Data Science classroom Training in hyderabad

1. DATASCIENCE CLASSROOM TRAINING IN HYDERABAD DATASCIENCE CLASSROM TRAINING Information SCIENCE INTRODUCTION AND TOOLBOX : Beginning WITH GITHUB Prologue to Git Prologue to Github Making a Github Repository Fundamental Git Commands Fundamental Markdown Beginning WITH R Review of R R information sorts and Objects Getting Data In and Out of R Subsetting R Objects Dates and Times Beginning WITH R Control structures Capacities Perusing guidelines of R Coding Standards for R Dates and times Beginning WITH R Circle Functions Vectorizing a Function Troubleshooting Profiling R Code Recreation Information EXTRACTION, PREPARATION AND MANIPULATION ( R, MYSQL, HDFS, HIVE AND SQOOP) Information EXTRACTION Downloading Files Perusing Local Files Perusing Excel Files Perusing JSON Perusing XML Perusing From WEB Perusing From API Information EXTRACTION Perusing FROM HDFS Perusing FROM MYSQL SQOOP Perusing FROM HIVE Sparing AND TRANSPORTING OBJECT Perusing COMPLEX STRUCTURE Information PREPARATION Subsetting and Sorting Outlining Data Making New Variable Normal Expression Working With Dates Information MANIPULATION Overseeing DataFrame with dplyr bundle Reshaping Data Combining Data Expressive STATISTICS Univariate Data and Bivariate Data Clear cut and Numerical Data Recurrence Histogram and Bar Charts Condensing Statistical Data Box Plot, Scatter Plot, Bar Plot, Pie Chart Likelihood Contingent Probability Bayes Rule Likelihood Distribution Relationship versus Causation Normal Fluctuation Exceptions Measurable Distribution Binomial Distribution Focal Limit Theorem Typical Distribution 68-95-99.7 % Rule Connection Between Binomial and Normal Distribution Speculation TESTING Speculation Testing Contextual investigations INFERENTIAL STATISTICS Testing of Hypothesis Level of Significance Correlation Between Sample Mean and Population Mean z-Test t-Test ANOVA (F-TEST) ANCOVA MANOVA MANCOVA Relapse AND CORRELATION Relapse Relationship CHI-SQUARE Foremost OF ANALYTIC GRAPH Prologue TO GGVIS Exploratory and Explainatory Plan Principle Load ggvis and begin to investigate Plotting System in R ggvis - illustrations sentence structure LINES AND SYNTAX Properties for Lines Properties for Points Show Model Fits Changes ggvis and dplyr HTMLWIDGET Geo-Spatial Map Time Series Chart System Node Prescient MODELS AND MACHINE LEARNING ALGORITHM - SUPERVISED REGRESSION Relapse ANALYSIS Straight Regression Non-Linear Regression Polynomial Regression Curvilinear Regression Various LINEAR REGRESSION Gather Data Investigate and Prepare the information Prepare a model on the information Assess Model Performance Enhance Model Performance Strategic REGRESSION Gather Data Investigate and Prepare the information Prepare a model on the information Assess Model Performance Enhance Model Performance TIME SERIES FORECAST Gather Data Investigate and Prepare the information Prepare a model on the information Assess Model Performance Enhance Model Performance Prescient MODELS AND MACHINE LEARNING ALGORITHM - SUPERVISED CLASSIFICATION Gullible BAYES Gather Data Investigate and Prepare the information Prepare a model on the information Assess Model Performance Enhance Model Performance Bolster VECTOR MACHINE Gather Data Investigate and Prepare the information Prepare a model on the information Assess Model Performance Enhance Model Performance Irregular FOREST Gather Data Investigate and Prepare the information Prepare a model on the information Assess Model Performance Enhance Model Performance K-NEAREST NEIGHBORS Gather Data Investigate and Prepare the information Prepare a model on the information Assess Model Performance Enhance Model Performance Characterization AND REGRESSION TREE (CART) Gather Data Investigate and Prepare the information Prepare a model on the information Assess Model Performance Enhance Model Performance Prescient MODELS AND MACHINE LEARNING ALGORITHM - UNSUPERVISED K MEAN CLUSTER Gather Data Investigate and Prepare the information Prepare a model on the information Assess Model Performance Enhance Model Performance APRIORI ALGORITHM Gather Data Investigate and Prepare the information Prepare a model on the information Assess Model Performance Enhance Model Performance Contextual analysis : CUSTOMER ANALYTIC - CUSTOMER LIFETIME VALUE Gather Data Investigate and Prepare the information Prepare a model on the information Assess Model Performance Enhance Model Performance Content MINING, NATURAL LANGUAGE PROCESSING AND SOCIAL NETWORK ANALYSIS Characteristic LANGUAGE PROCESSING Gather Data Investigate and Prepare the information Prepare a model on the information Assess Model Performance Enhance Model Performance Informal organization ANALYSIS Gather Data Investigate and Prepare the information Prepare a model on the information Assess Model Performance Enhance Model Performance CAPSTONE PROJECT Sparing R Script Planning R Script