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More Data Mining with R – Udemy

(10 customer reviews)

$15

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Description

What you’ll learn

  • Understand the conceptual foundations of association analysis and perform market basket analyses.
  • Be able to create visualizations of social (and other) networks using the iGraph package.
  • Understand how to examine and mine social network data to understand all of the implicit relationships.
  • Mine text data to create word association visualizations, term documents with word frequency counts and associations, and create word clouds.
  • Learn how to process text and string data, including the use of ‘regular expressions’.
  • Extract prototypical information about cycles from time series data.

More Data Mining with R presents a comprehensive overview of a myriad of contemporary data mining techniques. More Data Mining with R is the logical follow-on course to the preceding Udemy course Data Mining with R: Go from Beginner to Advanced although it is not necessary to take these courses in sequential order. Both courses examine and explain a number of data mining methods and techniques, using concrete data mining modeling examples, extended case studies, and real data sets. Whereas the preceding Data Mining with R: Go from Beginner to Advanced course focuses on: (1) linear, logistic and local polynomial regression; (2) decision, classification and regression trees (CART); (3) random forests; and (4) cluster analysis techniques, this course, More Data Mining with R presents detailed instruction and plentiful “hands-on” examples about: (1) association analysis (or market basket analysis) and creating, mining and interpreting association rules using several case examples; (2) network analysis, including the versatile iGraph visualization capabilities, as well as social network data mining analysis cases (marriage and power; friendship links); (3) text mining using Twitter data and word clouds; (4) text and string manipulation, including the use of ‘regular expressions’; (5) time series data mining and analysis, including an extended case study forecasting house price indices in Canberra, Australia.

Who this course is for:

  • This course would be useful for undergraduate and graduate students wishing to broaden their skills in data mining.
  • This course would be helpful to analytics professionals who wish to augment their data mining skills toolset.
  • Anyone who is interested in learning about association analysis (also called ‘market basket analysis’), analyzing and mining data from social networks, text (such as Twitter) data, or time series data should take this course.

Course content

  • Introduction to R and to Data Mining
  • Association Analysis (part 1)
  • Association Analysis: Online Radio and Predicting Income
  • Social Network Analysis: iGraph Visualizations
  • Social Network Analysis (part 2)
  • Text Mining Twitter Data
  • Text (String) Manipulation
  • Time Series Data Mining
  • Case Study: Forecasting House Price Indices in Canberra, Australia

10 reviews for More Data Mining with R – Udemy

  1. Donny Phan

    Super practical. Lessons are catered towards anyone looking to find work in this industry. It felt very comprehensive and gave me a broad understanding of the programming spectrum

  2. Madhav raj Verma

    Thanks for your great effort. i am fully satisfied with this course the way you teach and your explanation are very clear ,The content you provide in your course no one can do this at this price.

  3. Sachin Gupta

    I really didn’t want to leave a low rating as Angela is a great teacher. The 1st half of this course was terrific. The 2nd half was terrible. Under the justification of “teaching students how to figure things out on their own”, pretty much all videos and all explanations were dropped. You were just told what to do, given links to documentation and told to figure it out on your own. I understand doing that to some degree, but to revert to that entirely for nearly half the content barely makes this a course. It’s just a list of things for you to learn, then you’re left on your own to learn them. The 2nd half was so bad, especially the data science component, that I didn’t bother finishing the course.

  4. Vincent Beaudet

    Amazing 40 days course.
    Angela is a great teacher.
    The other 60 days are all about web developement, interacting with web pages, on your own with little to no explanations. I did not expect that at all. I wanted to learn more about software and scripting.
    This left me disappointed , confused and i started to doubt myself. Not a fun experience after the amount of effort i’v put in this course.

    Exercices format and explanations for the first 40 days were worth it tho.

  5. Ben K

    Not just an introduction to python, but really helps you learn fundamental aspects of python and coding in general. Some parts may require some knowledge on the subject (data science comes to mind) and there is quite some web development in the course. So, a few areas were not completely to my liking (I would have liked to see it done differently), but this course deserves the 5 stars in my opinion.

  6. Omid Alikhel

    I found the method a bit difficult when a code is written and then changed back to something different, with no enough explanation of how something happened and where it came from or a step by step explanation of why something is happening, i have no doubt in the instructors talent, but we are beginners!

  7. Devang Jain

    The course is not updated and most of the solution codes don’t work and there are no video solutions towards the end

  8. Szymon Kozak

    I think that the course tutor is really good in giving right information to learn at the right time. Thanks to this fact, my understanding of coding in python after 29 days of learning is above my expectations.

  9. Begoña Ruiz Diaz

    Ha sido la mejor elección que podría haber hecho.

  10. Vaibhav Sachdeva

    I want to thank Angela for making such an amazing course. It really helped me explore more things with python.

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