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Instructor-led Classroom Adult Training in Singapore - Modular Fast Track Skill-Based Trainings

WSQ - Data Mining and Machine Learning with Orange

Data mining is the process of finding anomalies, patterns and correlations within large data sets to predict outcomes. Using a broad range of techniques such as statistics and machine learning , you can use this information to increase revenues, cut costs, improve customer relationships, reduce risks and more.

Orange is a platform built for data mining, predictive analytics on a GUI based workflow. This signifies that you do not have to know how to code to be able to work using Orange and mine data, crunch numbers and derive insights.

Orange comes with many machine learning and predictive analytics toolbox such as supervised learning, unsupervised learning that make it a great tool for predictive analytics and machine learning

This 2 days WSQ Data Mining and Machine Learning courses will teach you how to apply data mining and machine learning techniques using Orange.

Course Learning Outcomes

By the end of the course, learners will be able to 

  • LO1 - Apply data mining and machine learning principles to assess business insights

  • LO2 - Integrate information from datasets
  • LO3 - Apply predictive data modelling techniques to identify underlying trends in data
  • LO4 - Apply machine learning classification techniques to gain new insights from data
  • LO5 - Apply clustering techniques to discover data pattern and make decision
  • LO6 - Develop prototype algorithms with dimension reduction techniques
  • LO7 - Construct association rules to Identify patterns across multiple data sets to derive insights

Certification

Two certificates will be awarded to trainees who have demonstrated competency in WSQ Data Mining and achieved at least 75% attendance.

  • A SkillsFuture WSQ Statement of Attainment (SOA) – Data Analytics MED-ACE-3018-1 under Media Skills Framework issued by WSG
  • Certification of Achievement issued by Tertiary Infotech Pte Ltd 

WSQ 80%-95% Funding

WSQ funding is only applicable to Singaporeans and PR. Subject to eligibility, the funding support is from 80% -95% subject to funding caps.

Full Fee GST Nett Fee after Funding (Incl. GST)
Normal MCES / SME WTS
$688 $48.16 $496.16 $116.96 $82.56

Normal: Singaporean/PR age 21 and above
MCES: Singaporean age 40 and above
WTS: Singaporean age 35 and above and earning  $2,000 or below per month

SkillsFuture Credit

For the unfunded portion, Singaporeans can use your SkillsFuture Credit to pay. Click here for SkillsFuture Credit submission

PSEA

Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding. Click here for ad-hoc PSEA application form.

WSQ Eligibility

Please fill up the WSQ Trainee Eligibility Form after you have registered for this course

Please do not pay up front. We will advise you on the eligibility and nett fee after registration

Course Code: CRS-Q-0040506-MED

Course Booking

$688.00 (GST-exclusive)
$736.16(GST-inclusive)

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

Topic 1 Overview of Data Mining and Machine Learning

  • Data Mining Process
  • Overview of Machine Learning
  • Impact of Data Mining and ML to Access Business Insights

Topic 2: Data Preparation

  • Import/Export Data
  • Filter Data
  • Join Data
  • Clean Data

Topic 3: Regression

  • What is Regression
  • Linear Regression
  • Underfitting and Overfitting
  • Regularization Techniques

Topic 4: Classification

  • What is Classification
  • Classification Algorithms
  • K-Fold Cross Validation
  • Model Evaluation Metrics
  • Confusion Matrix

Topic 5: Clustering

  • What is Clustering
  • K-Means Clustering
  • Silhouette Analysis
  • Hierarchical Clustering

Topic 6: Dimension Reduction

  • Principal Component Analysis (PCA)
  • Feature Ranking

Topic 7: Association Analysis

  • Association Rules
  • Constructing Rules

Final Assessment

  • Practical Performance (Written Assessment)
  • Oral Questioning

Course Admin

Prerequisite

The learner must meet the minimum requirement below :

  • At least O levels and above education
  • Read, write, speak and understand English

Software Requirement

  • Download and Install Orange before the class

Mode of Training

Instructor Classroom Training

WSQ Funding Validity Period

01 Mar 2020-01 Mar 2022

WSQ Course Fee Funding

Self-Sponsored

  • Click here for more info on the funding for self-sponsored.
  • Eligible Singapore Citizens can use their SkillsFuture Credit and PSEA funds to offset course fee payable after funding.

Employer-Sponsored

  • Click here for more info on the funding for employer-sponsored.
  • Absentee Payroll claimable by SMEs: Up to 80%of hourly basic salary capped at $7.50/hr
  • Absentee Payroll claimable by Non-SMEs: Up to 80% of hourly basic salary capped at $4.50/hr
  • Absentee payroll claimable by companies (SMEs and Non-SMEs) sponsoring candidates under WTS Scheme: Up to 95% of hourly basic salary (no dollar cap)

WSQ Assessment

  • Participants will be assessed through individual assessment
  • Passing Criteria – Participants are to answer all questions accurately in the individual written assessment.
  • Participants may need to attend additional coaching sessions and re-assessments if they do not pass the required competency standards. 

Who Should Attend

  • Data Scientists
  • Data Analysts
  • Engineers

Trainers

WSQ Tableau Data Visualization Trainer Dr. Alfred Ang is the founder of Tertiary Courses. He is a serial entrepreneur. He founded OSWeb2Design Singapore Pte Ltd in 2007 offering web development, e-commerce store development, graphics design, ebook publishing, mobile apps development, and digital marketing services. He established the first online gardening store in Singapore, Eco City Hydroponics Pte Ltd in 2000, offering a wide range of gardening products such as seeds, plant nutrients, hydroponics kits etc. Eco City Hydroponics has become the most popular and successful gardening store in Singapore. He founded Tertiary Infotech Pte Ltd in 2012 and transformed the business to a training platform, Tertiary Courses in 2014. Tertiary Courses offers a wide range of SkillsFuture courses for PMETs to upgrade their skills and knowledge. He also established Tertiary Courses Malaysia in 2016. He also founded Tertiary Robotics in 2015 offering Arduino, Raspberry Pi, Microbit and Robotics products

Dr. Alfred Ang earned his Ph.D. from National University of Singapore in 2000, majoring in Electrical and Electronics Engineering. He also completed an online MBA course with U21 Global based in Australia. He obtained his B.Sc (Hons) from National University of Singapore in 1992, majoring in Physics. He topped his Physics cohort for 3 consecutive years and funded his degree study with Book prizes, Study awards, bursaries and tuition. He has worked in Defence, Electronics and Semiconductor Industries. His current interests include Machine Learning, Deep Learning, Artificial Intelligence, Internet of Things, Robotics and Programming.

Dr. Alfred Ang is ACTA certified trainer. He was Distinguished Toastmasters (DTM) and Senior Member of IEEE. He has published more than 20 peer reviewed papers and co-inventors for more than 20 inventions.

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