code in Julia this course is for you!

In this comprehensive course, you’ll take small steps up all the way to Julia proficiency and proficiency in programming in general. By the end, you’ll be able to tackle substantial projects all on your own with only what you’ve learned in this course. Plus, you’ll earn a free certificate.

No prior programming experience is needed to take this course.

What You’ll Learn

You’ll start this course by writing, running, and analyzing your first piece of Julia code. First, you’ll learn how to assign variables to values on which you can perform operations. Then, you’ll learn how to debug mistakes in your code from the error messages, along with an introduction to boolean logic. Finally, you’ll study how text, called strings, is represented and manipulated in Julia before being given an introduction to functions that allow you to reuse blocks of code.

You’ll add to your knowledge of functions by learning how to define one yourself. This means you’ll learn about Julia’s type system and how different functions can be given the same name with a technique known as multiple dispatch. You’ll also learn about scopes in relation to functions.

Moving on, you’ll investigate controlling the flow of your code with comparison and logical operators as well as conditionals and loops. These concepts allow you to make decisions within your program and repeat blocks of code. Moreover, you’ll learn about anonymous functions, which are functions without names.

The final week of this course discusses text files. You’ll learn to access text files on your computer through I/O functions and then read and manipulate them. Finally, you’ll end this course by performing a Monte Carlo simulation on a sample text file.

How You’ll Learn

This course is 4 weeks long and is around 7–8 hours long. You’ll learn mainly by watching the lecture videos, doing the in-course quiz, and reading through the course materials.

Institution	JuliaAcademy
Instructor	Dr. Henri Laurie
Level	Beginner
Workload	7–8 hours total
Certificate	Free

Fun Facts

• The course has 69 bookmarks on Class Central, and it is also recommended by the official Julia website.
• Dr. Henri Laurie is retired senior lecturer at the University of Cape Town.
• The course also has a support forum where you can ask questions.

If you’re interested in this course, you can find more information about the course and how to enroll here.

2. Introduction to Julia (for programmers) (JuliaAcademy)

My second pick for the best Julia course goes to Introduction to Julia (for programmers), also by JuliaAcademy.

This course is designed to help those who already have programming experience get up to speed with Julia, fast! And, you’ll also get a free certificate once you’ve completed the course.

What You’ll Learn

Beginning with the basics, you’ll learn about variables and data types. Next, you’ll learn how to get used to Julia’s operators and data structures, like strings, dictionaries, tuples, and arrays, making it convenient to work with many pieces of data at once.

Next, you’ll go over writing loops and conditional statements to control the flow of your program. You’ll also explore how functions work in Julia, including how to declare functions, mutable vs. non-mutable functions, and broadcasting.

Packages help programmers write more efficiently, utilizing code that other experienced programmers use. Julia supports packages, and you’ll explore how to manage use packages from the general registry. One of the essential packages you’ll need to use for visualizing data is Plots.jl. You’ll learn how to create beautiful kinds of plots with this package.

The final section of the course covers a few useful topics. You’ll discuss a key feature of Julia called multiple dispatch that allows you to create various functions with the same name, structs (short for structured data), basic linear algebra, and factorizations.

How You’ll Learn

This course has 1–2 hours worth of material. You’ll learn by watching the lecture videos and practicing coding in the Julia Jupyter notebooks.

Institution	JuliaAcademy
Instructor	Dr. Jane Herriman
Level	Intermediate
Workload	1–2 hours total
Certificate	Free

Fun Facts

• The course has 52 bookmarks on Class Central.
• Dr. Jane Herriman is Director of Diversity and Outreach at Julia Computing and a PhD student at Caltech.

If you’re interested in this course, you can find more information about the course and how to enroll here.

3. Julia Scientific Programming (University of Cape Town)

My third pick for the best Julia course is Julia Scientific Programming by the University of Cape Town.

This free-to-audit course is for beginners who want to explore the Julia programming language, although those with some experience with programming can also benefit from the course.

By the end of the course, you’ll learn how to utilize Julia packages to write simple Julia programs from scratch.

Some programming experience is required to take this course.

What You’ll Learn

The course begins with an introduction to Julia and demonstrates its capabilities. First, you’ll start programming from the browser with Julia Notebooks, which are very similar to Jupyter Notebooks. Then, you’ll learn how to write simple arithmetical and logical expressions, along with Julia’s type system and arrays. Lastly, you’ll use and define functions, taking note of a neat feature in Julia called multiple dispatch.

After a brief overview of Julia, the course illustrates a real example of scientific computing using data from the Ebola Virus outbreak. You’ll learn how to work with data tables with arrays, convert data types, and iterate through them with loops. You’ll also become familiar with the Plots package that beautifully visualizes data.

The final two weeks of the course continue the Ebola Virus case study. You’ll mathematically model the Ebola disease using the SIR model and use DataFrames for descriptive statistical analysis. An optional honors material for those interested includes lessons on collections and functions.

How You’ll Learn

This course consists of 4 weeks of study, with each week taking 3–4 hours. You’ll learn through video lectures, on-screen demonstrations, quizzes, and practical peer-reviewed projects designed to give you an opportunity to work with the packages.

Institution	University of Cape Town
Provider	Coursera
Instructor	Dr. Juan H Klopper and Dr. Henri Laurie
Level	Beginner
Workload	12–16 hours total
Enrollments	33K
Rating	4.4 / 5.0 (404)
Certificate	Paid

Fun Facts

• The course has 1.9K bookmarks on Class Central.
• This course is #1 in Class Central’s Julia Programming Languages Topic.

If you’re interested in this course, you can find more information about the course and how to enroll here.

4. Julia for Beginners (julia for talented amateurs)

Julia for Beginners gives an introduction to the Julia programming language for amateurs, hobbyists, and enthusiasts. By the end of this course, you’ll have an excellent understanding of Julia programming.

These free tutorials are intended for beginners to programming, so no programming experience is required.

What You’ll Learn

The first part of the course covers essential programming concepts. You’ll begin by setting up your development environment, where you’ll write and run Julia code. Then, you’ll start programming with the basics: variables, expressions, memory, and data types. Knowing these four concepts will be enough to write a simple program.

But you’ll probably want to go further than just writing simple programs. So, you’ll learn about data structures and containers that store data, like arrays, tuples, and dictionaries. You’ll find these data structures everywhere in programming. Then, you’ll want to learn how to use control flow by writing conditionals and loops before learning the primary building blocks of programming, and functions, to reuse blocks of code.

Now that you have the basics covered, you’ll investigate further into the nature of Julia programming. For example, you’ll study how functions of the same name can behave differently through multiple dispatch, create composite types, and conform to style guidelines. Furthermore, you’ll discover how to debug programs in Julia and the wonderful world of Julia packages, where you’ll import a package to help you plot and visualize data.

The second part of the course covers some intermediate computer science concepts. For example, you’ll learn what algorithms are (specifically searching and sorting algorithms), how to analyze them, and how recursion plays a role in them. You’ll also peek into the black box and look at how Julia works behind the scenes.

The third part of the course recaps what you’ve learned so far throughout the course and ends with a ‘final exam’ that consists of many fun projects for you to practice your newfound knowledge.

How You’ll Learn

This course consists of 13 tutorials divided into three parts, with 6 hours worth of material. You’ll learn primarily from watching the lecture videos, going through the supplemental course materials, and following along with the instructor as he codes.

Channel	julia for talented amateurs
Provider	YouTube
Level	Beginner
Workload	6 hours total
Enrollments	18K
Likes	297
Certificate	None

Fun Facts

• Julia is the first programming language the instructor has learned. In fact, he is entirely self-taught!
• He also has several other Julia courses, the next course being Julia Analysis for Beginners.

If you’re interested in this course, you can find more information about the course and how to enroll here.

5. MIT 18.S191: Introduction to Computational Thinking (Massachusetts Institute of Technology)

MIT’s 18.S191 provides a rigorous but rewarding introduction to computational thinking.

The goal of this free course is to broaden your understanding of how computer science and mathematics can connect and mingle with one another to produce exciting applications in other non-related fields like social and climate science. Not only that, the course also plans to make the learning process fun and enjoyable through interactive exercises.

Although it isn’t strictly a course on Julia, it does aim to teach you Julia and additionally, all of the programming in this course is done in Julia. By the time you finish this course, you’ll be proficient in this language.

There are no prerequisites to take this course.

What You’ll Learn

The first module deals with images, transformations, and abstractions. First, you’ll learn how to represent images as arrays of pixels and see how this helpful abstraction can help us creatively manipulate and transform an image by applying mathematical functions. Afterward, you’ll dive into dynamic programming, which deals with optimization problems, and seam carving, which ‘shrinks’ an image without resizing objects within the image.

The second module is about social science and data science. You’ll start with principal component analysis, which tries to reduce the dimensionality of a dataset, before moving on to sampling datasets. You’ll then learn about random walks, which model random motion in time and space, before moving into data science territory where you’ll simulate a real-world statistical application.

The third module’s central theme is climate science. First, you’ll learn about time-stepping, which deals with the problem of analyzing time in datasets. Then, you’ll discover why you can predict the climate but not the weather before building your first climate model. Finally, you’ll explore more complicated climate models like ocean currents and global warming.

How You’ll Learn

The course consists of 3 modules that’ll take you 24–36 hours in total to complete. You’ll learn by watching lecture videos and going through the provided Julia notebooks.

Institution	Massachusetts Institute of Technology
Instructors	Alan Edelman, David P. Sanders, and Charles E. Leiserson
Level	Beginner
Workload	24–36 hours total
Certificate	None

Fun Facts

• Alan Edelman is a professor of applied mathematics at MIT and is in fact one of the cocreators of the Julia programming language.
• There’s also a discord server open to both MIT and non-MIT students where you can ask questions and maybe find a course grading partner.

If you’re interested in this course, you can find more information about the course and how to enroll here.

6. Learning Julia (LinkedIn Learning)

Learning Julia by LinkedIn Learning aims to teach you the basics of Julia.

This course with 1 month of free trial covers the syntax, basic concepts, and features of Julia. First, you’ll go over the language’s feature set, explaining how it differs from other languages. Next, you’ll learn about data types, numbers, and strings in Julia; language features such as data type casting; and control and data structures. At the end of the course, you’ll be ready to write and run Julia code.

What You’ll Learn

The course begins by introducing the Julia language and what distinguishes it from other scientific computing languages: it is fast and easy to learn and write. Then, you’ll learn the basics of writing Julia code, like variables and data types and handling numbers and strings.

Next, you’ll learn control structures like conditional statements, loops, functions, and exception-handling to help streamline your code. Data structures like arrays, tuples, sets, and dictionaries will also be part of the course discussion. Finally, you’ll conclude the course by exploring some of the language’s features, like data type casting, string processing, custom types, and sorting data.

How You’ll Learn

This course has 2–3 hours worth of material. You’ll learn by watching the lecture videos and completing the programming exercises provided.

Institution	LinkedIn Learning
Instructor	Joe Marini
Level	Beginner
Workload	2–3 hours total
Enrollments	13K
Rating	4.6 / 5.0 (55)
Certificate	Paid

Fun Facts

• Joe Marini is a Senior Author for LinkedIn Learning with over 50 published titles, covering subjects such as Python programming, Android Development, XML and JSON data processing, Mobile Development, jQuery, and HTML5.

If you’re interested in this course, you can find more information about the course and how to enroll here.

7. Julia on Exercism (Exercism)

Exercism is an online, open-source, free coding platform where you can practice coding and receive mentorship in the Julia programming language. It is recommended by the official Julia website as a great place to put your skills and knowledge into practice.

One special thing about this platform is that you’ll receive personal mentoring for free. When you have solved an exercise, it’ll be reviewed by the volunteer team and feedback will be given to help you improve your code.

Exercises range from easy to hard, so the platform is suitable for all levels of programmers.

What You’ll Learn

There are 52 exercises in total that range in difficulty. You’ll begin with the tutorial exercise where you’ll print “Hello, World!”. Then, you’ll have the option of picking between three difficulties: easy, medium, and hard.

Some easy exercises have you find the difference of squares, calculate leap years, and implement a rotational cipher.

You’ll implement a clock that handles times without dates for medium exercises, write a robot simulator, and calculate a Pythagorean triplet.

Some of the most challenging exercises include writing a function to solve alphametics puzzles and implementing rational and complex numbers in Julia.

How You’ll Learn

This course is self-paced, so you can take all the time you need to complete the 52 hands-on programming exercises. Each exercise comes with automatic analysis of your code as well as personal mentoring to help you understand your code’s strengths and flaws.

Institution	Exercism
Level	Beginner to Advanced
Workload	Self-paced
Enrollments	11K
Certificate	None

Fun Facts

• Exercism provides exercises on 50+ programming languages like Python, Kotlin, F#, and WebAssembly.
• Their mission is to help everyone get really good at programming, regardless of their background, share the love of programming, and help people upskill as part of their upward social mobility.

If you’re interested in this course, you can find more information about the course and how to enroll here.

8. Julia Programming For Data Science & Machine Learning: Julia (Udemy)

If you’re here to learn Julia for data science and machine learning, check out this paid course!

By the end of Julia Programming For Data Science & Machine Learning: Julia, you’ll have the foundational knowledge and skills needed to tackle your own data science project.

No programming experience is required for this course.

What You’ll Learn

You’ll begin the course with an introduction to Julia and how it compares to other programming languages like Python. Then, after setting up your development environment, you’ll learn Julia’s basics. Starting with variables, you’ll know how variables can have different data types like numbers and strings. You’ll also learn about data structures that hold data like arrays, dictionaries, and sets. Lastly, you’ll learn how to control the flow of a program with conditional statements and loops.

Julia has a great package management system. You’ll learn how to install and use functions from packages, as well as define your functions. With packages, you can process vectors and matrices and access a nifty data structure — DataFrames.

DataFrames make it easier to work with multi-dimensional data for data science. The final sections of the course revolve around data science and machine learning. You’ll learn how to visualize DataFrames and perform several machine learning techniques in Julia, including regression, classification, clustering, and dimensionality reduction.

How You’ll Learn

This course has 3–4 hours worth of material. You’ll learn by watching the lecture videos and practicing coding by completing the Jupyter notebook exercises.

Institution	Data Science & Machine Learning Academy
Provider	Udemy
Instructors	Ankit Mistry
Level	Beginner
Workload	3–4 hours total
Enrollments	2K
Rating	4.6 / 5.0 (163)
Certificate	Paid

Fun Facts

• Ankit Mistry is a software developer with a Master’s in machine learning and artificial intelligence from IIT Kharagpur.
• He has also created Udemy courses in the areas of cloud computing, Google cloud, Python, data science, data analysis, and machine learning.

If you’re interested in this course, you can find more information about the course and how to enroll here.

9. Learn Julia in Three Small Projects (Manning)

In Learn Julia in Three Small Projects, you’ll get familiar with Julia by building a series of real-world projects.

You’ll complete three projects: a simple stock tracker for a shop; joining the fight against a global pandemic by plotting and modeling the effectiveness of several measures; and finding the cure for a global pandemic using Longest Common Subsequences (LCS), which measures the similarity between two sequences of characters.

By the end of the paid course, you’ll go from beginner-level to solving everyday, real-world problems using Julia.

To take this course, you need some basic mathematics and statistics as well as basic programming skills.

What You’ll Learn

In the first project, you’ll build a simple shop stock tracker. You’ll start by creating a structure for your shop. Then, you’ll write a function to manage inventory delivery and keep track of items sold. Finally, you’ll wrap up by creating a function to handle cash transactions. When you’re done, you’ll have hands-on experience using essential Julia tools, including functions, arrays, and dictionaries, and more advanced tools such as multiple dispatch and composite types.

You’ll help fight against a (fictional) global pandemic for the second project. You’ll gain hands-on experience plotting in Julia as you estimate new cases per day. Next, you’ll understand the effect of several measures through plot analysis and basic time-series forecasting. Finally, you’ll deduce the best measures, determine and predict their impact, and report your findings to decision-makers.

The final project will have you find a cure for an (also fictional!) global pandemic by identifying the virus’s origin. Biologists have already narrowed the list of suspects down to three animal species. Longest Common Subsequences can help you measure the similarity between two sequences. You’ll use them to compare the animal sequences with the virus sequence. You’ll get a sense of what percentage of the sequences should be common versus what is actually common between the sequences studied. Then, you’ll be able to identify the virus origin based on your findings.

How You’ll Learn

This course is 3 weeks long, with each week taking 4–6 hours on average. You’ll learn by watching the lecture videos, with more emphasis placed on hands-on coding.

Provider	Manning
Instructor	Joris Limonier
Level	Beginner to Advanced
Workload	12–18 hours total
Certificate	Paid

Fun Facts

• Joris Limonier has worked at the Unit of Research in Computer Science at the University of Luxembourg and has a strong background in Julia, Python for data science, LaTeX, and Swift.
• To share his passion for Julia, he creates Julia content including YouTube videos and open-source projects on GitHub.
• To obtain a certificate for this course, you’ll need to set up a 15-minute video call with the mentor to verify your work.

If you’re interested in this course, you can find more information about the course and how to enroll here.

10. Julia: Getting Started (Pluralsight)

In this Pluralsight course with 10 days of free trial, you’ll learn the foundational knowledge needed to write Julia code. By the end, you’ll have the skills and knowledge required to call yourself a Julia coder.

To take Julia: Getting Started, you’ll need an understanding of programming in general (preferred knowledge of Python, R, or Scala), and as a bonus, a mathematical background.

What You’ll Learn

First, you’ll answer the question: “Why Julia?”. Then, you’ll learn how to set up your Julia development environment. Lastly, you’ll move on to coding in Julia by learning to define variables, use data types, and control program flow.

You’ll follow that up by learning how to create functions, methods, and modules, which will ease code reusability and work with files. Finally, you’ll discover how to find packages with JuliaHub to help you use other people’s polished code and build any application you can dream of.

How You’ll Learn

This course is 2–3 hours worth of material. You’ll learn by watching the lecture videos and following along with the instructor as he codes.

Institution	Pluralsight
Instructor	Xavier Morera
Level	Beginner
Workload	2–3 hours total
Rating	4.5 / 5.0 (12)
Certificate	Paid

Fun Facts

• Xavier is an entrepreneur, project manager, technical author, trainer, and holds a few certifications with Cloudera, Microsoft, and the Scrum Alliance, along with being a Microsoft MVP.

If you’re interested in this course, you can find more information about the course and how to enroll here.