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Data Analytics with R

Coursack’s Data Analytics with R Certification Course makes you a professional in statistics analytics the usage of the R programming language. This path permits you to take your Data Analytics skills into a variety of companies. Supporting them to examine statistics and make more knowledgeable decisions.

Data Analytics with R Certification Course 

  • Derives the meaning from custom created charts used to represent complex data. To manipulate this data and make statistical models for predictive analysis

  • Learn to visualize and explore the data by polishing your skills in techniques like Predictive Analytics, Association Rule Mining and much more

  • Learn to use R, not even as a statistical tool but to make your own functions, objects and packages

1 to 1 Instructor led Training

Group Classes

Corporate Training

Student Discount

  • 30 Hours of Training.

  • Class for Individual Students

  • Labs and Assignments

  • Class Recording is provided

  • 30 Hours of Training.

  • Training is provided to group of students

  • Labs and Assignments

  • Class Recording is provided

Looking for corporate training ? Contact us for group discount 

  • 30 Hours of Training.

  • Training is provided to group of students

  • Labs and Assignments

  • Class Recording is provided

₹28,000

$485

₹23,000

$390

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Who is that the targeted audience?

 Business Analysts, Data Analysts and professionals keen to find out more on science and practice of data analysis using R. By this course the  students will get a knowledge on predictive and prescriptive data analytics, specifically with optimization, modeling, and additionally become familiarity with programming syntax. This course, recommended for any professional who uses data to make business decisions in a better way

1. Data Handling and Visualization in R

1
• Introduction and Overview of R Package
2
• Data Cleaning and Management in R
3
• Logic Building in R
4
• Data Visualization in R
5
• Exercise: Data Summarization using Financial Retail Datasets

2. Data Modeling & Statistics Refresher

1
• Data Modeling Techniques Overview
2
• Missing Imputations
3
• Multi-collinearity Check
4
• Hypothesis Testing

3. Linear Regression

1
• Regression
2
• BLUE Property
3
• Residual Analysis
4
• Multiple Regression
5
• Model Building

4. Logistic Regression

1
• Model theory, Model Fit Statistics
2
• Reject Reference, Binning, Classing
3
• Dummy Creation, Dummy Correlation
4
• Model Development (Multicollinearity, WOE, IV, HLT, Gini KS, Rank Ordering, Clustering Check)
5
• Model Validation (Rerun, Scoring)
6
• Final Dashboard

5. Factor Analysis & Clustering

1
• Factor Analysis
2
• Cluster Analysis

6. Time Series / ARIMA Forecasting

1
• Univariate Time Series
2
• ARIMA

7. Text Mining & Analysis

1
• Extract & Process Unstructured Text Data from Social Media Channels
2
• How to Choose Correct Statistical Tools for Text Analysis

8. Introduction to Machine Learning

1
• How does Machine Learning Work?
2
• ML using Random Forest

9. Live Mentoring Session

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Enrolled: 160 students
Duration: 30 hours
Lectures: 28
Level: Beginner

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Data Analytics with R
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₹26,000 ₹23,000