Online Training: Batch starts on Oct 22nd,2018 at 7:30 PM Central Time, For a free demo please contact +1 (469) 287-7949 ::   Hyderabad: Batch Starts on 27 Oct 2018, Call Help Desk +91 90001 55700.::   Hyderabad: Free Seminar by Industry Expert on 27 Oct 2018. Call Help Desk +91 90001 55700.::   Chennai: Batch Starts on 27 Oct 2018, Call Help Desk +91 89393 73021::   Bangalore: Batch Starts on 27 Oct 2018, Call Help Desk +91 9742306227 / 8147766658 ::   Pune: Free Demo on 27 Oct 2018; Call Help Desk +91 77220 37493 ::   Pune: Batch Starts on 27 Oct 2018, Call Help Desk +91 77220 37493.::   Bangalore: Free Seminar by Industry Expert on 27 Oct 2018. Call Help Desk +91 9742306227 / 8147766658::   Mumbai: Batch Starts on 27 Oct 2018, Call Help Desk +91 7414917172.::   Felicitation Ceremony for Alumni on 28 Oct 2018 from 10:00 AM::  

Data Science Training

  • Batch Starts on 18 June 2018, Call Help Desk +91 7997992876
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Are you looking for the best Data Science course in Hyderabad? You are at right place. Your search to learn Data Science ends here at COEPD. Here, we are an established training institute who have trained more than 10,000 participants in all streams. We will help you to convert your passion to learn into an enriched learning process.


R language has been the game changer in Data Analytics industry. It is the most popular analytical software compared to any of its rival commercial Data Analytics products. R has the potential to offer bright job prospects for both fresher and experienced. R Language is ranked at 8th position in TIOBE language rankings. At COEPD, we provide finest Data Science and R-Language training.

       
  • INTRODUCTION TO R
  • Getting Data into R
  • Accessing Variables and Managing Subsets of Data
  • Simple Functions
  • An Introduction to Basic Plotting Tools
  • Loops and Functions
  • Graphing Tools
  • An Introduction to the Lattice Package
  • Probability and distributions with R
  • Simple Regression and correlation
  • Analysis of Variance and the Kruskal-Wallis test
  • Multiple Regression
  • Logistic Regression
  • Rates and Poisson Regression
  • Non-linear curve fitting
  • Common R Mistakes
  • Data Science – R Language Implementation
  • Points and Space
  • Set Theory
  • Vectors
  • Matrices
  • Differential Equations
  • Linear Algebra
  • Multinomial Data
  • Data Pre-Processing
  • Data Transformations
  • Dimensionality Reduction
  • Data Visualization
  • Stationary Processes
  • Frequency distribution
  • Measures of dispersion
  • Skewness
  • Normal Distributions
  • Binomial distribution
  • Probability
  • Conditional Probability
  • Subjective Probability
  • Multiplication law of Probability
  • Mutually exclusive events and independent events
  • Bayes Theorem
  • Random Variables
  • Correlation and Regression
  • Logistic regression
  • Multi nominal Logistic Regression
  • Count Regression
  • Non Parametric Regression
  • Multivariate Analysis
  • Single Factor Studies
  • Multi Factor Studies
  • Specialized Study designs
  • Testing of Hypothesis
  • Sampling
  • Design and Analysis of experiments
  • Anova
  • Linear Regression
  • Non-Linear Regression
  • Design of experiments
  • Multivariate Analysis
  • Canonical correlation
  • Discriminant
  • Factor Analysis
  • Cluster Analysis
  • Multivariate Analysis variance
  • Time series Analysis
  • Forecasting Analysis
  • Quality Control
  • Linear Programming Problem
  • Game Theory
  • Transportation Problem
  • Simulation
  • Decision Analysis
  • Decision Trees
  • Assignment Problems
  • Predictive Analysis
  • Data Mining Concepts
  • Neural Networks
  • WekaDatamining
  • Item Set Mining
  • Sequence Mining
  • Graph Pattern Mining
  • Kernal Methods
  • Classification
  • Likelihood Theory
  • Arbitrage Theory
  • Machine Learning
  • Ensemble learning
  • Estimation
  • Simulation

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