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Вернуться к Julia Scientific Programming

Отзывы учащихся о курсе Julia Scientific Programming от партнера Кейптаунский университет

Оценки: 407

О курсе

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 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....

Лучшие рецензии


14 дек. 2020 г.

Really great pacing, practical examples and quizzes without being overwhelming. Great for both beginners in programming and statistics, and for those with some experience. Awesome lesson, thank you!


26 янв. 2018 г.

Excellent, engaging teaching that makes me want to use Julia language (and Jupyter notebooks) all the time. As the language evolves, you need to adjust to newer Julia versions - just a part of fun.

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126–138 из 138 отзывов о курсе Julia Scientific Programming

автор: Subhankar

20 авг. 2018 г.

The course could have been much better if it was more aligned with the language itself instead of the epidemic and disease stuffs.

автор: Sonja S

6 дек. 2021 г.

It's a good course if you don't know anything about coding.

автор: Vishal S

30 апр. 2020 г.

sound problem in all videos, audio is very low

автор: Jm

17 окт. 2016 г.

fair intro level to julia

автор: bingining

24 дек. 2019 г.

A little bit to easy.

автор: Alexey V

15 мая 2021 г.

The course gives some basic understanding of Julia and packages that can be used in data science (not exactly in scientific programming). However, the course is quite messy, outdated, and with errors. The quiz for week 4 was a major disappointment; "guess what the authors wanted" instead of "answer the question".

автор: Luis A C G

27 мая 2018 г.

While it's indeed a very good introduction to Julia lang, it makes no sense videos are based on course notes. I paid for the course because it has very positive comments, but in my opinion it doesn't worth it.

автор: Ashrith R

25 дек. 2017 г.

Poorly organised course content

автор: Matthieu L

24 дек. 2020 г.

With all due respect, this is the worst course I followed on Coursera.

- First of all week 1 is extremely basic. I would think that most people learning Julia are coming from Python and/or data-science background with programming knowledge. Yet the week 1 feels like for people with no programming experience.

- But then week 2 goes directly into plotting! Plotting is the last phase of any data analysis. Before that, you need to manipulate your data and there is a lot to learn about as Julia's Array seems very different than Python or Numpy's arrays but is absolutely not covered.

- Worse, week 3 has nothing to do with Julia. I appreciate having a real world example but most of the lectures are explaining epidemiology SIR models and teach nothing more about Julia. In terms of learning Julia, that entire week can be skipped.

- Week 4, which should have been before week 2 is more interesting going into DataFrames and data manipulation. But again, I think there's a lot to teach first about basic Julia data types like Arrays, Vectors, Sets...

An example. In week 4 there is a code doing the following on DataFrames dataA = data[data[:Treatment] .== "A", :] But never in the course is it explained that the period, when prefixing a function or operator is used to indicate broadcasting (performing the operation element wise).

In short, the course fails on teaching any of the important specificities about Julia.

And on top of that, as other mentions, it is outdated.

автор: Lafras U

4 окт. 2021 г.

T​his course is very basic. For somebody with industry experience using Python or R a more rigorous and comprehensive course would be needed. The course also still relies on Julia 1.0, at the time of writing this I was using Julia 1.6.

автор: Arturo E

23 окт. 2019 г.

Low quality course in many aspects: videos, updates, code, ideas.

автор: Isai A M M

13 февр. 2022 г.

They only read a jupyter notebook

автор: Alireza L

6 авг. 2022 г.

It was not useful at all!