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Essential Machine Learning with R

Essential Machine Learning with R

12 Review(s) | Add Your Review

Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention

Many industries working with large amounts of data have recognised the value of machine learning technology. By gleaning insights from this data, organisations are able to work more efficiently or gain an advantage over competitors.

In this basic machine learning course with R, you will learn the fundamental of machine learning using R. R is a good tool to learn machine learning due to its user friendliness and large community support

Course Highlights

What is machine learning
Regression Models
Classification Models

Course Objectives

By the end of the training, learners will be able to:

Identify appropriate machine learning methods to address the problems and issues
Perform data analysis using machine learning methods
Draw inferences from the data analysis - Using R for machine learning

Certificate

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

Funding and Grant Applications

Click the links below to apply. Note that you need to register the course first.

For Singaporeans: SkillsFuture Credit

For Company: SSG Training Grant

Course Code: CRS-N-0034714

Course Booking

$298.00 (GST-exclusive)

$318.86(GST-inclusive)

Course Date * Course Date

Course Time * Course Time: No. of Participants

Name(s) on Certificate *

NRIC (Needed only for TRAQOM Survey and SkillsFuture Credit Verification)

Additional Message or Emails for Course Notification

* 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 Introduction to Machine Learning

What is Machine Learning
Types of Machine Learning
Supervised vs Unsupervised Learning
Python vs R for Machine Learning
Install R Machine Learning Package

Module 2 Data Preprocessing

Sample Data
Impute Missing Data
Normalize Data
Split Data

Module 3 Regression Methods

What is Linear Regression
Regularization - Bias vs Variance Tradeoff
Lasso Regression
Ridge Regression

Module 4 Classification Methods

What is Classification
Logistic Regression
Gaussian Naive Bayes (GNB)
K Nearest Neighbor (KNN)
Support Vector Machine (SVM)
Decision Tree
Confusion Matrix
ROC and AUC Analysis

Course Admin

Prerequisite

This is an intermediate course. the following knowledge is assumed

R Programming

Software Requirement

Please download and install the following software prior to the class

R https://cran.r-project.org/
R Studio https://www.rstudio.com/products/rstudio/download/

Who Should Attend

Data Scientists
Data Analysts
Marketeers

Trainers

R Machine Learning Trainer Dr. Ravi Kumar Tiwari got his PhD from NUS (Chemical Engineering) in 2013. After graduation, he worked 3 years as a research scientist in the Institute of High Performance Computing (IHPC). He is currently a big data R data analyst in Rakuten. His core skills are R, big data, Hadoop and machine learning.

R Machine Learning Trainer Dwight Nuwan Fonseka have a degree in Biotechnology (from NUS) ,Advanced diploma in Pharamceutical 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.

R Machine Learning Trainer Herman Tan is a certified Business Intelligence Professional by TDWI (The Data Warehouse Institute). He has developed analytics solution for businesses for the last 15 years. He is proficient in SQL, data management using Pentaho and Microsoft SQL Server, Oracle, and predictive analytics using open source tools mainly in R. Herman has conducted hands-on courses in R and Pentaho for Banking and Retail as well as instructor for NUS Masters of Science in Business Analytics program.

R Machine Learning Trainer Dr. Zhu Tianming did her PhD in NUS, major in Statistics, and will graduate in August 2017. She has been a part-time teaching assistant for more than three years in NUS. She has taught the modules related to probability, regression analysis, categorical data analysis and multivariate statistical analysis. Her research interests are functional data classification and her core skills are R, machine learning and statistical analysis.

R Machine Learning Trainer Dr Brandon Ooi has a Bachelors degree in Computer Engineering and a PhD in Bioengineering from the National University of Singapore. He has published papers on machine learning, bioinformatics and microarray data analysis. He has six years of teaching experience at the polytechnic level and was also involved in the creation and teaching of modules for adult learners.

R Machine Learmning Trainer Dr Zheng Zejun has seven years’ experience in the data-mining field. Zejun worked as a (Sr.) bioinformatics scientist for six years and currently works as a data scientist manager. Dr. Zheng;s expertise covers machine learning, statistics, algorithm design, bioinformatics and high performance computing. He has published three machine learning algorithms on well-recognized academic journals together with the open source software (CUDA-CRISY, FSOM, DYSC). Zejun is professional with an extensive set of programming languages, including C/C++, Python, R, JAVA and flask for data driven analytics and scalable computing. He has also a broad knowledge of algorithms and mathematical models in the data-mining field.

R Machine Learning Trainer Wesley Goi is currently in his final year of his PhD in Bioinformatics at National University of Singapore (NUS) where he previously received his degree in Molecular Biology at NUS (Honours 2nd Uppers). He was the TA for Introductory Bioinformatics LSM2241. He specialises in analysing high throughput DNA and RNA sequencing data of complex microbial communities using network analyses and various functional analyses. In his previous projects he has applied machine learning methods to vaccine discovery.

Data Science Trainer Dr. Shailey Chawla is an experienced academician and researcher with over 10 years of experience in teaching and research. Her PhD research topic was on Web Requirements Engineering. She has published various research papers and book chapters in reputed international journals and conferences. Her recent research has been in Big Data Analytics at Hong Kong Polytechnic University where she worked on Urban Data Analytics and Educational Data Mining. She is proficient in R, Python, Java, Advanced Excel, Data Mining, C, Linux programming among various other core computing subjects.

R Machine Learning Trainer Ariff is a recent Graduate from Murdoch University in BSc in Business Information System and Management (Double Major). He is a MOE Registered Instructor teaching in most of the Information Technology and Multimedia aspects such as Web programmer, Mobile App Developer, Video director and editor, and game development and design (PC and Mobile). Besides Information Technology and Multimedia, he is also giving entrepreneurship, leadership workshops and motivation speech training.

He has a strong passion in IT and gaming design been since 2005. He is currently doing games design for his own project and continues to teach and share his knowledge. He still hungers for new skills to keep himself up to date as technology continues to change.

R Machine Learning Trainer Siva Kumar is an experienced Solutions Architect with a demonstrated history of working in the computer software industry. Skilled in J2EE Web Services, Oracle Database, Maven, C++, and Apache Kafka. He is a strong engineering professional with a Bachelor of Technology (B.Tech.) focused in Computer Science from JNTU University Hyderabad.

Customer Reviews (12)

Will Recommend Review by Katherine

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

Thank you for running the R-machine learning short course on 6 August, despite being the sole participant. Lisa was an excellent instructor! I have learnt heaps.

FYI, I will be looking to attend a series of courses at your centre in the next few months, to upskill myself (Posted on 8/8/2018)

Excellent course with experienced trainer.Review by Eugene Lum Yao Jun

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

Dr Ravi Kumar is an excellent trainer in the subject, with relevant domain expertise. He is able to provide intuitive insight on the inner workings of machine learning algorithms without diving into the math. Interactive RShiny visualizations were used to explain models and algorithms, minimizing confusion and .
I highly recommend this course for anybody seeking to gain a foothold into machine learning, as it provides both practical examples for practice and an understanding of how the algorithms work. (Posted on 6/26/2018)

I learned a lot in this course, and the instructor is very good.Review by Lum Yao Jun

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

Will Recommend (Posted on 6/24/2018)

Will RecommendReview by Nicky Ren

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 time allocated for course or split it into two days, as content is quite heavy (Posted on 11/19/2017)

Will RecommendReview by HH ONG

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

The course was effective in providing a basic understanding of various ML techniques. Trainer was knowledgable, explained content well, and was patient in answering participants' questions. (Posted on 8/21/2017)

Will RecommendReview by Adriel Cheng

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

Summarize key methods or approaches and specify in summary what type of data can be used for each method at the last portion of the training. (Posted on 8/21/2017)

Will RecommendReview by Chang Wei Lin

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

Water in classroom (Posted on 8/21/2017)

Might RecommendReview by Chia Sin Fei

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 6/7/2017)

Will RecommndReview by Marie Wong

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

Less repetitive things like slicing data and more in depth about which situations you would use the different method (Posted on 2/26/2017)

Will recommendReview by Dwight

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 7/31/2016)

Contents coveredReview by LIM KAH KHENG

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

Awaiting for full day course purely on SHINY APPS (Posted on 7/31/2016)

excellentReview by lkk

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

Very good course for those who already has R background.

Trainer has simplify the ML codes using shiny apps to demo the concepts.

awaiting for Programming for Shiny - if the school has such course (Posted on 7/31/2016)