Training in BTM is a leading Training as well as Placement company with experience in leading IT Sectors of India. Our training reproduces the latest technologies, techniques, as well as processes that are advanced in practical knowledge collected from years of experience. DataScience with R Training in BTM Layout offers planned training paths intended for the certification skills necessary to work in latest technological environment, while offering a wide-ranging curriculum of application centric courses for customers looking to implement upgraded/new business applications. The purpose of software Professional training is to help students to advance their knowledge overtime while being acknowledged for their achievement.

DataScience with R Training in BTM Layout is an outstanding Online and corporate training center. We provide a number of tailored training programs for small, medium along with big organizations in Bangalore and across India. Our training courses are very cost effective for all clients/students plus students. Our training Syllabus is prepared from the team of experts and the students can improve from basic knowledge to advance level. Our Syllabus includes Introduction to R , Understanding R data structure , Importing data , Manipulating Data , Using functions in R , R Programming , Charts and Plots , Machine Learning Algorithm , Statistics , Leading Topics with real time experience.

Training in BTM Layout is one of the greatest Software training institutes in Bangalore with 100% placement support. It has well defined training modules in addition to training sessions for pupils. At DataScience with R Training in BTM Layout, training is conducted in day time classes on all weekdays as well as weekends to suit the timings for all students and working professionals .DataScience with R Training in BTM Layout helps you acquire a foothold in the growing IT & ITeS industry. 100% Placement Assistance- While a student finishes his/ her course effectively, our dedicated Placement Cell arranges interviews with major companies. This wide hands-on experience in Software training ensures that you captivate the knowledge as well as skills that you can apply at work after your placement. All of our mentors are work specialists with years of experience in well recognized IT sectors. Learning from the work experts is the only method to understand what happens in the actual IT world.

Data Science with R Syllabus

    Module 1: Introduction to Data Science (Duration-1hr)

    • What is Data Science?
    • What is Machine Learning?
    • What is Deep Learning?
    • What is AI?
    • Data Analytics & it’s types

      • Module 2: Introduction to R (Duration-1hr)

      • What is R?
      • Why R?
      • Installing R
      • R environment
      • How to get help in R
      • R Studio Overview

        • Module 3: R Basics (Duration-5hrs)

        • Environment setup
        • Data Types
        • Variables Vectors
        • Lists
        • Matrix
        • Array
        • Factors
        • Data Frames
        • Loops
        • Packages
        • Functions
        • In-Built Data sets

          • Module 4: R Packages (Duration-2hrs)

          • DMwR
          • Dplyr/plyr
          • Caret
          • Lubridate
          • E1071
          • Cluster/fpc
          • Data.table
          • Stats/utils
          • Ggplot/ggplot2
          • Glmnet

            • Module 5: Importing Data (Duration-1hr)

            • Reading CSV files
            • Saving in Python data
            • Loading Python data objects
            • Writing data to csv file

              • Module 6: Manipulating Data (Duration-1hr)

              • Selecting rows/observations
              • Rounding Number
              • Selecting columns/fields
              • Merging data
              • Data aggregation
              • Data munging techniques

                • Module 7: Statistics Basics (Duration-11hrs)

                  Central Tendency

                • Mean
                • Median
                • Mode
                • Skewness
                • Normal Distribution

                  • Probability Basics

                • What does mean by probability?
                • Types of Probability
                • ODDS Ratio?

                  • Standard Deviation

                • Data deviation & distribution
                • Variance

                  • Bias variance Trade off

                • Underfitting
                • Overfitting

                  • Distance metrics

                • Euclidean Distance
                • Manhattan Distance

                  • Outlier analysis

                • What is an Outlier?
                • Inter Quartile Range
                • Box & whisker plot
                • Upper Whisker
                • Lower Whisker
                • Scatter plot
                • Cook’s Distance

                  • Missing Value treatments

                • What is a NA?
                • Central Imputation
                • KNN imputation
                • Dummification

                  • Correlation

                • Pearson correlation
                • Positive & Negative correlation

                  • Module 8: Error Metrics (Duration-3hrs)

                  Classification

                • Confusion Matrix
                • Precision
                • Recall
                • Specificity
                • F1 Score

                  • Regression

                • MSE
                • RMSE
                • MAPE

                  • Module 9: Machine Learning

                    Module 10: Supervised Learning (Duration-6hrs)

                      Linear Regression

                    • Linear Equation
                    • Slope
                    • Intercept
                    • R square value

                      • Logistic regression

                    • ODDS ratio
                    • Probability of success
                    • Probability of failure
                    • ROC curve
                    • Bias Variance Tradeoff

                      • Module 11: Unsupervised Learning (Duration-4hrs)

                      • K-Means
                      • K-Means ++
                      • Hierarchical Clustering

                        • Module 12: Machine Learning using R (Duration-10hrs)

                        • Linear Regression
                        • Logistic Regression
                        • K-Means
                        • K-Means++
                        • Hierarchical Clustering – Agglomerative
                        • CART
                        • 5.0
                        • Random forest
                        • Naïve Bayes

                        Thanks for the best ever Training. I did my Android Course here. Trainer is very good in knowledge. They provides the best ever Support to me.

                        Kaviya