Data Analytics Online Training

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Data Analytics Online Training


 (4.9) | 350 Ratings


Introduction


Data Analytics Online Training Details
Track Regular Track Weekend Track Fast Track
Course Duration 35 Hrs 8 Weekends 5 Days
Hours 1hr/day 2 Hours a day 6 Hours a day
Training Mode Online Classroom Online Classroom Online Classroom
Delivery Instructor Led-Live Instructor Led-Live Instructor Led-Live


Course Curriculum

Data Analytics Introduction

Analytics

  • Introduction to Analytics
  • Market & Use cases
  • Analytics Tools

Data Processing

  • Introduction to Data & Data Types
  • Analytics Methodology
  • Case Study

Statistical Tools I

  • Role of Statistics & Mathematics
  • Descriptive Statistics
  • Concepts of Sample, Population, Probability
  • Probability Distributions

Statistical Tools II

  • Data Visualization
  • Correlation Analysis
  • Regression Analysis

Introduction to 'R'

  • What is "R"& importance of R
  • R installation, Basic Function in R
  • Loading Data File, Saving
  • Descriptive statistics using R

Data Treatment

  • Data Visualization
  • Data Cleaning
  • Data Transformation

Exploratory Data Analysis

  • Correlation & Regression Analysis
  • Multicollinearity
  • Introduction to Factory Analysis
  • Principal Component Analysis

Cluster Analysis

  • Supervised & unsupervised Techniques
  • Hierarchical Clustering
  • K-Means Clustering
  • Case study uisng R

Association rules

  • Introduction
  • Apriori algorithm
  • Case study using R

Predictive Modeling

  • Linear Regresion
  • Logistic Regression
  • Case study using R

Classification Modeling

  • Introduction to Classification
  • Decision Trees
  • Decision Tree Modeling
  • Case study using R

Assessment

  • Modeling Development using "R"

Exam & Certification

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Course Curriculum

Data Analytics Introduction

Analytics

  • Introduction to Analytics
  • Market & Use cases
  • Analytics Tools

Data Processing

  • Introduction to Data & Data Types
  • Analytics Methodology
  • Case Study

Statistical Tools I

  • Role of Statistics & Mathematics
  • Descriptive Statistics
  • Concepts of Sample, Population, Probability
  • Probability Distributions

Statistical Tools II

  • Data Visualization
  • Correlation Analysis
  • Regression Analysis

Introduction to 'R'

  • What is "R"& importance of R
  • R installation, Basic Function in R
  • Loading Data File, Saving
  • Descriptive statistics using R

Data Treatment

  • Data Visualization
  • Data Cleaning
  • Data Transformation

Exploratory Data Analysis

  • Correlation & Regression Analysis
  • Multicollinearity
  • Introduction to Factory Analysis
  • Principal Component Analysis

Cluster Analysis

  • Supervised & unsupervised Techniques
  • Hierarchical Clustering
  • K-Means Clustering
  • Case study uisng R

Association rules

  • Introduction
  • Apriori algorithm
  • Case study using R

Predictive Modeling

  • Linear Regresion
  • Logistic Regression
  • Case study using R

Classification Modeling

  • Introduction to Classification
  • Decision Trees
  • Decision Tree Modeling
  • Case study using R

Assessment

  • Modeling Development using "R"

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