Data Science Certification Training - Simplilearn | IT Training & Certification | Info Trek
Respect Your Dreams
Follow through on your goals with courses

Data Science Certification Training - Simplilearn

R Programming Data Science

Location

Format What’s this?

Ways to train

Classroom
Live, instructor-led training in a standard, professional classroom environment

Virtual
Live, instructor-led training conducted over the internet, with hands-on labs

Online
An online, HTML5, self-paced learning experience available for all courses

On-site
Private training for your entire team, delivered at your location, a training center, or online

Video classroom
High-definition video of our most popular courses, streamed to your laptop or personal device

Learn more about our training formats
Starting From
RM 3866.00
  1. 24 Hours
  1. HRDF SBL Claimable
  2. Certificate of Attendance available
  3. 180 days of access from date of purchase
Get started
  1. 0 Days
  1. All of our private classes are customized to your organization's needs.
  2. Click on the button below to send us your details and you will be contacted shortly.

Already purchased this offering? Log in

Request more information

Inquiry for: Myself    My Company

By providing your contact details, you agree to our Privacy Policy

 

 

 

Thank You

Our learning consultant will get back to you in 1 business day

Data Science Certification Training - Simplilearn

WHAT YOU WILL LEARN

This course forms an ideal package for aspiring data analysts aspiring to build a successful career in analytics/data science. By the end of this training, participants will acquire a 360-degree overview of business analytics and R by mastering concepts like data exploration, data visualization, predictive analytics, etc.

AUDIENCE

There is an increasing demand for skilled data scientists across all industries, making this data science certification course well-suited for participants at all levels of experience. We recommend this Data Science training particularly for the following professionals:

• IT professionals looking for a career switch into data science and analytics

• Software developers looking for a career switch into data science and analytics

• Professionals working in data and business analytics

• Graduates looking to build a career in analytics and data science

• Anyone with a genuine interest in the data science field

• Experienced professionals who would like to harness data science in their fields


METHODOLOGY

This program will be conducted with interactive lectures, PowerPoint presentation, discussion and practical exercise.

COURSE OBJECTIVES

The Data Science Certification with R has been designed to give you in-depth knowledge of the various data analytics techniques that can be performed using R. The data science course is packed with real-life projects and case studies.

• Mastering R language: The data science course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various graphics available in R.

• Mastering advanced statistical concepts: The data science training course also includes various statistical concepts such as linear and logistic regression, cluster analysis and forecasting. You will also learn hypothesis testing.


Expand All

Modules

Module 1: Course Introduction
• Course Introduction
Module 2: Introduction to Business Analytics

• Overview

• Business Decisions and Analytics

• Types of Business Analytics

• Applications of Business Analytics

• Data Science Overview

• Conclusion

• Knowledge Check


Module 3: Introduction to R Programming

• Overview

• Importance of R

• Data Types and Variables in R

• Operators in R

• Conditional Statements in R

• Loops in R

• R script

• Functions in R

• Conclusion

• Knowledge Check


Module 4: Data Structures

• Overview

• Identifying Data Structures

• Demo Identifying Data Structures

• Assigning Values to Data Structures

• Data Manipulation

• Demo Assigning values and applying functions

• Conclusion

• Knowledge Check


Module 5: Data Visualization

• Overview

• Introduction to Data Visualization

• Data Visualization using Graphics in R

• ggplot2

• File Formats of Graphic Outputs

• Conclusion

• Knowledge Check


Module 6: Statistics for Data Science-I

• Overview

• Introduction to Hypothesis

• Types of Hypothesis

• Data Sampling

• Confidence and Significance Levels

• Conclusion

• Knowledge Check


Module 7: Statistics for Data Science-II

• Overview

• Hypothesis Test

• Parametric Test

• Non-Parametric Test

• Hypothesis Tests about Population Means

• Hypothesis Tests about Population Variance

• Hypothesis Tests about Population Proportions

• Conclusion

• Knowledge Check


Module 8: Regression Analysis

• Overview

• Introduction to Regression Analysis

• Types of Regression Analysis Models

• Linear Regression

• Demo Simple Linear Regression

• Non-Linear Regression

• Demo Regression Analysis with Multiple Variables

• Cross Validation

• Non-Linear to Linear Models

• Principal Component Analysis

• Factor Analysis

• Conclusion

• Knowledge Check


Module 9: Classification

• Overview

• Classification and Its Types

• Logistic Regression

• Support Vector Machines

• Demo Support Vector Machines

• K-Nearest Neighbours

• Naive Bayes Classifier

• Demo Naive Bayes Classifier

• Decision Tree Classification

• Demo Decision Tree Classification

• Random Forest Classification

• Evaluating Classifier Models

• Demo K-Fold Cross Validation

• Conclusion

• Knowledge Check


Module 10: Clustering

• Overview

• Introduction to Clustering

• Clustering Methods

• Demo K-means Clustering

• Demo Hierarchical Clustering

• Conclusion

• Knowledge Check


Module 11: Association

• Overview

• Association Rule

• Apriori Algorithm

• Demo Apriori Algorithm

• Conclusion

• Knowledge Check


Course Reviews

No Remarks

0

0 Ratings