Отзывы учащихся о курсе Julia Scientific Programming от партнера Кейптаунский университет

Julia is now at V1.3. The course was based on Julia 0.6 and done around the time Julia 1.0 was close to release. The material sorely needs to be updated.

A clear and well presented course.

Suitable for newcomers and relatively new users of Julia. The course notes (Jupyter notebooks) are a useful reference after the course.

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.

I general, I can recommend this course.

I was able to learn the basics of Julia language.

The three things that stand out for me are:

Data structures, Plotting, Data Frames.

Parallel computing is not part of this course.

There are a few weaknesses in this course, but it seems that the course is being reviewed frequently, in order to adress issues, and enhance the content.

Weaknesses I found were:

Some typos and dead links in tests

In some tests, correct answers (when the code works in the computer language) are graded as incorrect, because the grading software only accepts one correct answer, rather than a variety of correct answers.

Some tests are testing your ability to pay attention in small details, rather than your ability to understand the computer language

There are not enough participants in the course for mutual grading to work properly. Instead instructors have to do grading, which often occurs with a delay of a few days.

I suggest that the course material should give more references to side information (e.g. cheat sheet for markup language, definition of SIR model, links to collections of open datasets)

I found this a great introductory course on Julia for scientists. I specially loved the classes about data frames, user-defined types, and the Gadfly package.

The course needs to be updated, though, videos, exercises and Julia notebooks. Nothing too serious, yet, but some of the contents need to be reviewed in face of the current development status of Julia.

I am looking forward to see a course on data science with Julia.

Great course, well taught and thorough. I would only add that it needs to be updated from the version in the course (0.4.6) to the latest, full version of Julia, e.g. (1.x). I would have given 5 stars but for that fact.

Content is out of date and no one responds to questions on discussion board. For example, the last quiz had several bugs that make it impossible to answer correctly, but people have been pointing this out for months on the discussion board with no response from course moderators.

Lectures are using different version of Julia from the notebooks, so packages don't work or you need to use a different package. Quizzes often refer to things that were not included in any of the lectures or notebooks. Note that I passed the course, but it was super frustrating.

Honestly, I was a bit underwhelmed at the content of the course. There is a fairly large amount of overlap in the content covered by the two instructors which makes Weeks 1-3 and Week 4 somewhat redundant, and the amount of ground covered in terms of pure Julia code is very basic and sometimes methods shown are suboptimal or outdated.

Amazing course! I learned a lot during this course. The assignments made me improve my coding skills and the questions were challenging enough. The instructors are engaging and innovative!

Nice introduction into Julia. The content is well structured and provides enough details so you can write your own (basic) data science routines in Julia. I also liked the Ebola use-case and to learn about modelling such an outbreak.

Personally I would prefer more videos about some of the more advanced language features and less about plotting libraries and the likes. But I guess that really depends what you are looking for.

Overall a highly recommended course.

The course was a good overview of Julia, starting from the very basics. This makes it relevant for programming beginners at the start. As the course builds up, it nicely introduces Julia's complexity in the assignments, and introduced many of Julia's must-know features such as multiple dispatch and user defined types, without getting too daunting. The explanation was clear and crisp at all times. More content could be covered for data analysis and perhaps more forum discussion could be encouraged. The course didn't take a great deal of time to complete. Perhaps there is a need in the industry for a multiple Julia certification as the language gains momentum. I would recommend this course for those who want to get to know Julia and many key libraries in it for data analysis and visualization.

Solid overall course for both introduction to Julia as well as programming as a whole. A few aspects could be updated. Juliabox is about to be sunset(discontinued) so it would be nice for them to walk users through using JupyterLabs in Anaconda for loading the Julia notebooks needed for the course assignment. Atom and Juno are briefly mentioned but I would recommend using these to anyone looking to take this course. Some of the code used in the course is now deprecated, but using the error messages it is not that difficult to debug and update - though it does slow down the overall speed with which the course can be completed. Overall, I would highly recommend this to anyone involved in data science or interested in programming languages in general

This course was a good introduction to Julia, and it has helped me start to use Julia regularly for data analysis. I think the course would benefit from being longer and covering a greater number of topics, as it really just scratches the surface of using a coding language for scientific analysis, but in its present form it is definitely worth the money. One specific thing that the course taught me which I may not have learned had I purely taught myself, is the importance of Jupyter-style notebook environments for Julia, which given the import times of some modules, are more useful for Julia than Python. Though of course, Julia is also used in conventional IDEs for different types of work, as the course mentions.

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.

This is a great introductory course for getting acquainted with the Julia programming language and its many data science applications. However, the curriculum is too easy for someone with a prior DS background or knowledge of other language such as Python. It's interesting to see how similar tasks such as array manipulation and data visualization are done in Julia, but for a better command of the language, I recommend that one examine other available literature in addition to this course.

I wasn't completely familiar with types in Julia and this course helped me understand a very important aspect of Julia programming. Now, I feel I have a much better understanding of how Julia works. The professors were amazing and the course was extremely crisp and fun. I would like to extend them my warm wishes and would want to know if an advanced level of Julia Programming course could be planned in the future

This is an excellent introduction to the Julia language. My only complaint is that the course was written when Julia 0.4.6 was the standard, so when I used the current Julia 0.6.0 some of the instructor-provided code contained deprecated functions, or did not run at all, requiring a trip to the Julia API to find the currently-used syntax. But this course is still very good in spite of the dated code.

It's a very good course for beginners of Julia, though I have learned Julia for more than one year, I still learned many useful things in this course. Julia is so beautiful, wonderful and powerful, and two honorable professors have deep insight about it, I hope there are more and more people will learn it through this course and make the world better.

This course was very interesting and well planned. The course material is clear and comprehensive. As for the instructors, they demonstrated experience and deep knowledge in Julia ana statistical software, proving their success for this course. I am certainly going to make Julia one of my main tools.

Not a bad course as an introduction to Julia. It gives a good feel of how Julia defines functions, uses for loops, arrays, dataframes, and statistics. It would be of interest to those who have prior experience with other statistical programming languages such as R and Python.

This course gave me more insight on how data should be compiled and expressing the meaning of it. On such way to express data is trough interactive graphs. Working with Big Data and the analysis of it helps a lot into making some of the most crucial decision.

Liked the Honors course content. A good introduction to Julia. Recommended to all freshers in coding, especially for those who are pursuing courses in numerical techniques. You'll be able to write very intractable and efficient codes.

It was exceptional and so fun.I have learned many exciting things such as mathematics functions in easy coding Such a great language to learn.It really going to be used by many aspiring data scientist.Thanks for the wonderful course.

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.

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!