Python

  1. Python Programming Basics
  2. Data Structures used
  3. Packages and libraries used
  4. Project Specific Training on Machine Learning

Python Programming Basics

Introduction to Python

  • Installation and working with Python
  • Python as a script and language
  • Datatypes used in Python
  • Understanding variables
  • Working with Operators

Control Statements

  • Simple If
  • Multiple If
  • Nested If
  • While Loop
  • For Loop
  • Nested Loop
  • Break, Ccontinue and Pass

    Functions

  • Defining a function
  • Calling a function
  • Types of functions
  • Function Arguments
  • Writing main()

    OOPS using Python

  • Defining Class and object
  • Defining Attributes and Methods
  • Implementing Inheritance
  • Method Overloading
  • Method Overriding
  • Data Hiding

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Data Structures Used in Python

Handling Strings

  • Declaring and using String constants
  • Accessing Strings
  • Basic String operations
  • String Slicing
  • Formatting String
  • Using methods on string objects
  • Examples and Excercises

Using Lists

  • Introduction to Lists
  • Accessing List
  • Basic operations
  • indexing on list
  • Functions and Methods
  • Examples and Excercises

Dictionaries

  • Concept
  • Using Key:Value pairs
  • Accessing Values in Dictionaries
  • Working with Dictonaries
  • Functions and methods
  • Examples and Excercises

Tuples in Python

  • Concept of Tuples
  • Declaring and populating Tuple
  • Accessing Tuples
  • Operation on Tuples
  • Functions and methods
  • Examples and Exercises

Files

  • What is a File?
  • Opening files of different types
  • Closing a file
  • Writing data to a file
  • Appending Data to a file
  • How to read from a file
  • Reading line by line at a time
  • Python File methods
  • File Modes
  • Examples and exercises
  • Mini project-1
  • Mini project-2
  • Mini project-3

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Packages and Libraries Used

NumPy

  • Introduction to NumPy
  • NumPy arrays
  • Review on Array Indexing
  • NumPy array Indexing
  • NumPy Operations
  • NumPy Matrix operations
  • NumPy Exercies

Pandas for Data Analysis

  • Introduction to Pandas
  • Series
  • Creating and Handling DataFrames
  • Missing Data Handling
  • Using GroupBy
  • Merging, Joining, concatenating
  • Data Input/Output
  • Exercises

MatPlotLib

  • Simple Plot
  • Multiplots
  • Subplots
  • Grids
  • Formatting Axes
  • Setting Tick and Tick Labels
  • Bar chart
  • Histogram
  • Scatter Plot
  • Pie Chart
  • Box Plot
  • Exercisews

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Project Specific Training

Machine Learning

  • Introduction to Machine Learning Concepts
  • Supervised Learning
  • Unsupervised Learning
  • Reinforced Learning
  • Classification
  • Regression
  • Clusturing

Any One for Project Implementation

  • Linear Regression
  • Logistic Regression
  • K Nearest Neighbors
  • Decision Trees and Random Forests
  • Support Vector Machines
  • K Means Clustering
  • Principal Component Analysis

Project Implementation

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