Data Science with R

An Introductory Short Course in Applied Statistics and Data Analytics

Payap Logo

To be hosted 3, 10 and 17 June 2014 by the
Payap University Faculty of Science
Preregistration required.

In 1 day, a typical Internet user will

Office Worker

  • generate 5 GB of information
  • upload 10 photographs
  • send 58 email messages
  • read 60 social media messages
  • submit 10 search queries
  • watch 16 videos

3.2 billion Internet users

And the sources of data keep growing...

DS

  • Mobile devices
  • Sensor networks
  • Smart devices
  • Internet of Things
  • More users

But...

  • 95% data collected is never used.
  • 39% market data is infrequent and outdated
  • 43% managers seldom use data to drive decision making
  • 26% companies do not use data to improve customer experience

Data Science: a new academic discipline

DS

  • data acquisition, encoding and standardization
  • data security, storage and retrieval
  • data analytics, modeling and graphics
  • data mining, forecasting and decision making

What will I learn in this course?

  • Gather insights from data
  • Discover significant factors and associations
  • Identify trends and predict expected futures
  • Uncover the key points in text and datasets
  • Use data notesbooks to draft research papers
  • Find useful datasets for research and education

Short Course Objectives

  • Hands-on tutorial in R to build skills in data science
  • Learn how to construct and manage data sets
  • Analyze, model and visualize relationships in the data
  • Test for statistical significance and levels of confidence
  • Apply machine learning and data mining techniques

Software to be Covered

  • R - the statistical language
  • R commander - platform for data analysis
  • R Studio - development environment for software, graphics, and documentation
  • R Shiny- interactive web pages

R Studio

Short Course Schedule

3 Sessions June 2015

  • 3 June: Introduction to data analytics in R
  • 10 June: Search for data patterns and relationships
  • 17 June: Data modelling, forecasting, and mining

Daily Routine:

Daily routine

Time Activity
 9:00-10:30 First session
10:30-10:45 Break
10:45-12:15 Second session
12:15-13:00 Lunch
13:00-14:15 Third session
14:15-14:30 Break
14:30-15:30 Fourth session

Day 1: Intro to Data Science in R

  • Installation of software
  • Working with interactive slides and notebooks
  • Acquiring data sets from different sources
  • Descriptive statistics
  • Comparison of individuals and groups
  • Useful matrix operations
  • Qualitative text analysis

Day1

Day 2: Patterns and Relationships

Day2

  • Confidence limits and outliers
  • Correlation and regression
  • Multiple variant regression
  • Chi Square and ANOVA
  • Clusters and associations
  • Geolocation
  • Word clouds

Day 3: Models, Forecasts, Analytics

  • Factor and decision tree analysis
  • Work flow analysis
  • Associations and synergy
  • Machine learning approaches to data analysis
  • Forecasting methods

Day3

To get the most out of this course...

You should:

Registration Fees

  • The regular cost of registration is 5,000 baht per person

  • There are special reduced price for a limited number of seats:

    • Pioneer Price: 3,500 baht for the first 10 paid registrations
    • Payap Student and Staff Special: 4,000 baht for the next 5 paid registrations after the Pioneer Price

There is limited seating so register and pay early to get the best price.

What is included with the registration?

  • Notebook
  • USB drive preloaded with

    • R, R Studio and R Commander
    • Course workbook
    • Course manual
  • Lunch, breaks and refreshments

Data Science in R

Mark your calendar for 3 June 2017

Click here to register online today.