Data Science

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Introduction to Data Analysis using R

The R language is widely used among statisticians and data miners for developing statistical software and data analysis. Polls and surveys of data miners are showing R’s popularity has increased substantially in recent years. R allows users to visualize data, run statistical tests, and apply machine learning algorithms.
Learn how to tackle data analysis problems using the powerful open source language R. The course will take you from learning the basics of R to using it to explore many different types of data. You will learn how to prepare data for analysis, compute various statistical measures, create meaningful data visualizations, create reusable R functions, create R models to predict expected future outcomes and more!

Course Content

  • Introduction to R

  • Getting Started – R Console
  • Data types and Structures
  • Exploring and Visualizing Data
  • Programming Structures, Functions and Data Relationship

SQL Fundamentals

Most software written today relies on relational databases such as MySQL or DB2. Within this SQL course, you will learn the basics of the relational database model and the SQL language using DB2 Express-C, the free version of IBM DB2 database server. You will learn SQL and how to create, read, update and delete data from a database. This SQL tutorial is aimed at beginners, but it will give you enough information to get you started working with databases.

Course Content

  • Getting started

  • Relational database concepts

  • Working with database objects

  • Reading data

  • Inserting, updating, and deleting data

  • Working with multiple table

Data Mining with Excel

Complex organizations are relying more and more on electronic spreadsheets for their daily operations. A number of Excel’s features can probably be called advanced features if for no better reason than the ways in which they expand the definitions of what a spreadsheet program can do
Delegates attending this Excel course should understand the basic concepts of creating an Excel Spreadsheet, or have attended both Beginners & Intermediate Excel training course.

Course Content

    1. Introduction
      to Data Mining.

      1. Meaning

      2. Where
        Data Mining find Expressions in the Ordinary Business of Man.

    2. Scope
      of Data Mining.

      1. The
        Data Mining Cycle

      2. Basic
        tools for Data Mining

    1. Preparing
      data for Data Mining

      1. Collection

      2. Data
        Quality

      3. Data
        Sharing

    2. Using
      Microsoft Excel for Data Mining

      1. Power
        Tool in Excel for Data Mining.

      2. Add-ins
        for Data Mining.

      3. The
        Scope of Excel’s Data Mining Potential.

    3. Data
      Mining with:

      1. Pivot
        Tables

      2. Data
        Analysis Add-in

        1. Correlation

        2. Regression

        3. Moving
          Average

        4. Anova
          Single Factor

        5. Anova
          Two Factor

Registration

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