Advanced Predictive Modelling in R Certification Training by Edureka: Fee, Duration, How to Apply

Quick Facts

particular	details
Medium of instructions English	Mode of learning Self study	Mode of Delivery Video and Text Based

Course overview

The Advanced Predictive Modelling in R certification course has been curated to help you make better business decisions with the help of helpful data insights. It teaches the widely used techniques of predictive modelling as well as its core principles. Business organisations use these techniques throughout functional areas such as finance, human resource management, accounting, operations, and strategic planning.

The Advanced Predictive Modelling in R course curriculum dives into logistic regression models, advanced regression, dimensionality reduction and more. You will also get to learn about the basics of Statistics that include Correlation and Linear Regression Analysis. Moreover, R programming offers a free and open-source environment perfect for learning and deploying predictive modelling solutions.

Since the Advanced Predictive Modelling in R training will take place through online self-paced classes, you will learn through video lectures, PPTs, assignments and projects. Upon successful completion of the programme, you can earn Edureka’s certification to improve your professional prospects.

Course and certificate fees

Fees information

₹ 5,932 ₹8,475

You are allowed to pay the Advanced Predictive Modelling in R course fee upfront or through a monthly EMI plan.

Advanced Predictive Modelling in R Certification fee structure

Course Name	Fees
Program fee	Rs. 8,475
Monthly EMIs	Rs 1,978 / month

certificate availability

Yes

certificate providing authority

Edureka

Who it is for

Business analyst Analytics manager

The Advanced Predictive Modelling in R certification by Edureka is suitable for:

Business Analysts who wish to understand Machine Learning techniques
‘R’ professionals looking to capture and analyze Big Data
Analytics Managers leading a team of analysts
Developers who aspire to be a ‘Data Scientist’

Eligibility criteria

Eligibility Criteria

To pursue the Advanced Predictive Modelling in R Certification, you must have basic knowledge and understanding of the R programming language.

What you will learn

Statistical skills

Edureka’ Advanced Predictive Modelling in R syllabus includes the following concepts:

Regression
Forecasting
Imputation
What is Survival Analysis?
What is Heteroscedasticity?
Learning Neural Networks
Understanding Dimensionality Reduction
The basics of Statistics using R programming
Using Linear Regression to perform model fitting
Understanding simple, multiple, advanced, and Logistic Regression
Understanding Linear Probability Model and Binary Response Variable
Understanding the algorithms associated with Dimensionality Reduction

The syllabus

Basic Statistics in R

Covariance & Correlation
Central Limit Theorem
Z Score
Normal Distributions
Hypothesis

Ordinary Least Square Regression 1

Bivariate Data
Quantifying Association
The Best Line: Least Squares Method
The Regressions
Simple Linear Regression
Deletion Diagnostics and Influential Observations
Regularization

Ordinary Least Square Regression 2

Model fitting using Linear Regression
Performing Over Fitting & Under Fitting
Collinearity
What is Heteroscedasticity?

Logistic Regression

Binary Response Regression Model
Linear regression as Linear Probability Model
Problems with Linear Probability Model
Logistic Function
Logistic Curve
Goodness of fit matrix
All Interactions Logistic Regression
Multinomial Logit
Interpretation
Ordered Categorical Variable

Advanced Regression

Poisson Regression
Model Fit Test
Offset Regression
Poisson Model with Offset
Negative Binomial
Dual Models
Hurdle Models
Zero-Inflated Poisson Models
Variables used in the Analysis
Poisson Regression Parameter Estimates
Zero-Inflated Negative Binomial

Imputation

Missing Values are Common
Types of Missing Values
Why is Missing Data a Problem?
No Treatment Option: Complete Case Method
No Treatment Option: Available Case Method
Problems with Pairwise Deletion
Mean Substitution Method
Imputation
Regression Substitution Method
K-Nearest Neighbour Approach
Maximum Likelihood Estimation
EM Algorithm
Single and Multiple Imputation
Little’s Test for MCAR

Forecasting 1

Need for Forecasting
Types of Forecast
Forecasting Steps
Autocorrelation
Correlogram
Time Series Components
Variations in Time Series
Seasonality
Forecast Error
Mean Error (ME)
MPE and MAPE---Unit free measure
Additive v/s Multiplicative Seasonality
Curve Fitting
Simple Exponential Smoothing (SES)
Decomposition with R
Generating Forecasts
Explicit Modeling
Modeling of Trend
Seasonal Components
Smoothing Methods
ARIMA Model-building

Forecasting 2

Analysis of Log-transformed Data
How to Formulate the Model
Partial Regression Plot
Normal Probability Plot
Tests for Normality
Box-Cox Transformation
Box-Tidwell Transformation
Growth Curves
Logistic Regression: Binary
Neural Network
Network Architectures
Neural Network Mathematics

Dimensionality Reduction

Factor Analysis
Principal Component Analysis
Mechanism of finding PCA
Linear Discriminant Analysis (LDA)
Determining the maximum separable line using LDA
Implement Dimensionality Reduction algorithm in R

Survival Analysis

Time-to-Event Data
Censoring
Survival Analysis
Types of Censoring
Survival Analysis Techniques
PreProcessing
Elastic Net

Admission details

Step 1: Access the Advanced Predictive Modelling in the R certification course webpage.

Step 2: Click on ‘Enrol Now’ and provide your email address and phone number. Click on ‘start learning’ to proceed.

Step 3: Now, you must make the payment through a secure medium and begin the course.

Filling the form

Just enter your email ID and mobile number to sign up for the Advanced Predictive Modelling in R certification. You must pay the course fee through a secure medium.

How it helps

The Advanced Predictive Modelling in R Certification course benefits Analytic managers, Business Analysts, R professionals, etc. You can benefit from the comprehensive course syllabus designed by industry practitioners and the self-paced online learning format that allows you to decide when to study. What’s more, you will be awarded an Advanced Predictive Modelling in R certificate by Edureka if you complete the programme on time.

FAQs

Does the course allow a demo class for the live sessions?

No, you cannot attend a live class without enrolling in the course. But you can access a sample class recording to get an idea.

Is a community forum feature added to the course?

Yes, a community forum is added to facilitate learning through knowledge sharing and peer interaction.

Can absolute beginners enrol in the course?

The Advanced Predictive Modelling in R online course requires a basic understanding of R from the learners.

Does the course allow EMI payments?

Yes, you can pay through a no-cost EMI option for the Advanced Predictive Modelling in R certification.

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