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Full Machine Learning with R

Embark on an enriching journey into the world of Machine Learning with R at Tertiary Courses. This all-encompassing course is designed to take participants from the foundational concepts of machine learning through to the intricacies of neural networks. With a balance of both supervised and unsupervised learning models, the curriculum ensures a robust understanding, prepping learners for real-world challenges.

In addition to theoretical knowledge, the course focuses on pragmatic skills. Participants will hone their proficiency in identifying the most appropriate machine learning methods tailored to specific problems. Leveraging the power of R for hands-on data analysis, students will derive actionable insights, fostering their ability to draw astute inferences. With the seamless blend of theory and application, learners are set on a path to become adept at data-driven decision-making using R.

Course Brochure

Download Full Machine Learning with R brochure

Certificate

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

Funding and Grant Applications

SGTech STAR Fund

Free course for SGTech members after SGTech STAR Funding. For details, check here.

For WSQ funding, please checkout the details at NICF - Pattern Recognition and Machine Learning with R

Course Code: C925

Course Booking

The course fee listed below is before subsidy/grant, if applicable. We will apply for the grant and send you the invoice with nett fee.

$600.00 (GST-exclusive)
$654.00 (GST-inclusive)

Course Date

Course Time

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Post-Course Support

  • We provide free consultation related to the subject matter after the course.
  • Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Course Cancellation/Reschedule Policy

  • You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commerce.
  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
  • Note the venue of the training is subject to changes due to availability of the classroom

Course Details

Topic 1 Overview of Machine Learning

  • Introduction to Machine Learning
  • Pattern Recognition Problems Suitable for Machine Learning
  • Supervised vs Unsupervised Learnings
  • Types of Machine Learning
  • Machine Learning Techniques
  • R Packages for Machine Learning

Topic 2 Regression

  • What is Regression
  • Applications of Regression
  • Least Square Error Minimization
  • Data Pre-processing
  • Bias vs Variance Trade-off
  • Regression Methods with Regularization

Topic 3 Classification

  • What is Classification
  • Applications of Classification
  • Classification Algorithms
  • Confusion Matrix
  • Classification Performance Evaluation

Topic 4 Clustering

  • What is Clustering
  • Applications of Clustering
  • Distance Measure
  • Clustering Algorithms
  • Clustering Performance Evaluation
  • Anomaly Detection Problem

Topic 5 Principal Component Analysis

  • Principal Component Analysis (PCA) and Dimension Reduction
  • Applications of PCA
  • PCA Workflow

Topic 6 Neural Network

  • What is Neural Network
  • Activation Functions
  • Deep Learning vs Machine Learning
  • Classification Using Neural Network

Topic 7 Ensemble Methods

  • Random Forest Ensemble
  • Gradient Boost and XGBoost Ensemble
  • Stacking Ensemble

Topic 8 Hyperparameter Tuning

  • Exhaustive Grid
  • Random Search

Course Info

Promotion Code

Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.

Minimum Entry Requirement

Knowledge and Skills

  • Able to operate using computer functions
  • Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

  • Positive Learning Attitude
  • Enthusiastic Learner

Experience

  • Minimum of 1 year of working experience.

Target Age Group: 18-65 years old

Minimum Software/Hardware Requirement

Software:

Hardware: Window or Mac Laptops

Job Roles

  • Data Scientists
  • Data Analysts
  • Marketeers

Trainers

Dwight Nuwan Fonseka: Dwight Nuwan Fonseka is a ACLP certified trainer. He have a degree in Biotechnology from NUS ,Advanced diploma in Pharmaceutical 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.

Marcel Leng: Marcel Leng is a ACTA certified. Marcel graduated with majors in Applied Mathematics and Physics from the National University of Singapore.

His core specialisation skills are R, Python, Machine Learning, Statistical Analysis, and Data Visualisation in Tableau. His current interests include Machine Learning, Deep Learning, Artificial Intelligence, Internet of Things, Robotics and Programming.

Customer Reviews (7)

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
. (Posted on 5/26/2024)
Trainer explained concepts in an intuitive 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
Trainer explained concepts in an intuitive and relatable way, facilitating participant's understanding even without background knowledge in the subject. He also shared additional resources for further reading/exploration (Posted on 4/24/2022)
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
More examples (Posted on 1/23/2021)
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
. (Posted on 3/4/2020)
This is an excellent course for people who has interest in Machine learning and R 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
This is an excellent course for people who has interest in Machine learning and R. The tutor is knowledgeable and is able to conduct the course in a very engaging manner. (Posted on 2/7/2020)
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
. (Posted on 10/3/2019)
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
. (Posted on 10/3/2019)

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