Python For Data Analytics
Vitti offers certified project based training program in advanced Python for Data Analytics

This Python Programming Course covers both concepts and project of Python like Data Structures & Types, writing python scripts, sequence and file operations, Graphs & Plots, Data Wrangling, Statistical Computation etc. This course will also offer practical exposure to some of the important and widely used Python Programs like Pandas, Numpy, Matplotlib, Anaconda, Scipy etc.
Especially developed in collaboration with academia & AI Industry experts to reskill and retool working professionals towards Artificial Intelligence space.This program offers the benefits of Experienced Faculty Led Sessions: Live-Interactive Online classes and Project based Learning. Program content & structure designed in collaboration with Industry experts.

Duration: 30 Hours Session: 2 hours/day - 2 days a week (weekend) Batch Size: 50 Students

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Python is a very powerful open-source language that has powerful libraries for data manipulation and analysis. For a longtime, Python has been used in scientific computing and highly quantitative domains such as Healthcare, Transportation, Retail & Finance. As of today, it is the most preferred language for Artificial Intelligence, Robotics and Web Development.

Syllabus Structure

What you will learn from this course


Module 1 : Introduction to Python Programming
  • Installation of Python
  • Interactive Shell
  • User Interface or IDE , Pycharm, Eclipse, Visual Studio
  • Program structure in Python
  • Execution steps
  • Executable or script files.
Module 2 : Introduction to Packages
  • Installation of packages
  • Using Anaconda, Numpy Pandas
  • Scipy, Matplotlib
Module 3 : Data Structure and Types in different Packages
  • Array
  • Lists
  • Tuples
  • Strings
  • Variables
  • Arithmetic and Logical operations
  • Date and Time
Module 4 : Statements and controls in Python
  • Assignments, Expressions and prints
  • If tests and conditional logic
  • While and For Loops
  • Iterations and Comprehensions
Module 5 : Processing Texts
  • Texts and Strings
  • Converting Strings to numbers
  • Converting numbers to strings
  • Concatenation of strings

Module 6 : Graphs and Plots
  • Matplotlib package
  • Interactive graphs and Image files
  • Plotting graphs
  • Lines and Markers
  • Colors
  • Plotting several graphs in one figure
  • Controlling the graph
  • Histogram and different graphs
Module 7 : File Operations
  • Opening a file
  • Closing a file
  • searching inside text file
  • Working with csv files
  • Working with Binary files
Module 8 : Data Wrangling
  • Filtering out missing data.
  • Filling in missing data
  • Finding outliers.
  • Re-shaping and Pivoting
  • Removing duplicates.
  • Replacing values.
  • Web Scraping
Module 9 : Statistical Computation
  • Correlation & Co-variance.
  • Polynomials & Liner regression.
  • Statistical tests
Module 10 : Database Connection
  • Files versus Database
  • Visual Studio and SQl
  • SQL queries in Python projects

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