Text Mining and Sentiment Analysis with Tableau and R (Udemy.com)

The guide to creating a twitter developer account appears to be obsolete as the twitter developer portal is quite different from is described in the video, making it difficult to following. I will rate this below average.

There are no links to download code or data for the lexicon. There are several places where there are jumps that are not explained. Overall, I think this is the last time I try one of these courses. I am able to move along thanks to outside websites that cover the same topic and give more detailed information.

Instructor is very good in delivery. The presentations are clear, concise and direct. There is no halting speech, repetitive comments or irrelevant discussion. Instructor mostly explains a context at the beginning of a module and then summarizes at the end. There is some coding in R Studio. Instructor gives useful coding tips along the way. Visual aids are generally effective.

I have been struggling to find a course in tweeter Analytics until I enrolled for your work and i can't complain. The material is easy to understand and really interactive and applicable at the same time. I had little knowledge in R but the seamless with which the course materials are delivered is just precise. Thanks man

It is surprisingly easy to integrate R into Tableau. There is even a feature in Tableau that lets you do that. At the R side there are some packages that need to be installed first, but these are explained in the course. The course uses a simple library approach to sentiment analysis, but as far as I believe that is totally sufficient in most cases. The course is well thought out and the instructor does a great job at delivering the content in a way that is easy to digest.

Wow, this course is fantastic!! I completed it over two days and I can now perform sentiment analysis on tweets in R, explore the data in Tableau and present the results in an interactive dashboard. This course really takes you from 'absolute novice' to 'highly skilled at performing sentiment analysis on tweets'. As a result I feel confident adding 'sentiment analysis' to the skills section of my CV and know that if I am called on to do one, I will be able to do a really professional job of it. And as an added benefit I learnt a lot of new R commands and A LOT of hands-on Tableau stuff. Altogether an incredibly worthwhile course! I can't thank the creator enough!!

Overall this is very good. I feel there are some small gaps - though they could be inside me - it is never easy to separate one's own deficiencies from the instructor's content. If I don't have a means to extract a .rar file for the lexicon, it's my fault, I suppose. But it's a crucial step that would trip up some basis users. 7-zip got me through it. Overall I like it and the instructor, and that was just one example.

This is a great course and well prepared. The instructor is making it easy to learn the R code. The best part is the integration. This course is like a capstone project. It shows one how to do a project from scarping data and clean data, analyze data and visualize data. I am happy that I chose this course , put time and efforts on this course. Many thanks for the instructor. Wonderful job.

Marten has created another great and very practical course. He has struck a balance between demonstrating complexities in R and moving the analysis to Tableau to illustrate insightful aspects of the data collected from twitter. The approach is lexicon based and Marten has outlined the pros and cons of the approach. I would like to see alternative ways of harvesting twitter content to include emoticons to complement the lexicon approach.

Overall, the course was really outstanding. Two elements are covered that are so important and difficult to find information: 1. the drawbacks : these are covered in detail, and allow for a thorough defense of the method, if scrutinised by a superior or in an academic setting. 2. Visualisation: really helpful and gives a great overview of Tableau