# Best way to learn Julia for non-programmer data analyst?

**URL:** <https://discourse.julialang.org/t/best-way-to-learn-julia-for-non-programmer-data-analyst/46110>\
**Category:** New to Julia\
**Tags:** question, recommendations\
**Created:** [September 5, 2020, 4:06pm UTC](https://discourse.julialang.org/t/best-way-to-learn-julia-for-non-programmer-data-analyst/46110 "2020-09-05T16:06:02Z")\
**Posts on this page:** 1\
**Showing post:** 15

<div class="post-metadata">

**Author:** ![phendric](https://avatars.discourse-cdn.com/v4/letter/p/58f4c7/32.png) [@phendric](https://discourse.julialang.org/u/phendric)\
**Post date:** [September 6, 2020, 10:44pm UTC](https://discourse.julialang.org/t/best-way-to-learn-julia-for-non-programmer-data-analyst/46110/15 "2020-09-06T22:44:32Z")

</div>

> [@Tamas\_Papp](#):
>
> Typically, the kind of analysis which involves 1. writing code (as opposed to using some canned method)

I assume this is because there are very few useful canned methods …??? If that’s the case, then the natural follow-up question is: “is there any plan in Julia’s roadmap to become something more than ‘write your own code’? If so, over what time frame (assuming that can even be predicted)?”

Several of the comments in a different thread seem related to this question. For example:

> [@Why is Python, not Julia, still used for most state-of-the-art AI research?](https://discourse.julialang.org/t/why-is-python-not-julia-still-used-for-most-state-of-the-art-ai-research/45896/24):
>
> I think the answer is very simple: Python is a very simple language, with a lot of consolidated libraries in the area (Scikit-learn, Numpy, PyTorch, Keras, OpenCV .API …). The majority of pre-processing algorithms are also available in Python (as sci. The Julia equivalents are, obviously, not so complete yet. Also, many researchers in the AI area are reluctant to learn another programming language (Python is the easier). Also, the performance topic is not important for many (when the training…

> [@Why is Python, not Julia, still used for most state-of-the-art AI research?](https://discourse.julialang.org/t/why-is-python-not-julia-still-used-for-most-state-of-the-art-ai-research/45896/34):
>
> I kind of feel like the two language problem is getting less important over time. Lower level languages are getting easier to use. Rust and Cpp with modules are very appealing.

I think that a core question I’m asking myself is the following: when I need to do something that’s non-canned, what’s the best long-term solution, assuming I only have time/energy to do one? Am I better off learning a completely new language that shares many of Python’s strengths but still lacks maturity and reach? Or am I better off learning a language that can act as a good companion/2nd language to Python (eg, C++ or Rust)?

> [@kevbonham](#):
>
> I can also recommend _Think Julia_ as an introduction - it’s the first thing I suggest for my students - but also given your interests, the [DataFrames tutorial](https://github.com/bkamins/Julia-DataFrames-Tutorial) will likely be of use.

Thanks; I’ll take a look. What do you teach?

> [@kevbonham](#):
>
> you might want to take a look at Automa.jl

Will also look at this.

> [@SteffenPL](#):
>
> these courses from the Julia Academy:

> [@mthelm85](#):
>
> Learning resources:
> 
> - [https://juliaacademy.com/](https://juliaacademy.com/)
> - [https://julia.quantecon.org/index\_toc.html](https://julia.quantecon.org/index_toc.html)
> 
> These are two really solid resources for learning some of the fundamentals. Based on the kind of work you describe, I would also recommend that you have a look at the following packages

Thanks and thanks. How useful will the 2nd course/book be to someone who knows next to nothing about economics?

---

_[View the full topic](https://discourse.julialang.org/t/best-way-to-learn-julia-for-non-programmer-data-analyst/46110)._