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Key Features

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DataScience with Python and R


Course Objective:

After completion of this course student will get an overview about what is data science today and how they can implement python and R language for data science.


Prerequisite:

Basic knowledge of C or Java and basic python and statistics


Course Content:

Introduction to Python for Data Science
  • Python DataScience
  • Python Pandas
  • Python NumPy
  • Python Scipy
  • Python Matplotlib
Python Data Processing
  • Python Data Operation
  • Data cleansing
  • Processing CSV Data
  • Python relational Database
Python Data Visualization
  • Python chart properties
  • Chart Styling
  • Python Graph Data
  • Python Scatter plot
  • Python 3D charts
Statistical Data Analysis
  • Measuring central tendency
  • Measuring variance
  • Normal , binomial and Poisson distribution
  • Correlation and linear regression
Introduction To R
  • Overview of R language
  • DataType ,variable and operators
  • Decision Making and loops
  • Function
  • Array
  • Factors
  • DataFrame
  • Package
R Data Interface
  • CSV files
  • Excel file
  • Binary files
  • Database
R charts and graphs
  • R-pie charts
  • R- Bar charts
  • Histogram
  • Line graph
  • Scatter diagram
R Statistics
  • Mean , median and mode
  • Regression
  • Normal , Binomial and Poisson distribution
  • Analysis of covariance
  • Time series analysis

Doubt session & Revision

Q & A


Includes

  • Course Duration: 4 – 6 Weeks
  • Suitable For: 2nd/ 3rd / 4th Yr B.Tech. / Diploma students
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