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Machine Learning and Statistical Modeling with R Examples – Udemy

(10 customer reviews)

$15

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Description

What you’ll learn

  • understand the most common principles of machine learning and statistical modeling
  • perform machine learning tasks in R
  • understand which machine learning tool is suitable for a given problem
  • know what machine learning can do
  • implement machine learning and statistical modeling in your work

See things in your data that no one else can see – and make the right decisions!

Due to modern technology and the internet, the amount of available data grows substantially from day to day. Successful companies know that. And they also know that seeing the patterns in the data gives them an edge on increasingly competitive markets. Proper understanding and training in Machine Learning and Statistical Modeling will give you the power to identify those patterns. This can make you an invaluable asset for your company/institution and can boost your career!

Marketing companies use Machine Learning to identify potential customers and how to best present products.

Scientists use Machine Learning to capture new insights in nearly any given field ranging from psychology to physics and computer sciences.

IT companies use Machine Learning to create new search tools or cutting edge mobile apps.

Insurance companies, banks and investment funds use Machine Learning to make the right financial decisions or even use it for algorithmic trading.

Consulting companies use Machine Learning to help their customers on decision making.

Artificial intelligence would not be possible without those modeling tools.

Basically we already live in a world that is heavily influenced by Machine Learning algorithms.

1. But what exactly is Machine Learning?

Machine learning is a collection of modern statistical methods for various applications. Those methods have one thing in common: they try to create a model based on underlying (training) data to predict outcomes on new data you feed into the model. A test dataset is used to see how accurate the model works. Basically Machine learning is the same as Statistical Modeling.

2. Is it hard to understand and learn those methods?

Unfortunately the learning materials about Machine Learning tend to be quite technical and need tons of prior knowledge to be understood.

With this course it is my main goal to make understanding those tools as intuitive and simple as possible.

While you need some knowledge in statistics and statistical programming, the course is meant for people without a major in a quantitative field like math or statistics. Basically anybody dealing with data on a regular basis can benefit from this course.

3. How is the course structured?

For a better learning success, each section has a theory part, a practice part where I will show you an example in R and at last every section is enforced with exercises. You can download the code pdf of every section to try the presented code on your own.

4. So how do I prepare best to benefit from that course?

It depends on your prior knowledge. But as a rule of thumb you should know how to handle standard tasks in R (courses R Basics and R Level 1). You should also know the basics of modeling and statistics and how to implement that in R (Statistics in R course).

For special offers and combinations just check out the r-tutorials webpage which you can find below the instructor profile.

What R you waiting for?

Martin

Who this course is for:

  • You should take this course if you are interested in statistics and analytics
  • You should take this course if you want to use R to solve modeling problems
  • You should take this course if you encounter problems that need more complex statistical solutions
  • You should take this course if you want to enlarge your analytics toolbox

Course content

  • Introduction
  • Validation Methods
  • Classification
  • Tree Based Models
  • Clustering

10 reviews for Machine Learning and Statistical Modeling with R Examples – 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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