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Advanced R Data Analysis Training

This is an extension of the R Statistics Essential Training. R is a software package that provides a language and an environment for data manipulation and statistics calculation. This course will go through some advanced data analysis concepts techniques such as data extraction, data pre processing, data visualization, data modeling and finally data presentation

Topics include:

  • qqplots for data visualization
  • download data from file or web
  • data analysis using regression
  • data analysis using clustering
  • data analysis using classification
  • shiny for data presentation


SkillsFuture Credit Applicable for Individual

WDA Training Grant Applicable for Company

Course Code: CRS-N-0033597

Course Booking

$298.00

Course Date

Course Time

* Required Fields

Course Cancellation/Reschedule Policy

We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
Note the venue of the training is subject to changes due to class size and availability of the classroom.
Note the minimal class size to start a class is 3 Pax.

Course Details

Module 1: R Data Analysis Packages

  • Data Analysis Components
  • Data Analysis Steps
  • R Data Analysis Packages

Module 2: Obtaining Data

  • Reading Data from CSV file
  • Reading Data from Excel file
  • Reading Data from JSON file
  • Reading Data from XML file
  • Reading Data from Web
  • Reading Data from APIs

Module 3: Data Preprocessing

  • Mutating Data 
  • Merging Data
  • Reshaping Data
  • Missing Data

Module 4: Data Visualization

  • Using ggplot

Module 5: Advanced R Functions

  • Lapply
  • Sapply
  • Split
  • Mapply

Module 6: Data Modeling : Regression

  • Univariate and Multivariate Linear Model Regression
  • Polynomial Model Regression
  • Generalized Regression Models

Module 7: Data Modeling: Classification & Clustering

  • Classification
  • Clustering

Module 8: Time Series

  • Creating Time Series
  • Forecasting

Module 9: Data Presentation (Optional)

  • Shiny

Who Should Attend

  • Data analysts who perform data analysis using R
  • Financial analysts who use R for financial data analysis
  • Marketeers who use R for market analysis
  • Researchers who use R for data analysis

Prerequisite

This course assumes some basic knowledge of the R language and data science.

Trainers

R Programming TrainerRavi Kumar Tiwari got his PhD from NUS (Chemical Engineering) in 2013. After graduation, he worked 3 years as a research scientist in the Institute of High Performance Computing (IHPC). He is currently a big data R data analyst in Rakuten. His core skills are R, big data, Hadoop and machine learning.

R TrainerDwight Nuwan Fonseka have a degree in Biotechnology (from NUS) ,Advanced diploma in Pharamceutical management (from MDIS) and Masters in Education (from NTU). He have 8 years experience of teaching biology at O and A levels/ IB level in international schools in Singapore and overseas.

R TrainerZhu Tianming did her PhD in NUS, major in Statistics, and will graduate in August 2017. She has been a part-time teaching assistant for more than three years in NUS. She has taught the modules related to probability, regression analysis, categorical data analysis and multivariate statistical analysis. Her research interests are functional data classification and her core skills are R, machine learning and statistical analysis.

Matlab and R TrainerZhang Liang is a PhD candidate of Statistics at NUS, his research is mainly on developing statistical methods of hypothesis testing for high-dimensional data, and application to biostatistical problems. He has a couple of years experience using MATLAB and R for his research and real data analysis.

R TrainerWesley Goi is currently in his final year of his PhD in Bioinformatics at National University of Singapore (NUS) where he previously received his degree in Molecular Biology at NUS (Honours 2nd Uppers). He was the TA for Introductory Bioinformatics LSM2241. He specialises in analysing high throughput DNA and RNA sequencing data of complex microbial communities using network analyses and various functional analyses. In his previous projects he has applied machine learning methods to vaccine discovery.

Data Science TrainerDr. Shailey Chawla is an experienced academician and researcher with over 10 years of experience in teaching and research. Her PhD research topic was on Web Requirements Engineering. She has published various research papers and book chapters in reputed international journals and conferences. Her recent research has been in Big Data Analytics at Hong Kong Polytechnic University where she worked on Urban Data Analytics and Educational Data Mining. She is proficient in R, Python, Java, Advanced Excel, Data Mining, C, Linux programming among various other core computing subjects.

Customer Reviews (7)

Will RecommendReview by Chia Sin Fei
1. Do you find the course meet your expectation?
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3. How do you find the training environment
sharing more use case and how to apply will help us to understand how to apply R in work (Posted on 6/5/2017)
Will RecommendReview by Sean Lee
1. Do you find the course meet your expectation?
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Nil (Posted on 5/26/2017)
Trainer was very approachable and clear in explanations. Delivered his lecture materials well and provided timely clarification on our queries. Great dedication for a full day course!Review by David
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
In a small group teaching setting, would be better if trainer could contact the attendees earlier to create a slightly more customised tutorial if possible. We would have loved to have gone through a little bit more on logistics regression and survival curve analysis if we had been contacted earlier.
(Posted on 3/11/2017)
Will RecommndReview by Meenakshi Krishnamoorthi
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Nil (Posted on 1/20/2017)
Will RecommendReview by Lee Chui Teng
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Nil (Posted on 9/19/2016)
Will recommendReview by Xin Chen
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Nil (Posted on 7/18/2016)
Will recommendReview by Dwight Fonseka
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3. How do you find the training environment
More examples of visualization techniques (Posted on 7/16/2016)

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