- Covariance & Correlation
- Central Limit Theorem
- Z Score
- Normal Distributions
- Hypothesis
Advanced Predictive Modelling in R Certification Training
Learn the most commonly used predictive modelling technique & the core principles behind them in the Advanced ...Read more
Online
₹ 7627 8475
Quick Facts
particular | details | |||
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Medium of instructions
English
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Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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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.
The highlights
- Edureka certificate
- Online self-learning course
- Learning Management System (LMS)
- Taught by subject matter experts
- Community forum
Program offerings
- Certificate by edureka
- Community forum
- Learning management system
- Taught by subject matter experts
- Recorded sessions
Course and certificate fees
Fees information
Advanced Predictive Modelling in R Certification fee structure
Head | Amount in INR |
Original price | Rs. 8,475 |
Discounted price | Rs. 7,627 |
*No Cost EMI starts at Rs. 2,543 / month
certificate availability
Yes
certificate providing authority
Edureka
Who it is for
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
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
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.
Is this programme beneficial for Analytics Managers?
Yes, the course is suitable for Analytics Managers who lead a team of analysts.