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HRDF Approved Training Provider in Malaysia - Modular Fast Track Skill-Based Trainings

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

Course Highlights

  • 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

Certificate

All participants will receive a Certificate of Completion from Tertiary Courses after achieved at least 75% attendance.

 

HRDF SBL Claimable for Employers Registered with HRDF

HRDF claimable

Course Code: M294

Course Booking

MYR880.00

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

Module 3: Data Exploration and Cleaning

  • Exploring data
  • Imputing missing data
  • Dealing with Outliers

Module 4: Data Preprocessing

  • Selecting columns and rows
  • Calculated columns
  • Arranging data
  • Chain operations
  • Joins
  • Summarize and group by

Module 5: Data Reshaping

  • Splitting and merging columns
  • Rearranging and reorienting columns

Module 6: Data Visualization

  • ggplot2 syntax and analysis

Module 7: Advanced Analysis (optional)

  • Map function
  • User defined functions & logical testing
  • pmap function

Course Admin

Prerequisite:

This is an intermediate course. the following knowledge is assumed

Software Requirement

Pls download and install the following software prior to the class

Who Should Attend

  • Data Scientists
  • Data Analysts
  • Marketeers

Trainers

Tableau TrainerLee Cheong Loong is a manager with an EMBA – 21 years working experience indifference role/ Dept. (Sales, Logistic, IT, Online Store, Internal Trainer and Customer services), involved in multiple IT project (Server P2V upgrade, Network infra upgrade, and ERP system Deployment). He has switched career to Project management role, Big - data / Data scientist related project, with Professional Certification Big Data & Analytics, Professional Certificate in Tableau, & Pass the HRDF Certified Trainer Programme. He also involves in AI chatbot and application development to help small-medium practitioner (accounting industry).

R Statistics TrainerMostafa has more than 5 years’ experience in teaching mathematics and statistics. His main teaching interests are statistical topics such as descriptive analysis and basic data modeling, regression analysis, design of experiment, non-parametric methods, and statistical software such as SAS, R, SPSS, and Minitab. He has started computer programming using visual basics and C++ around 15 years ago, and he has more than 10 years’ experience in programming using R.

R Trainer Dr. Ghazaleh Babanejad has received her Ph.D from University Putra Malaysia in Faculty of Computer ‎Science and Information Technology. She is working on recommender systems in the ‎field of skyline queries over Dynamic and Incomplete databases for her PhD thesis. She is also working ‎on Data Science field as a trainer and Data Scientist. She worked on Machine Learning and Process ‎Mining projects. She also has several international certificates in Practical Machine Learning (John ‎Hopkins University) Mining Massive Datasets (Stanford University), Process Mining (Eindhoven ‎University), Hadoop (University of San Diego), MongoDB for DBAs (MongoDB Inc) and some other ‎certificates. She has more than 5 years of experience as a lecturer and database administrator.

Customer Reviews (9)

might recommend Review by Course Participant/Trainee
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. (Posted on 17/01/2020)
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. (Posted on 13/12/2019)
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. (Posted on 12/08/2018)
Will Recommend Review by Course Participant/Trainee
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To improve in terms of deliverable (more easy to understand) (Posted on 18/07/2017)
Will Recommend Review by Course Participant/Trainee
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It would be better if we can invite the speaker to share her knowledge at our university. (Posted on 17/07/2017)
Might Recommend Review by Course Participant/Trainee
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not to conduct on Friday of which Muslim need to have longer break during lunch hour for Friday prayers. (Posted on 17/07/2017)
Will Recommend Review by Course Participant/Trainee
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More examples of visualization techniques (Posted on 21/10/2016)
Will Recommend Review by Course Participant/Trainee
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Nil (Posted on 21/10/2016)
Will Recommend Review by Course Participant/Trainee
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
Nil (Posted on 21/10/2016)

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