Course Description:-

INTRODUCTION:

Certified Data Science using R Language Training Course:

• In this course on Certified Data Science using R Language, you will learn Data Manipulation & Statistics Basics, Statistics, Probability & Distribution, Business Analytics using R, Testing & Forecasting, Visualizations.
• The course starts from scratch and hence a beginner can also take and enjoy this course on Certified Data Science using R Language.

What are the requirements Certified Data Science using R Language ?

• Basic knowledge of statistical reasoning
• Passion to learn about R- Programming
• Computer with Internet connection

What am I going to get from Certified Data Science using R Language Training?

• To give the learners the introduction to R programming
• Learn important concepts like regression, Distribution etc using the R Software

Certified Data Science using R Language Training target audience?

• People from Analytics domain
• Anyone who wants to learn about Business Analytics Using R

Certified Data Science using R Language Training Objective?

• To give the participants complete knowledge of Data Science using tool like R.

Benefits of online course:

• High Quality Content
• Learn Anywhere Anytime & at Your Pace
• 24X7 Customer Support
• Complete Student Support Throughout The Program
• Course Completion Certificate 
• Lifetime course access

For any query feel free to call

Mob - 8587999769/9818826705

CURRICULUM

CURRICULUM

Section 1: Understanding R

1. Basics of R
2. Basic R Functions
3. Data Types
4. Recycling Rule
5. Special Numerical Values
6. Parallel Summary Functions
7. Logical Conjunctions
8. Pasting Strings together
9. Type Coercion
10. Array & Matrix
11. Factor
12. Repository & Packages
13. Installing a Package
14. Importing Data
15. Importing Data SPSS
16. Working with Data
17. Data Aggregation

Section 2: Data Manipulation & Statistics Basics

1. Data Manipulation & Statistics Basics
2. Merging
3. Data Creation
4. Merge Example
5. What is Statistics
6. Variables
7. Quantiles
8. Calculating Variance
9. Calculating Covariance
10. Cumulative Frequency
11. Library (mass)
12. Head (faithful)
13. Scatter Plot
14. Control Flow

Section 3: Statistics, Probability & Distribution

1. Statistics, Probability & Distribution
2. Random Variable
3. Random Example
4. Discrete Example
5. Practice problem
6. Continuous Case
7. Exponential Distribution Practice Problem
8. Expected Value
9. Gambling Example
10. Deal or no deal
11. Distribution details
12. Binomial Distribution continued
13. Expected Value from Binomial
14. Uniform Random Variables
15. Probability distributions examples
16. Probability distributions examples continued

Section 4: Business Analytics using R

1. Business Analytics using R
2. Normal PDF
3. What is Normal, Not Normal
4. SAT Example
5. Example- Birth Weights
6. dNorm, pNorm, qNorm
7. Understanding Estimation
8. Properties of Good Estimators
9. Central Limit Theorem
10. Kurtosis
11. Constructing Central Limit Theorem
12. Confidence Intervals for the Mean
13. Confidence Intervals Examples
14. Computer Lab Example
15. t-distribution
16. t-distribution continued

Section 5: Examples, Testing & Forecasting

1. R Examples
2. Standard error of the mean
3. Downloading the Package
4. Sample Differences
5. Hypothesis Generation & Testing
6. Hypothesis Testing
7. One sided P Value
8. Power & Sample Size
9. Testing Hypothesis using R
10. Calculating the Z value
11. Lower Tail proportion of population proportion
12. Forecasting
13. Time Series Analysis Applications
14. Approaches to Forecasting
15. Observation Components
16. Traditional Approaches
17. Double Exponentional Smoothing
18. ARIMA Steps
19. Forecasting Performance
20. Univariate ARIMA

Section 6: Understanding Visualizations

1. R Visualization
2. Why Visualize
3. Overlaying Plots
4. Graphs representation of Data
5. Graphs representation of Data continued
6. Advanced Graphs
7. Bubble Charts
8. Anova
9. Concept of effect
10. Estimate of Treatment effect
11. Factorial Anova
12. Regression
13. Regression Model
14. Linear Relationship
15. Output of Regression Model

Here is a sample for the course completion certificate which you will receive after complete the course. This certificate is widely accepted across industries and will boost your chances to grab the job opportunities.

Mail us at: [email protected] with below details to receive your certificate:

• Name
• Course Name
• Date of Completion
• Address