Generate and visualize data in Python and MATLAB (Udemy.com)

The introductory course, which is explaining the goals of the course seems to be well composed. Maybe it is little too much to speak in the 'introductory' about why the data simulation is important, althought it certainly is. I was writing the code in Matlab (not being an expert) and I am trying to shift to Python, in which I am at the (early) beginning phase. Following the video of this first 'lecture' my mind was all the time worried about 'how will I be able to get the python source code and the 'documentation files' (?) for the cases with which I will be faced with. Would I be able to place the files in my working directory and with I be able to run the code and 'change' it? Play with the parameters, as you mentioned in the presentation, expecially if I am using the Visual Studio Code environment? I suspect that I will be able to retrieve the pdf 'documentary' file in which there will be some explanations about the procedures applied and also the excercises, that I would like to do. Similar questions are also present for the code in Matlab, not that much to run the code in Matlab (I hate when I have to rely on the license of the institute or the faculty). Perhaps the Matlab code would be suitable to understand the code in Python. Therefore, I would appreciate if in the first introductory, 'these worries' would be addressed, so the student could concentrate on to the stuff that needs to be understand. The simulation of the data seems to fit better in the front of the next 'lecture', which I am expecting now. Sincerely Vlado Malacic

I took the course with the expectations of having a deeper understanding of the data simulation. Therefore I honestly enjoyed the first 4 sections of the course. The remaining ones are focused on times series and signals which I had no interest in deepening, actually I had really had times going forward. For the future students meaning to take this course I advice them to take only the first sections if interested in statistical data simulation, the whole course if interested in times series and signals.

Good explanation of plotting and data visualization. The course also covers basic explanation of different types of data, distributions, signals along with how to plot and visualize them in MATLAB and PYTHON.

This course was very helpful. Many concepts were new to me, and I obtained lots of new information. At first, you gain some knowledge and intuition about the importance of data visualization by seeing some interesting examples which convince you why you have always to keep visualization in your mind. Then you learn about different data types, some methods of creating data, time series, clustering, and forward models, ... By seeing some examples through MATLAB\Python codes, you learn how to draw different plots, create distributions, implement transients, stimulate different noise, ... In each lecture, first, the theoretical concepts are explained, and then you will see the code and after that, it’s the conclusion which I think is the most important one, since in the last part some applications of the topics are briefly described or mentioned, that allows you to understand the materials better and gives you some new topics for search the similar and related concepts. Many thanks for creating such an informative course! For better understanding, you have to go through the codes, line by line, and once you are sure that you get the idea, then make change some parameters, compare the results and analyze them. It’s an interesting part! In this way, I’ve also learned some new knowledge in MATLAB as well. Many Many Thanks again Dr. Cohen! :)

This class was put together very well with a good balance between the discussion and exercises. The instructor is engaging and presents the material clearly. I took this course in part because I took a previous excellent course from this instructor. I very highly recommend this instructor.

Instructor has done a perfect job laying a foundation introducing the course and the relevance and interconnection of the aspects. I am serious looking forward to comparing Python versus Matlab in their respective analysis of same data

I am in the situation that Mr. Cohen described in lecture three. I am learning data science and only reacting to the data that I am presented. In laying out the "why simulate data", I feel he is addressing my desire to understand the mechanics of data analysis and get me beyond reacting to the data that I'm presented.

First of all the course resembles the title, which means you will not be disappointed buying this course. A sound explanation of concepts which can be easily understood and then used in your data analysis, thanks to the well documented Matlab code.

This course is helping me learn more about the statistical application of math. During my 36 year career as an applied mathematician, I mostly applied math to help solve engineering problem during research and development of naval systems. I did do some simulation of different configurations of systems to fine-tune design parameters. We were required to use FORTRAN computer language. So far, I haven't seen anything in MATLAB/OCTAVE that we could not have done in FORTRAN, but I do see that MATLAB is very efficient. My career started 52 years ago and I have been retired for 17 years. Math is like a hobby for me now. I enjoy re-learning math and learning new math.

This course is very friendly, interesting, and useful. Actually, I wanted to learn data simulation long time ago, but there was no such a course in my University in Australia. I thank Mike's course for helping me realize my passion in this direction. This course provides a very easy-to-understand explanation of some of the important knowledge about data science in general and some applications in brain science in particular. I like and highly recommend this course and hope an advanced course following this course can also be released if possible. :) Particularly, I want to thank Mike for sharing his knowledge online so that more people could learn those knowledge which might be hard to get in their own Universities. I think Mike is one of the pioneers in cognitive neuroscience field who revolutionize the way of teaching and learning.