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Clustering & Classification With Machine Learning In R – Udemy

(10 customer reviews)

$15

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What you’ll learn

  • Be Able To Harness The Power Of R For Practical Data Science
  • Read In Data Into The R Environment From Different Sources
  • Carry Out Basic Data Pre-processing & Wrangling In R Studio
  • Implement Unsupervised/Clustering Techniques Such As k-means Clustering
  • Implement Dimensional Reduction Techniques (PCA) & Feature Selection
  • Implement Supervised Learning Techniques/Classification Such As Random Forests
  • Evaluate Model Performance & Learn The Best Practices For Evaluating Machine Learning Model Accuracy

HERE IS WHY YOU SHOULD TAKE THIS COURSE:

This course your complete guide to both supervised & unsupervised learning using R…

That means, this course covers all the main aspects of practical data science and if you take this course, you can do away with taking other courses or buying books on R based data science.

 In this age of big data, companies across the globe use R to sift through the avalanche of information at their disposal. By becoming proficient in unsupervised & supervised learning in R, you can give your company a competitive edge and boost your career to the next level.

LEARN FROM AN EXPERT DATA SCIENTIST WITH +5 YEARS OF EXPERIENCE:

My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University.

I have +5 years of experience in analyzing real life data from different sources using data science related techniques and producing publications for international peer reviewed journals.

Over the course of my research I realized almost all the R data science courses and books out there do not account for the multidimensional nature of the topic…

This course will give you a robust grounding in the main aspects of machine learning- clustering & classification. 

Unlike other R instructors, I dig deep into the machine learning features of R and gives you a one-of-a-kind grounding in  Data Science!

You will go all the way from carrying out data reading & cleaning  to machine learning to finally implementing powerful machine learning algorithms and evaluating their performance using R.

THIS COURSE HAS 8 SECTIONS COVERING EVERY ASPECT OF R MACHINE LEARNING:

• A full introduction to the R Framework for data science 

• Data Structures and Reading in R, including CSV, Excel and HTML data

• How to Pre-Process and “Clean” data by removing NAs/No data,visualization 

• Machine Learning, Supervised Learning, Unsupervised Learning in R

• Model building and selection…& MUCH MORE!

By the end of the course, you’ll have the keys to the entire R Machine Learning Kingdom!

NO PRIOR R OR STATISTICS/MACHINE LEARNING KNOWLEDGE REQUIRED:

You’ll start by absorbing the most valuable R Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R.

My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement R based data science in real life.

After taking this course, you’ll easily use data science packages like caret to work with real data in R…

You’ll even understand concepts like unsupervised learning, dimension reduction and supervised learning. Again, we’ll work with real data and you will have access to all the code and data used in the course. 

JOIN MY COURSE NOW!

Who this course is for:

  • Students Interested In Getting Started With Data Science Applications In The R & R Studio Environment
  • Students Wishing To Learn The Implementation Of Unsupervised Learning On Real Data
  • Students Wishing To Learn The Implementation Of Supervised Learning (Classification) On Real Data Using R

Course content

  • Introduction to the Course
  • Read in Data From Different Sources in R
  • Data Pre-processing and Visualization
  • Machine Learning for Data Science
  • Unsupervised Learning in R
  • Feature/Dimension Reduction
  • Feature Selection to Select the Most Relevant Predictors
  • Supervised Learning Theory
  • Supervised Learning: Classification
  • Additional Lectures

10 reviews for Clustering & Classification With Machine Learning In 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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