Advanced Analytics with R

This is the Course Landing Page for Advanced Analytics with R. Visiting this page will help you access alll the lecutre materials and other necessary announcements if any.

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Learning Objective

The ultimate aim of this course is to provide a gentle introduction to statistical learning techniques. I aim to expose the learners to a wide variety of techniques.¹

After successful completion of this course, a learner will have foundational understanding of statistical learning techniques, when to apply a given technique and how to use R to apply these techniques.

Pre-requisite

If you can comfortably understand the following code and are fairly confidant about the functions used in the code, you most likely have the necessary R programming skills to absorb the materials covered in this course.

## read data on disk and store as an object

data <- read_csv("file location/fil.csv")

## Data Wrangling

data %>% 
  filter(semister == 5) %>% 
  group_by(division) %>% 
  summarise(
    avg_attend = mean(attend, na.rm = T),
    max_score = max(score, na.rm = T)
  )

In case you are having difficulty in guessing what the above piece of code does, Please read the Chapter 5 of R for Data Science

Following are the programming techniques that are not required for this course but are highly useful and will make learning experience easier:

• Iterations
• Writing custom functions
• Data Visualization

Teaching Material

Here are links to lecture slides, this will keep updating. Please visit this page before every lecture to gain access to lecture slides.²

• Refresher: Introduction to R
• Refresher: Data Wrangling
• Refresher: Data Visualization using R
• Lecture 1: Resources and Introduction
• Lecture 2: Linear Regression
• Lecture 3: Classification
• Lecture 4: Resampling Methods
• Lecture 5: Exercises
• Lecture 6: Linear Model Selection and Regularization
• Lecture 7: Multiple Testing

Announcements

Here you will find any important Announcements regarding the course.

• The Lecture scheduled on the 16th of Aug has been delayed by an hour for Division 2 only. This means that the lecture will start at 11:45 am.

Get in Touch

The best way to reach me is by email. You can use either of the following:

• ayush.ap58@gmail.com
• ayush.patel@gipe.ac.in

Footnotes

1. There is a trade off here. Given the time constraint of 40 teaching hours and the choice of exposing to a wide variety of techniques, I can afford only a reasonable amount of depth to each topic.

2. The slides will be uploaded a day before or on the day of the lecture.