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3 Students

#### What Will You Learn?

• How to use RapidMiner for data mining
• How to interpret and prepare data
• How to create models for data evaluation

#### Requirements

• Basic computer proficiency
• Interest in data mining

#### Curriculum

Course consist of total 1h 22min of content, in total.

##### Section 2: Data Understanding
05:48
Data Understanding - Statistics
00:46
Data Understanding - Scatterplot
00:56
Data Understanding - Line
00:45
Data Understanding - Bar
00:38
Data Understanding - Histogram
00:47
Data Understanding - Boxplot
00:33
Data Understanding - Pie
00:40
Data Understanding - Scatterplot Matrix
00:43
##### Section 3: Data Preparation
04:51
Data Preparation - Normalization
01:41
Data Preparation - Replace Mssing Value
01:15
Data Preparation - Remove Duplicates
01:08
Data Preparation - Detect Outlier
00:47
##### Section 4: Modeling
53:15
Simple LInear Regression
03:07
Simple Linear Regression 2
04:21
KMeans Clustering
03:06
KMeans Clustering 2
01:52
Agglomeration Clustering
03:46
Agglomeration Clustering 2
01:07
Decision Tree ID3 Algorithm
09:15
Decision Tree ID3 Algorithm 2
02:20
Decision Tree ID3 Algorithm 3
00:34
Decision Tree ID3 Algorithm 4
00:43
KNN Classification
03:50
KNN Classification 2
01:06
KNN Classification 3
00:44
Naive Bayes Classification
05:37
Naive Bayes Classification 2
00:58
Naive Bayes Classification 3
01:10
Neural Network Classification
05:45
Neural Network Classification 2
00:59
Neural Network Classification 3
01:20
What Algorithm to Use?
01:35
##### Section 5: Evaluation
08:17
Model Evaluation
03:45
Model Evaluation 2
04:32

#### Eric Goh

Eric Goh is a data scientist, software engineer, adjunct faculty and entrepreneur with years of experiences in multiple industries. His varied career includes data science, data and text mining, natural language processing, machine learning, intelligent system development, and engineering product design. He founded SVBook and extended it with DSTK.Tech and EMHAcademy. DSTK.Tech is where Eric develops his own DSTK data science software. Eric also publishes "Learn R for Applied Statistics" at Apress, and published 5 books at LeanPub and SVBook. He teaches the content at Udemy and EMHAcademy. During his free time, Eric is also an adjunct faculty at Universities and Institutions.

Eric Goh has been leading his teams for various industrial projects, including the advanced product code classification system project which automates Singapore Customâ€™s trade facilitation process, and Nanyang Technological University's data science projects where he develops his own DSTK data science software. He has years of experience in C#, Java, C/C++, SPSS Statistics and Modeller, SAS Enterprise Miner, R, Python, Excel, Excel VBA and etc. He won Tan Kah Kee Young Inventors' Merit Award and Shortlisted Entry for TelR Data Mining Challenge.

He holds a Masters of Technology degree from the National University of Singapore, an Executive MBA degree from U21Global (currently GlobalNxt) and IGNOU, a Graduate Diploma in Mechatronics from A*STAR SIMTech (a national research institute located in Nanyang Technological University), Coursera Specialization Certificate in Business Statistics and Analysis (Excel) from Rice University, IBM Data Science Professional Certificate (Python, SQL), and Coursera Verified Certificate in R Programming from Johns Hopkins University. He possessed a Bachelor of Science degree in Computing from the University of Portsmouth after National Service. He is also an AIIM Certified Business Process Management Master (BPMM), GSTF Certified Big Data Science Analyst (CBDSA), and IES Certified Lecturer.

Specialties: Data Science, Text Mining, Social Network Analysis, Natural Language Processing, Machine Learning, Software Engineering, Mechatronics, Business.

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