Data Science Training in Kuala Lumpur

SKU: 11767
10 Lesson
|
40 Hours
igmGuru provides the best Data Science training in Kuala Lumpur. Our course content, customized by industry professionals, covers important concepts from fundamentals to advanced topics like Descriptive Statistics (mean, median, and variance) and Programming for Data Science. We have successfully trained over 500 professionals and counting. We also offer flexible learning options including in-person classroom sessions, one-on-one training, and self-paced video lectures. Join us today and become a certified Data Science expert.

Data Science Course in Kuala Lumpur Overview

igmGuru’s Data Science course provides in-depth training in Python, statistics, data science and machine learning, SQL, and data visualization using Data science tools like Pandas, Scikit-learn, and Tableau. Designed for beginners and professionals, it equips learners with practical skills to analyze data and drive insights across diverse industry applications.

Prerequisites

Here are the prerequisites for Data Science training program for professionals of all levels-

  • Basic understanding of mathematics (algebra, statistics, probability)
  • Basic computer knowledge
  • Introductory programming knowledge (preferably Python)
  • Logical thinking and problem-solving skills
  • Curiosity and willingness to learn
  • Familiarity with Excel or spreadsheets (optional)
  • Basic knowledge of SQL or databases (optional)

What Will You Learn

In this program, you will learn Data Science along with the following topics:

  • Introduction to Business Analytics
  • Data Structures
  • Data Visualization
  • Statistics for Data Science-I
  • Statistics for Data Science-II
  • Regression Analysis
  • Classification
  • Clustering
  • Association

Key Features

Data Science Training in Kuala Lumpur Modules

1. Overview
2. Business Decisions and Analytics
3. Types of Business Analytics
4. Applications of Business Analytics
5. Data Science Overview
1. Overview
2. Importance of R
3. Data Types and Variables in R
4. Operators in R
5. Conditional Statements in R
6. Loops in R
7. R script
8. Functions in R
1. Overview
2. Identifying Data Structures
3. Demo: Identifying Data Structures
4. Assigning Values to Data Structures
5. Data Manipulation
6. Demo: Assigning values and applying functions
1. Overview
2. Introduction to Data Visualization
3. Data Visualization using Graphics in R
4. ggplot2
5. File Formats of Graphic Outputs
1. Introduction to Hypothesis
2. Types of Hypothesis
3. Data Sampling
4. Confidence and Significance Levels
1. Overview
2. Hypothesis Test
3. Parametric Test
4. Non-Parametric Test
5. Hypothesis Tests about Population Means
6. Hypothesis Tests about Population Variance
7. Hypothesis Tests about Population Proportions
1. Overview
2. Introduction to Regression Analysis
3. Types of Regression Analysis Models
4. Linear Regression
5. Demo: Simple Linear Regression
6. Non-Linear Regression
7. Demo: Regression Analysis with Multiple Variables
8. Cross Validation
9. Non-Linear to Linear Models
10. Principal Component Analysis
11. Factor Analysis
1. Overview
2. Classification and Its Types
3. Logistic Regression
4. Support Vector Machines
5. Demo: Support Vector Machines
6. K-Nearest Neighbours
7. Naive Bayes Classifier
8. Demo: Naive Bayes Classifier
9. Decision Tree Classification
10. Demo Decision Tree Classification
11. Random Forest Classification
12. Evaluating Classifier Models
13. Demo: K-Fold Cross Validation
1. Overview
2. Introduction to Clustering
3. Clustering Methods
4. Demo: K-means Clustering
5. Demo: Hierarchical Clustering
1. Overview
2. Association Rule
3. Apriori Algorithm
4. Demo: Apriori Algorithm
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Course Fees

Online Class Room Program

US $ 599.00
100% Money Back Guarantee
  • Duration : 40 Hrs
  • Plus Self Paced

Classes Starting From

  • Fast Track Batch 28 May 2026
  • Weekday Batch 01 Jun 2026
  • Weekend Batch 30 May 2026

Corporate Training

Corporate Training
  • Customized Training Delivery Model
  • Flexible Training Schedule Options
  • Industry Experienced Trainers
  • 24x7 Support

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Data Science with R Certification Exam

A Data Science with R certification exam is a test that assesses a candidate's knowledge and skills in using R for data science tasks. The exam typically covers topics such as data wrangling, exploratory data analysis, statistical modeling, machine learning, and data visualization. With igmGuru, you can prepare for and pass the exam effortlessly.

The format of the exam can vary depending on the organization offering the certification. Some exams may be taken online and consist of multiple-choice questions, while others may be taken in-person and consist of a combination of multiple-choice and open-ended questions.

To prepare for a Data Science with R certification exam, it is recommended to have a solid understanding of the R programming language, as well as experience working with data in R. Practicing with sample exam questions, working on data science projects, and reviewing relevant materials such as tutorials and documentation can also help in preparing for the exam.

It's important to note that different certification exams might have different focus and requirements, you should check with the organization offering the certification for more information.

Data Science with R Certification Exam

Data Science Course in Kuala Lumpur FAQ

Data Science and Machine Learning involve analyzing data to extract insights and build predictive models using algorithms and statistical techniques.

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