About Course
Course Structure
Financial Matters
About Course
Course Objectives
Participant will learn:- Create various charts to explore categorical data
- Create various graphs and distributions to explore numerical data
- Find and understand relationships among variables
- Understand how to process missing values
- Identify and process outlier data points
Course Description
This course introduces the statistical techniques and visualisation techniques to explore a dataset.The course covers the following:
• Exploring different types of data such as numeric, categorical etc.
• Univariate and Bivariate analysis
• Dealing with badly formatted data
• Outlier identification and treatment
Trainer's Profile
Mike Wee Toon Kim
Mike Wee is an experienced IT professional with over 20 years of expertise in deploying, supporting, and teaching enterprise systems. Throughout his career, he has worked with leading global companies such as BMW, Mercedes-Benz, and HP, leveraging his knowledge in enterprise computing to drive significant technological advancements and operational efficiencies.Mike's key domain areas encompass a wide range of critical IT functions, including Enterprise Computing, Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), Analytics, Data Visualisation, Machine Learning, SAP, Salesforce, PowerBI, Tableau, and Python. His multifaceted skill set enables him to provide comprehensive solutions that meet the complex needs of modern businesses.
Educationally, Mike Wee holds a Master’s Degree in Business Administration (MBA) from Nanyang Business School, Nanyang Technological University (NTU), and a Master of Education (MEd) from the University of Adelaide. He also possesses a Bachelor’s Degree (Honors) in Mechanical Engineering from NTU. Complementing his academic achievements, Mike is certified in Advanced Certificate in Training and Assessment (ACTA) and is a certified Scrum Master, underscoring his commitment to continuous professional development and excellence in project management.
Mike's extensive experience and diverse skill set make him an asset in the IT field. His proficiency in cutting-edge technologies and enterprise systems has enabled numerous organisations to achieve their strategic goals through effective IT solutions and innovative approaches. Whether it's through enhancing operational capabilities or teaching the next generation of IT professionals, Mike consistently demonstrates a passion for technology and a dedication to excellence.
Course Structure
TPG course reference No.
TGS-2021006411
Data Exploration (Synchronous e-learning)
Create various charts to explore categorical data
Create various graphs and distributions to explore numerical data
Find and understand relationships among variables
Understand how to process missing values
Identify and process outlier data points
Financial matters
Course fees payable (incl. GST & excl. supplementary fee)
| Description | Data Exploration (Synchronous e-learning) | Total course fee |
|---|---|---|
| Full Course fee | $1,744.00 | $1,744.00 |
| Enhanced Training Support for SMEs for Singapore Citizen | $203.20 | $203.20 |
| Enhanced Training Support for SMEs - SPR & LTVP+ | $203.20 | $203.20 |
| SkillsFuture Mid-Career Enhanced Subsidy for Singapore Citizen aged 40 and above | $203.20 | $203.20 |
| SkillsFuture Baseline Funding for Singapore Citizen Aged Below 40 | $523.20 | $523.20 |
| SkillsFuture Baseline Funding for SPR/LTVP+ | $523.20 | $523.20 |
GST rate
The course fees payable above are inclusive of 9% GST rate.
Payment option
The payment needs to be made upon the application is submitted.
Allowed payment by
The course fee allows to be paid by:
Post-Secondary Education Account (Adhoc withdrawal form);
SkillsFuture Credits (SFC);
Credit card (e-payment);
Debit card (e-payment);
PayNow (e-payment).
Post-Secondary Education Account (Adhoc withdrawal form);
SkillsFuture Credits (SFC);
Credit card (e-payment);
Debit card (e-payment);
PayNow (e-payment).
Refund and withdrawal policy
- Please note that a 100% refund will be available if the withdrawal request is submitted more than or equal to 14 days before the course start date.
- Please note that a 50% refund will be available if the withdrawal request is submitted less than 14 days before the course start date.
- Please note that no refund will be available if the withdrawal request is submitted on or after the course start date.