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R Analytics Programming Training Institutes in Bangalore

Best R Analytics Programming Training in Bangalore

R Analytics Programming Training in Marathahalli & Best R Analytics Programming Training Institutes in Bangalore

Best R Analytics Programming training institute Ecare technologies in Marathahalli, Bangalore, provides real-time and placement oriented R Analytics Programming training in Bangalore. Ecare technologies provide the Best R Analytics Programming training courses in Bangalore. Ecare R Analytics Programming training course content is designed from basics to advanced levels. We have a team of R Analytics Programming experts who are working professionals with hands-on real-time R Analytics Programming projects knowledge, which will give students an edge over other Training Institutes. R Analytics Programming training course content is designed to get the placement in major MNC companies in Bangalore as soon as you complete the R Analytics Programming training course.

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R Analytics Programming Training Syllabus in Bangalore

CHAPTER 1: What is Data Analytics

1.            R tools and their uses in Business Analytics

2.            Objectives

3.            Analytics

4.            Where is analytics applied?

5.            Responsibilities of a data scientist

6.            Problem definition

7.            Summarizing data

8.            Data collection

CHAPTER 2: About R

1.            Difference between R and other analytical languages

2.            Different data types in R

3.            Built in functions of R: seq(), cbind (), rbind(), merge()

4.            Subsetting methods

5.            Use of functions like str(), class(), length(), nrow(), ncol(),head(), tail()

CHAPTER 3: Data manipulation in R

1.            Steps involved in data cleaning

2.            Problems and solutions for Data cleaning

3.            Data inspection

4.            Use of functions grepl(), grep(), sub()

5.            Use of apply() function

6.            Coerce the data

CHAPTER 4: Data Import techniques

1.            How R handles data in a variety of formats

2.            Importing data from csv files, spreadsheets and text files

3.            Import data from other statistical formats like sas7bdat and sps

4.            Packages installation used for database import

5.            Connect to RDBMS from R using ODBC and basic SQL queries in R

6.            Basics of Web Scraping

CHAPTER 5: Exploratory Data analysis

1.            Understanding the Exploratory Data Analysis(EDA)

2.            Implementation of EDA on various datasets

3.            Boxplots

4.            Understanding the cor() in R

5.            EDA functions like summarize()

6.            llist()

7.            Multiple packages in R for data analysis

8.            Segment plot HC plot in R

CHAPTER 6: Data Visualization in R

1.            Understanding on Data Visualization

2.            Graphical functions present in R

3.            Plot various graphs like tableplot

4.            Histogram

5.            Box Plot

6.            Customizing Graphical Parameters to improvise the plots

7.            Understanding GUIs like Deducer and R Commander

8.            Introduction to Spatial Analysis

CHAPTER 7: Data Mining: Clustering Techniques

1.            Introduction to Data Mining

2.            Understanding Machine Learning

3.            Supervised and Unsupervised Machine Learning Algorithms

4.            K-means Clustering

CHAPTER 8: Data Mining: Association Rule Mining and Sentiment Analysis

1.            Association Rule Mining

2.            Sentiment Analysis

CHAPTER 9: Linear and Logistic Regression

1.            Linear Regression

2.            Logistic Regression

3.            CHAPTER 10: Anova

4.            Anova

5.            CHAPTER 11: Predictive Analysis

6.            Predictive Analysis

CHAPTER 12: More on Data Mining

1.            Decision Trees

2.            Algorithm for creating Decision Trees

3.            Greedy Approach: Entropy and Information Gain

4.            Creating a Perfect Decision Tree

5.            Classification Rules for Decision Trees

6.            Concepts of Random Forest

7.            Working of Random Forest

8.            Features of Random Forest

 


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R Analytics Programming Training trainer Profile & Placement

  • More than 10 Years of experience in R Analytics Programming Training
  • Has worked on multiple realtime R Analytics Programming Training
  • Working in a top MNC company in Bangalore
  • Trained 2000+ Students so far in R Analytics Programming Training.
  • Strong Theoretical & Practical Knowledge
  • Certified Professionals


R Analytics Programming Training Placement in Bangalore

  • More than 2000+ students Trained in R Analytics Programming Training
  • 92% percent Placement Record
  • 1000+ Interviews Organized

R Analytics Programming Training batch size in Bangalore


Regular Batch ( Morning, Day time & Evening)

  • Seats Available : 8 (maximum)

R Analytics Programming Training Weekend Training Batch( Saturday, Sunday & Holidays)

  • Seats Available : 8 (maximum)

R Analytics Programming Training Fast Track batch

  • Seats Available : 5 (maximum)

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R Analytics Programming Training in Bangalore - Marathahalli
Ecare Technologies

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