Overview of Python

The Companies using Python

Different Applications where Python is used Windows

Discuss Python Scripts on UNIX/Windows

Values, Types, Variables

Operands and Expressions

Lists, Ranges & Tuples in Python

Conditional Statements

Python Dictionaries and Sets

Loops

Command Line Arguments

Writing to the screen

Hands On/Demo: Creating “Hello World” code

Variables

Demonstrating Conditional Statements

Demonstrating Loops

Skills: Fundamentals of Python programming

Functions

Function Parameters

Global Variables

Variable Scope and Returning Values

Lambda Functions

Object-Oriented Concepts

Standard Libraries

Modules Used in Python

The Import Statements

Slicing with Negative Numbers

Module Search Path

Package Installation Ways

Errors and Exception Handling

Handling Multiple Exceptions

Hands On/Demo: Functions – Syntax, Arguments, Keyword Arguments, Return Values

Lambda – Features, Syntax, Options, compared with the Functions

Sorting – Sequences, Dictionaries, Limitations of Sorting

Errors and Exceptions – Types of Issues, Remediation

Packages and Module – Modules, Import Options, sys Path Skills:

Error and Exception management in Python

Working with functions in Python

Basic Functionalities of a data object

Merging of Data objects

Concatenation of data objects

Types of Joins on data objects

Exploring a Dataset

Analysing a dataset

Hands On/Demo: Pandas Function- Ndim(), axes(), values(), head(), tail(), sum(), std(), iteritems(), iterrows(),itertuples()

GroupBy operations

Aggregation

Concatenation

Merging Using and, or, in Conditions

Joining

Skills: Python in Data Manipulation

Python Revision (numpy, Pandas, scikit learn, matplotlib)

What is Machine Learning?

Machine Learning Use-Cases

Machine Learning Process Flow

Machine Learning Categories

Linear regression

Gradient descent

Hands On/Demo: Linear Regression – Boston Dataset

Skills: Machine Learning concepts

Machine Learning types

Linear Regression Implementation

What are Classification and its use cases?

What is Decision Tree?

Algorithm for Decision Tree Induction

Creating a Perfect Decision Tree

What is Random Forest?

Confusion Matrix

Hands On/Demo: Implementation of Logistic regression

Decision tree

Random forest

Skills: Supervised Learning concepts

Implementing different types of Supervised Learning algorithms

Evaluating model output

Introduction to Dimensionality

Why Dimensionality Reduction

PCA Factor Analysis

Scaling dimensional model

LDA

Hands-On/Demo: PCA

Scaling

Skills: Implementing Dimensionality Reduction Technique

What is Naïve Bayes?

How Naïve Bayes works?

Implementing Naïve Bayes Classifier

What is Support Vector Machine?

Illustrate how Support Vector Machine works?

Hyperparameter Optimization

Grid Search vs Random Search

Implementation of Support Vector Machine for Classification

Hands-On/Demo: Implementation of Naïve Bayes, SVM

Skills: Supervised Learning concepts

Implementing different types of Supervised Learning algorithms

Evaluating model output

What is Clustering & its Use Cases?

What is K-means Clustering?

How does K-means algorithm work?

How to do optimal clustering

What is C-means Clustering?

What is Hierarchical Clustering?

How Hierarchical Clustering works?

Hands-On/Demo: Implementing K-means Clustering

Implementing Hierarchical Clustering

Skills: Unsupervised Learning

Implementation of Clustering – various types

What are Association Rules?

Association Rule Parameters

Calculating Association Rule Parameters

Recommendation Engines

How does Recommendation Engines work?

Collaborative Filtering

Content-Based Filtering

Hands-On/Demo: Apriori Algorithm

Market Basket Analysis

Skills: Data Mining using python

Recommender Systems using python