Julia vs Haskell

Julia runs almost as fast as (and in fact in some cases faster than) C code.

Dynamic and high level, but does not isolate the user from properly thinking about types. Can do explicit type signatures which is great for teaching structured thinking.

Out of the box Julia has a very good Read-Eval-Print-Loop, which both completes functions and types, as well as completion based on history of previous statements. It integrates well with the shell and has an excellent online help system.

Julia code is easy to read and avoid a lot of unnecessary special symbols and fluff. It uses newline to end statements and "end" to end blocks so there is no need for lots of semicolons and curly braces. It is regular in that unless it is a variable assignment, function name always comes first. No need to be confused about whether something is a method on an object or a free function.

Unlike Python and Ruby, since you can annotate the types a function operates on, you can overload function names, so that you can use the same function name for many data types. So you can keep simple descriptive function names and not have to invent artificial function names to separate them from the type they operate on.

The Julia language is written in itself to a much larger extent than most other languages, so a budding programmer can read through the depths of the standard library and learn exactly how things work all the way down to the low-level bit-twiddling details, which can be englightening.

Julia has built in n-dimensional arrays similar in functionality as Python's numpy.

You can have multiple functions with the same name, but doing different things depending on function arguments and argument types.

Julia requires no boilerplate code – a beginner needs to write only the parts they care about. This combined with the REPL provides the best learning experience available.

Julia provides a high level of abstraction, making platform-independent programming trivial and easing the learning curve.

You can perform operations on scalars, for example 2^2 or [1, 2, 3].^2.

Julia allows you to edit Julia code in the language itself and write powerful macros. It is a great introduction to metaprogramming features

The Julia REPL allows quickly testing how some code behaves and gives access to documentation and package management immediately in the REPL.

Haskell's referential transparency, consistency, mathematics-oriented culture, and heavy amount of abstraction encourage problem solving at a very high level. The fact that this is all built upon little other than function application means that not only is the thought process, but even concrete solutions are very transferable to any other language. In fact, in Haskell, it's quite common for a solution to simply be written as an interpreter that can then generate code in some other language. Many other languages employ language-specific features, or work around a lack of features with heavy-handed design patterns that discourage abstraction, meaning that a lot of what is learned, and a lot of code that is needed to solve a particular problem just isn't very applicable to any other language's ecosystem.

It is pure and does not mix other programming paradigms into the language. This forces you to learn functional programming in its most pure form. You avoid falling back on old habits and learn an entirely new way to program.

All Haskell implementations are completely free and open source.

As Haskell lends itself exceedingly well to abstraction, and borrows heavily from the culture of pure mathematics, it means that a lot more code conforms to very high-level abstractions. You can expect code from vastly different libraries to follow the same rules, and to be incredibly self-consistent. It's not uncommon to find that a parser library works the same way as a string library, which works the same way as a window manager library. This often means that getting familiar and productive with new libraries is often much easier than in other languages.

Haskell's Purely Functional approach means that code is referentially transparent. This means that to read a function, one only needs to know its arguments. Code works the same way that expressions work in Algebra class. There's no need to read the whole source code to determine if there's some subtle reference to some mutable state, and no worries about someone writing a "getter" that also mutates the object it's called on. Functions are all directly testable in the REPL, and there's no need to remember to call methods in a certain order to properly initialize an object. No breakage of encapsulation, and no leaky abstractions.

Conciseness of Haskell lets us to write the expression on the whiteboard or paper and discuss with others easily. This is a strong benefit to learn FP over other languages.

The base language relies primarily on function application, with a very small amount of special-case syntax. Once you know the rules for function application, you know most of the language.

It's often said that, in Haskell, if it compiles, it works. This short feedback loop can speed up learning process, by making it clear exactly when and where mistakes are made.

Every function that expects more than one arguments is basically a function that returns a partially applied function. This is well-suited to function composition, elegance, and concision.

Haskell is a very terse language, particularly due to its type inference. This means there's nothing to distract from the intent of the code, making it very readable. This is in sharp contrast to languages like Java, where skimming code requires learning which details can be ignored. Haskell's terseness also lends itself to very clear inline examples in textbooks, and makes it a pleasure to read through code even on a cellphone screen.

Haskell is really popular in universities and academia as a tool to teach programming. A lot of books for people who don't know programming are written around Haskell. This means that there are a lot of resources for beginners in programming with which to learn Haskell and functional programming concepts.

Since the basic syntax is very similar to mathematics, Haskell syntax should be easy for people who have taken higher math courses since they would be used to the symbols used in maths.

Makes categorical higher order abstractions easy to use and natural to the language.