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Data analytics


Data analytics is the science of analyzing the data,generating insights, and making predictions.It easily finds applications in social media analysis,computational biology,climate modeling, health care, traffic monitoring and so on.This class aims to provide an overview of advanced machine learning, data mining and statistic techniques that arise in real data analytic applications. Selected topics include topic modeling, structure learning, time-series analysis, learning with less supervision, and massive-scale data analytics.One or more applications associated with each technique will also be discussed.

Course description

Data Analytics

Overview

Data Life Cycle

Data Analytics

Methodology

Core Deliverables

Key Stakeholders

Data Analyst

Data Scientist

Data Collection

Cleansing Data

Summarizing Data

Data Exploration

Data Visualization

Introduction to R

Introduction to SQL

Charts and Graphs

Data Analysis Tools

Statistical Methods

Machine Learning for Data Analysis

Naive Byes Classifier

K-Mean Clustring

Association Rules

Decision Rules

Logistic Regression

Time Series Analytics

Text Analytics

Data Analytics Certification


Course Completion Certificate will be given on the completion of Real-time Project work and the minimum scoring is at least 60%.

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