Data Science

Duration: 75 Hours

Price: ₹ 49,999.00

Launch Offer: ₹ 44,999.00

Category:

Description

Data Science Training specifically helps the developers to become an expert in Data Analysis Process through which they can have a better understanding on processing the data on large scale. Large number of tools and programming languages are being used for performing the Data Analysis. This training will primarily focus on using R, Tableau and Python Language as they are most recommended by many leading organization. Following courses are included in Data Science Training:

  • Data Science with R
  • Tableau Associate
  • Python
  • Project

Data Science with R

  • Basic Overview of R
    • Understanding the Prerequisites of R
    • Running the Code
    • Advantages of R using varied platforms
  • Introduction to Data Visualisation using R
    • Understanding Aesthetic Mappings
    • Working with Facets
    • Introduction to Geometric Objects
    • Using Statistical Transformation
    • Dealing with Adjustments of Positions
    • Working with Coordinated Systems
  • Basics of Workflow in R
  • Data Transformation
    • Basic Understanding of Transformation
    • Using filter() for Filtering Row
    • Using arrange() for Arranging Rows
    • Using select() for selecting Rows
    • Using mutate() for adding new variables
    • Working with summarise() for grouping summaries
  • Basic Understanding of Scripts for Workflow in R
  • Performing Data Analysis on higher level
  • Basic Introduction to Tibbles
    • Understanding the process of creating Tibbles
    • Difference between Tibbles and data.frame
    • Interaction with older code
  • Performing Data Import
    • Basic Overview of Data Import
    • Process of Parsing a Vector
    • Process of Parsing a File
    • How to write to a file
    • Dealing with other types of data
  • Tidy Data
    • Introduction to the term “Tidy Data”
    • Working with Spreading and Gathering
    • Working with Separating and Uniting
    • Using Missing Values
  • Basic overview of Relational Data
    • Dealing with nycflights13
    • What are keys
    • Working with Mutating joins
    • Working with Filtering Joins
    • Dealing with Join Problems
    • Set Operations
  • Working with Strings and Factors in R
  • Dealing with Dates and Times
  • Working with Model in R
    • Process of Building a Model
    • Process of Deploying a Model

Tableau Associate

  • Getting start with Tableau
  • Visual analysis and dashboard creation
    • Basics of building visualizations
    • Visulizing Data
    • Creating Dashboard
  • Data connection
    • File
    • Server
    • Cloud
    • Extract connections
    • Metadata & Data source connections
    • Data Filtering
  • Advance data visualization
    • Charts
    • Date and time visualization
    • Chart and plotting
  • Calculation for data enhancement
    • Multi-level calculation
    • Basics of Parameters
    • Overview on Ad hoc calculation
  • Dashboard with Data story
    • Objectives
    • Story Points
    • Examples
  • Understanding on Tableau server
  • Tableau server Installation
  • Cmd line tool for server automation

Python

  • Basic Overview of Data Science
  • Introduction to Data Analytics
    • Understanding the complete process of Data Analytics
    • Working with Exploratory Data Analysis (EDA)
  • Introduction to Python
    • Environment Setup for Python
    • Installation of Python
    • Working with various Data Types of Python
    • Using different operators and functions in Python
  • Performing Mathematical Computation using NumPy
    • Basic overview of NumPy
    • Working with Class and attributes of ndarray
    • Dealing with Mathematical functions of NumPy
  • Basic Introduction to Scientific Computing with Python (SciPy)
    • Basic Overview of SciPy
    • Understanding various SciPy SubPackages
  • Data Manipulation with Pandas
    • Basic Introduction to Pandas>
    • Understanding the process of DataFrame
    • Viewing and selecting Data Demo
    • Working with missing values
    • Dealing with various Data Operations
    • Working with File Read and Write Support
    • Using Pandas SQL Operation
  • Machine Learning with Scikit-Learn
  • Natural Language Processing with Scikit-learn
  • Data Visualisation using matplotlib

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