Data Science with Python Certification Training Course

Course Content

Introduction

 Overview

 The Companies using Python

 Different Applications where it is used

 Discuss Python Scripts on UNIX/Windows

 Values, Types, Variables

 Operands and Expressions

 Conditional Statements

 Loops

 Command Line Arguments

 Writing to the screen

 Hands On

Sequences and File Operations

 Python files I/O Functions

 Numbers

 Strings and related operations

 Tuples and related operations

 Lists and related operations

 Dictionaries and related operations

 Sets and related operations

 Hands On

Deep Dive – Functions, OOPs, Modules, Errors and Exceptions

 Functions

 Function Parameters

 Global Variables

 Variable Scope and Returning Values

 Lambda Functions

 Object-Oriented Concepts

 Standard Libraries

 Modules Used in Python

 The Import Statements

 Module Search Path

 Package Installation Ways

 Errors and Exception Handling

 Handling Multiple Exceptions

 Hands On

Introduction to NumPy, Pandas and Matplotlib

 NumPy – arrays

 Operations on arrays

 Indexing slicing and iterating

 Reading and writing arrays on files

 Pandas – data structures & index operations

 Reading and Writing data from Excel/CSV formats into Pandas

 matplotlib library

 Grids, axes, plots

 Markers, colours, fonts and styling

 Types of plots – bar graphs, pie charts, histograms

 Contour plots

 Hands On

Data Manipulation

 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

Introduction to Machine Learning with 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

Supervised Learning - I

 What are Classification and its use cases?

 What is Decision Tree?

 Algorithm for Decision Tree Induction

 Creating a Perfect Decision Tree

 Confusion Matrix

 What is Random Forest?

 Hands On

Dimensionality Reduction

 Introduction to Dimensionality

 Why Dimensionality Reduction

 PCA

 Factor Analysis

 Scaling dimensional model

 LDA

 Hands-On

Supervised Learning - II

 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

Unsupervised Learning

 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

Association Rules Mining and Recommendation Systems

 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

Reinforcement Learning

 What is Reinforcement Learning

 Why Reinforcement Learning

 Elements of Reinforcement Learning

 Exploration vs Exploitation dilemma

 Epsilon Greedy Algorithm

 Markov Decision Process (MDP)

 Q values and V values

 Q – Learning

 α values

 Hands-On

Time Series Analysis

 What is Time Series Analysis?

 What is Time Series Analysis?

 Components of TSA

 White Noise

 AR model

 MA model

 ARMA model

 ARIMA model

 Stationarity

 ACF & PACF

 Hands on

Model Selection and Boosting

 What is Model Selection?

 The need for Model Selection

 Cross-Validation

 What is Boosting?

 How Boosting Algorithms work?

 Types of Boosting Algorithms

 Adaptive Boosting

 Hands on