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Workshop on Advanced Data Analytics

  

This workshop introduces fundamental concepts and methods for machine learning and data mining. The objective is to familiarise the participants with commonly used learning algorithms and techniques and their applications, as well as general questions related to analysing and handling data sets. The emphasis will be thus on machine learning and data mining algorithms and applications, with some broad explanation of the underlying principles. 

 Course Objectives

  • To introduce participants to the techniques of machine learning and data mining
  • To develop skills of using machine learning and data mining algorithms and software to conduct data analysis and research study

There are 10 sessions in this workshop and each session is 3 hours duration (2pm - 5pm).

Session

Topic

Schedule

1.

 

Introduction, Data Pre-Processing

Data Reduction: Dimension Reduction, Features Selection, Data Cubes

14 Sep 2017

 

2.

Association Rules, Sequential Patterns, Correlations

21 Sep 2017

3.

Classification I: KNN, Naïve Bayesian, Decision Trees

5 Oct 2017

4.

Classification II: Discriminant Analysis and SVM

25 Oct 2017

5.

Classification III: Neural Networks, others, Predictive Validation and Ensembles (including predictive evaluation)

16 Nov 2017

6.

Clustering I: Similarities, Partitioning-based Algorithm

23 Nov 2017

7.

Clustering II: Hierarchical, Density-based Clustering, Subspace Clustering and Segmentation Validation (including segmentation evaluation)

11 Jan 2018

8.

Anomaly and Outlier Detection

25 Jan 2018

9.

Advanced Topic I: Advances in Similarity Functions and Clustering

22 Feb 2018

10.

Advanced Topic II: Introduction to Text Analysis

1 Mar 2018

 

 Course Fees   : S$ 1,500.00 (Inclusive of GST)

 Prerequisites  : Participants should be familiar with standard statistical methodologies and have some experience using software to conduct data analysis

 Notes               : RapidMiner will be used as main software for analysis.  However, whenever is possible algorithms in R or Python will be shared. 

                          * Participants will bring their own notebooks installed with RapidMiner

 Course Leader: Associate Professor Anthony K. H. Tung

 Registration    : Fill up the application form (Download the application form) and email to This e-mail address is being protected from spambots. You need JavaScript enabled to view it