Data Science R Programming Certification - eLearning
450,00 EUR
The Data Science with R Certification course enables you to take your data science skills into a variety of companies, helping them analyze data and make more informed business decisions. The course covers data exploration, data visualization, predictive analytics, and descriptive analytics techniques with the R language. You will learn about R packages, how to import and export data in R, data structures in R, various statistical concepts, cluster analysis, and forecasting.
Course timeline
Introduction to Business Analytics
Lesson 01
- Overview
- Business Decisions and Analytics
- Types of Business Analytics
- Applications of Business Analytics
- Data Science Overview
- Conclusion
- Knowledge Check
Introduction to R Programming
Lesson 02
- Overview
- Importance of R
- Data Types and Variables in R
- Operations in R
- Conditional Statements in R
- Loops in R
- Conclusion
- Knowledge Check
Data Structures
Lesson 03
- Overview
- Identify Data Structures
- Demo: Identify Data Structures
- Assigning Values to Data Structures
- Data Manipulation
- Demo: Assigning Values and Applying Functions
- Conclusion
- Knowledge Check
Data Visualization
Lesson 04
- Overview
- Introduction to Data Visualization
- Data Visualization Using Graphics in R
- Ggplot2
- File Formats of Graphic Outputs R
- Conclusion
- Knowledge Check
Statistics for Data Science-I
Lesson 05
- Overview
- Introduction to Hypothesis
- Types of Hypothesis
- Data Sampling
- Confidence and Significance Levels
- Conclusion
- Knowledge Check
Statistics for Data Science - II
Lesson 06
- 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
Regression Analysis
Lesson 07
- 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
Classification
Lesson 08
- Overview
- Classification and its Types
- Logistic Regression
- Support Vector Machines
- Demo: Naive Bayes Classifier
- Demo: Naive Bayers Classifier
- Decision: Tree Classification
- Demo: Decision Tree Classification
- Random Forest Classification
- Evaluating Classifier Models
- Demo: K-Fold Cross Validation
- Conclusion
- Knowledge Check
Clustering
Lesson 09
- Overview
- Introduction to Clustering
- Clustering Methods
- Demo: K-means Clustering
- Demo: Hierarchical Clustering
- Conclusion
- Knowledge Check
Association
Lesson 10
- Overview
- Association Rule
- Apriori Algorithm
- Demo: Apriori Algorithm
- Conclusion
- Knowledge Check
Learning Outcomes
At the end of this Data Science R Programming eLearning Course, you will be able to:
Gain a foundational understanding of business analytics
Install R, RStudio, workspace setup, and learn about the various R packages
Master R programming and understand how various statements are executed in R Gain an in-depth understanding of data structure used in R and learn to import/export data in R
Define, understand and use the various apply functions and DPLYR functions
Master R programming and understand how various statements are executed in R
Gain an in-depth understanding of data structure used in R and learn to import/export data in R
Define, understand and use the various apply functions and DPLYR functions
Understand and use the various graphics in R for data visualization
Gain a basic understanding of various statistical concepts
Understand and use the hypothesis testing method to drive business decisions
Understand and use linear and non-linear regression models, and classification techniques for data analysis
Learn and use the various association rules the Aprioiri algorithm
Learn and use clustering methods including k-means, DBSCAN, and hierarchical clustering.
Who Should Enroll in this Program?
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 course for the descending categories.
IT professionals
Analytics Professionals
Software Developers
Data scientist
Business Intelligent
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