📘 AM602PC

Data Analytics

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DA Unit 1: Data Management

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DA Unit 2: Data Analytics

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DA Unit 3: Regression and Logistic Regression

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Syllabus Overview

UNIT - 1: Data Management

Data Management

  • Design Data Architecture and manage the data for analysis
  • Understand various sources of Data like Sensors/Signals/GPS etc.
  • Data Quality (noise, outliers, missing values, duplicate data)
  • Data Processing & Processing

UNIT - 2: Data Analytics

Introduction to Analytics

  • Introduction to Tools and Environment
  • Application of Modeling in Business
  • Databases & Types of Data and Variables
  • Data Modeling Techniques
  • Missing Imputations
  • Need for Business Modeling

UNIT - 3: Regression and Logistic Regression

Regression

  • Concepts
  • Blue property assumptions
  • Least Square Estimation
  • Variable Rationalization
  • Model Building

Logistic Regression

  • Model Theory
  • Model fit Statistics
  • Model Construction
  • Analytics applications to various Business Domains

UNIT - 4: Object Segmentation and Time Series Methods

Object Segmentation

  • Regression Vs Segmentation – Supervised and Unsupervised Learning
  • Tree Building – Regression, Classification
  • Overfitting, Pruning and Complexity
  • Multiple Decision Trees

Time Series Methods

  • Arima
  • Measures of Forecast Accuracy
  • STL approach
  • Extract features from generated model as Height, Average Energy etc.
  • Analyze for prediction

UNIT - 5: Data Visualization

Data Visualization

  • Pixel-Oriented Visualization Techniques
  • Geometric Projection Visualization Techniques
  • Icon-Based Visualization Techniques
  • Hierarchical Visualization Techniques
  • Visualizing Complex Data and Relations
Data Analytics Notes