Python & DataScience

Module 1. Introduction to DataScience with Python

Duration: 30-35 hrs

Python  and Data Science

  • Installing Python Anaconda distribution

  • Python native Data Types

  • Basic programing concepts

  • Python data science packages overview

Module 2. Python Basics: Basic Syntax, Data Structures

  • Python Objects

  • Math &Comparision Operators

  • Conditional Statement

  • Loops

  • Lists, Tuples, Strings, Dictionaries, Sets

  • Functions

  • Exception Handling

Module 3 - Numppy Package

  • Importing Numpy

  • Numpy overview

  • Numpy Array creation and basic operations

  • Numpy Universal functions

  • Selecting and retrieving Data

  • Data Slicing

  • Iterating Numpy Data

  • Shape Manupilation

  • Stacking and Splitting Arrays

  • Copies and Views : no copy, shallow copy , deep copy

  • Indexing : Arrays of Indices, Boolean Arrays

Module 4 - Pandas Package

Module 5 - Python Advanced: Data Mugging with Pandas

  • Python Objects

  • Math &Comparision Operators

  • Conditional Statement

  • Loops

  • Lists, Tuples, Strings, Dictionaries, Sets

  • Functions

  • Exception Handling

  • Applying functions to data

  • Histogramming

  • String Methods

  • Merge Data :Concat, Join and Append

  • Grouping & Aggregation

  • Reshaping

  • Analysing Data for missing values

  • Filling missing values: fill with constant, forward filling, mean

  • Removing Duplicates

  • Transforming Data

Module 6 - Python Advanced: Visualization with MatPlotLib

  • Importing MatPlotLib&Seaborn Libraries

  • Creating basic chart : Line Chart, Bar Charts and Pie Charts

  • Ploting from Pandas object

  • Saving a plot

  • Object Oriented Plotting : Setting axes limits and ticks

  • Multiple Plots

  • Plot Formatting : Custom Lines, Markers, Labels, Annotations, Colors

  • Satistical Plots with Seaborn

  • Importing Numpy

  • Numpy overview

  • Numpy Array creation and basic operations

  • Numpy Universal functions

  • Selecting and retrieving Data

  • Data Slicing

  • Iterating Numpy Data

  • Shape Manupilation

  • Stacking and Splitting Arrays

  • Copies and Views : no copy, shallow copy , deep copy

  • Indexing : Arrays of Indices, Boolean Arrays

  • Python Objects

  • Math &Comparision Operators

  • Conditional Statement

  • Loops

  • Lists, Tuples, Strings, Dictionaries, Sets

  • Functions

  • Exception Handling