Practical Data Science using RapidMiner

  • TTDT02
  • Classroom
  • Fundamental
  • Thai
AI & Data Technology

การประยุกต์ใช้ RapidMiner สำหรับการทำงานด้าน Data Science และ AI
*** หลักสูตรเน้นใช้ Tools (RapidMiner) ไม่มีการเขียนโปรแกรม ***

Course description

Days :
3 Day(s)
Duration :
18 Hour(s)
Time :
09:00:00 - 16:00:00
Training Date :
08 November 2022 - 10 November 2022
Status :
Open Register
Name :
Mr.Veerasak Krisanapraphan
Language :
Venue :
ห้องอบรมชั้น 3 อาคารซอฟต์แวร์พาร์ค
Type :
Practical Data Science using RapidMiner

Objectives (วัตถุประสงค์) :

  • Able to understand the workflow of Data Science in practical way
  • Able to apply the statistical knowledge to the business problems
  • Able to apply the machine learning knowledge to the business problems
  • Able to understand the use cases and able to apply to students’ business problems.

Data Scientist, Data Analysis Engineer, Data Engineer, BI Consultant, BI Programmer,
System Programmer, System Analyst, Development Manager, Project Manager or
Chief Technology Officer, Chief Innovation Officer.

Benefits (ประโยชน์ที่จะได้รับ) :

  • Master the use of the RapidMiner interactive environment   
  •  Explore and understand how to use the RapidMiner documentation   
  • Read Structured Data into RapidMiner from various sources   
  • Deal with missing data   
  • Understand base RapidMiner visualization tools   
  • Use RapidMiner for descriptive statistics   
  • Use RapidMiner for inferential statistics
  • Write multivariate models in RapidMiner
  • Understand confounding and adjustment in multivariate models   
  • Understand interaction in multivariate models
  • Using Machine Learning in RapidMiner
  • Understand use cases and able to adapt to students’ environment

1.  What is Data Science?
2.  What is AI?
3.  Methodologies
4.  RapidMiner Introduction

  • IDE
  • Help
  • Process

5.  RapidMiner and CRISP-DM
6.  Reference Architecture for Data Science
7.  Introduction to Advanced Analytics
8.  ETL in RapidMiner
9.  Descriptive Analytics vs Referential Analytics
10. Exploratory Analysis

  • Univariate Analysis

11. Advanced Plot

  • Bivariate Analysis
  • Multivariate Analysis

12. Implementing Machine Learning Models with Rapidminer Stuidio

  • Supervised Learning Machine Learning Model
  • Unsupervised-Learning Machine Learning Model

13. Model Validation and Performance
14. Use Cases and Practices

  • Horizontal Use Cases
  • Vertical Use Cases

i.    Manufacturing
ii.    Retail
iii.    Transportation
iv.    E-Commerce
v.    Agriculture

Payment can be made by:

    1. Cash or Credit Card or Bank Cheque payable to “Software Park Thailand #2” (a post-dated cheque is not accepted) on the first day of the service or within the last day of the service.
     2. Account transfer and send the proof of the payment (the deposit slip) via fax or email to fax no. 02-583-2884 or email

        2.1 Siam Commercial Bank, Chaengwattana Branch
             Saving Account Number: 324-2-56262-0
             Account Name: Software Park Thailand#2

        2.2 Krungsri Bank, Chaengwattana (Software Park) Branch
             Saving Account Number: 329-1-34850-3
             Account Name: Software Park Thailand#2

- Withholding tax (3%) is exempt.
- Should you need to withdraw, you must send the notice of the withdrawal in writing no later than 7 working days before the commencement date. The cancellation less than 7 days will be subject to a fine of 40% of the fee.
- Software Park Thailand reserves the rights to cancel courses due to unforeseen circumstances.

Contact Person

For more information, contact our course coordinator on:

Juntima  Klumchaun

Tel: 02-583-9992 Ext. 81424

Tel: 02-564-7000 Ext. 81424


You are encouraged to use the course schedule as a guide to plan your training. The schedule is accessible at for more information.

12,000 THB .

Enroll now

Course Detail :
Days :
3 Day(s)
Duration :
18 Hour(s)
Time :
09:00:00 - 16:00:00
Training Date :
08 November 2022 - 10 November 2022
Status :
Open Register

Instructor info
Mr.Veerasak Krisanapraphan