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Data researcher needs to pre-process the large data before they visualize the data and/or find the data patterns, based on data patterns they perform data predictions. Using Java, Python and R programming language, Analyst can write custom user define functions and perform ETL Jobs. Programming skill help students to automate the data cleansing, processing and transformation logic.

Course Content
  • Java - Programming

    • Introduction to Programming

    • Variable, Data Types

    • Complex Data Types

    • Conditional Statement (IF, Switch)

    • Loops (For, While, Do While)

    • Array

    • File I/O

    • Java Util

    • UML [Unified Modeling Language]

    • OOP Concepts [Object Oriented Programming]

    • JDBC [Java Database Connection]

    • Exceptions

    • Thread

  • R - Programming

    • R for Data Analysis will introduce you to data manipulation in R programming. You will learn about analysis, manipulating data and grouping it to prepare the data. You will also learn how to take data you prepared and present it on visualizations.

    •  Vector creation

    • Data types and Structures

    • Data Statistics

    • Data Frame

    • Programming Structures, Functions, and Data Relationships

    • R Functions

    • Linear Programming

    • Data Analysis

    • Exploring and Visualizing Data

  • Python - Programming

    • Python is a general-purpose programming language that is becoming more and more popular for doing data science. Companies worldwide are using Python to harvest insights from their data and get a competitive edge. Unlike any other Python tutorial, this course focuses on Python specifically for data science.

    • Data Types

    • Variables

    • String operations

    • Control Statements

    • Loops

    • Functions

    • File operations

    • NumPy functions

    • SciPy functions

    • Pandas functions

    • Graphics functions

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