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Course Details
Module 1: Introduction to Machine Learning
- What is Machine Learning (ML)
- R packages for ML
- Installing R ML Packages
Module 2: Datasets
- Iris Dataset
- Mtcars Dataset
- Boston Housing Price Dataset
- Features
- Splitting Datasets for Training/Testing
Module 3: Supervised Learning
- What is Supervised Learning
- Performance Metric
- Decision Tree Classifier
- Random Forest Classifier
- Gaussian Navie Bayes (GNB) Classifier
- Support Vector Machine (SVM) Classifier
- Logistic Regression Classifier
- K-Nearest Neighbors (KNN) Classifier
- Linear Regression: Single and Multivariate,
- Variable Selection
- KNN Regression
Module 4: Unsupervised Learning
- What is Unsupervised Learning
- K-Means Clustering
- Hierarchical Clustering
- Dimensionality Reduction
Module 5: Intro to Neural Network (Optional)
- What is Neural Network
- Multi Layer Perceptron
Who Should Attend
- Data Scientists
- Data Analysts
- Marketeers
Prerequisite
Prerequisite
This is an intermediate course. the following knowledge is assumed
Software Requirement
Pls download and install the following software prior to the class
Trainers
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.
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.
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.
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.
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.
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.
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.
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.
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.
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
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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.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
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
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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 .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
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
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Will Recommend (Posted on 6/25/2018)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 RecommendReview by Nicky Ren
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More time allocated for course or split it into two days, as content is quite heavy (Posted on 11/19/2017)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 RecommendReview by HH ONG
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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)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 RecommendReview by Adriel Cheng
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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)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 RecommendReview by Chang Wei Lin
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Water in classroom (Posted on 8/21/2017)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 - Might RecommendReview by Chia Sin Fei
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Nil (Posted on 6/7/2017)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 RecommndReview by Marie Wong
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Less repetitive things like slicing data and more in depth about which situations you would use the different method (Posted on 2/26/2017)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 recommendReview by Dwight
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Nil (Posted on 7/31/2016)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 - Contents coveredReview by LIM KAH KHENG
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Awaiting for full day course purely on SHINY APPS (Posted on 7/31/2016)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 - excellentReview by lkk
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Very good course for those who already has R background.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 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)
