Data Analytics Training Course Content

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Data Analytics Training Course Content Details

What is Data Analytics

Data analysis, additionally called analysis information|of knowledge|of information} or data analytics, may be amethod of inspecting, cleansing, remodeling, and modeling information with the goal of discovering helpful info, suggesting conclusions, and supporting decision-making. information analysis has multiple sides and approaches, encompassing numerous techniques below a spread of names, in numerous business, science, and scientific discipline domains.Data Analytics training in hyderabad kukatpally
Data mining may be a explicit information analysis technique that focuses on modeling and data discovery for prophetic instead of strictly descriptive functions, whereas business intelligence covers information analysis that depends heavily on aggregation, that specialize in business info. In applied mathematics applications information analysis are often divided into descriptive statistics, explorative information analysis (EDA), and substantiative information analysis (CDA). EDA focuses on discovering new options within the information and CDA on confirming or disproof existing hypotheses. prophetic analytics focuses on application of applied mathematics models for prophetic prognostication or classification, whereas text analytics applies applied mathematics, linguistic, and structural techniques to extract and classify info from matter sources, a species of unstructured information. All ar kinds of information analysis.

Data integration may be a precursor to information analysis, and information analysis is closely coupled to information visualisation and information dissemination. The term information analysis is typically used as a word for information modeling. for more info click here.

Data Analytics Course Content


  • Introduction to Business Analytics and Big Data

02. Business Analytics Life Cycle

  • Business Analytics Process, CRISP-DM, introduction to JMP
  • Module

    03.Basic Analytics + Labs

  • Data concepts, review of basic statistics
  • Data exploration & visualization
  • Hypothesis testing, Type 1 & 2 errors
  • T-test, ANOVA, Chi-Square, and correlation

04. Advanced Analytics + Labs

  • Linear Regression Analysis
  • Logistic Regression
  • Decision Tree, Model comparison and evaluation
  • Cluster Analysis
  • Market Basket Analysis

05. Technology & Tools

  • Data Warehousing and OLAP concepts
  • Tools & Technologies for Big Data Ethical Issues, Final Exam Review

Data Analytics Training Demo

Contact Us for Data Analytics Online and Classroom Training

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Updated: May 13, 2017 — 4:25 am

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