Data Science Training Course

  Part 1: Python Programming
Lecture-1 Introduction of Python 
·      The Companies using Python

·      Different Applications where Python is used

·      Discuss Python Scripts on UNIX/Windows

·      Values, Types, Variables

·      Operands and Expressions

·      Conditional Statements

·      Loops

·      Command Line Arguments

·      Writing to the screen

·      Practical Exercise              

Lecture-2 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

·      Practical Exercise              

Lecture-3 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

·      Practical Exercise

  Part 2: Python for Data Science
Lecture-4 Introduction to Data Science for Python 
·      What is Data Science?

·      History of Data Science

·      Methodologies

·      Data Science Applications

·      Image Recognition

·      Speech Recognition

·      Business Intelligence vs. Data Science

·      Data Science Life-Cycle

·      Practical Exercise              

Lecture-5 Python Data Science Environment Setup 
·      Install Python

·      Getting Anaconda for Data Science Environment Setup

·      Anaconda Navigator

·      Installing Anaconda

·      Install Miniconda

·      Setting up a Virtual Environment

·      Important Python Data Science Packages

·      How to Get Jupyter Notebook?

·      Practical Exercise              

Lecture-6 Python Data Cleansing by Pandas & Numpy 
·      Python Data Cleansing – Prerequisites

·      Python Data Cleansing Operations on Data using NumPy

·      Python Data Cleansing Operations on Data Using pandas

·      Dataframe

·      Panel

·      Series

·      Python Data Cleansing

·      Ways to Cleanse Missing Data in Python

·      Python Data Cleansing – Other Operations

·      Practical Exercise              

Lecture-7 Python Data File Formats 
·      How to Read CSV, JSON, and XLS Files

·      Python Data File Formats

·      Prerequisites

·      Read CSV File in Python

·      Read JSON File in Python

·      Practical Exercise             

Lecture-8 Working with Relational Database with Python 
·      Introduction

·      Prerequisites for Relational Database

·      Reading a Relational Table

·      Insert Values in Relational Database with Python

·      Delete Values in Relational Database with Python

·      Practical Exercise             

Lecture-9 Work with NoSQL Database in Python using PyMongo 
·      What is NoSQL Database?

·      Need for NoSQL Database in Python

·      Database Types with NoSQL

·      Document Databases

·      Graph Stores

·      Key-Value Stores

·      Wide-Column Stores

·      Benefits of Using NoSQL Database

·      NoSQL vs. SQL

·      Installing the Prerequisites of NoSQL Database in Python

·      Operations Perform in NoSQL Database in Python

·      Practical Exercise             

Lecture-10 Python Stemming and Lemmatization 
·      Prerequisites for Python Stemming and Lemmatization

·      Python Stemming

·      Python Lemmatization

·      Practical Exercise              

Lecture-11 Aggregation and Data Wrangling with Python 
·      DataFrames

·      Python Data Wrangling – Prerequisites

·      Why we need Data Wrangling with Python

·      Dropping Missing Values

·      Grouping Data

·      Filtering Data

·      Pivoting Dataset

·      Melting Shifted Datasets

·      Merging Melted Data

·      Reducing into an ABT

·      Concatenating Data

·      Exporting Data

·      How Python Aggregate Data?

·      Practical Exercise              

Lecture-12 Python Statistics 
·      Introduction

·      p-value in Python Statistics

·      T-test in Python Statistics

·      KS Test in Python Statistics

·      Correlation in Python Statistics

·      Practical Exercise              

Lecture-13 Python Descriptive Statistics 
·      Data Analysis

·      Descriptive Statistics in Python

·      Central Tendency in Python

·      Dispersion in Python

·      Pandas with Descriptive Statistics in Python

·      Practical Exercise              

Lecture-14 Python Probability Distributions 
·      What is Python Probability Distribution?

·      Implement Python Probability Distributions

·      Normal Distribution in Python

·      Binomial Distribution in Python

·      Poisson Distribution in Python

·      Bernoulli Distribution in Python

·      Practical Exercise              

Lecture-15 Introduction to Python Anaconda 
·      What is Anaconda?

·      Benefits of Using Python Anaconda

·      Python Anaconda Installation

·      Installing Python Anaconda Libraries

·      Anaconda Navigator

·      Practical Exercise              

Lecture-16 Python Matplotlib 
·      What is Python Matplotlib?

·      Python Matplotlib – Pyplot

·      Python Matplotlib Keyword Strings

·      Categorical Variables to Python Plotting

·      Some Line Properties of Matplotlib

·      Showing a Grid in Python Plot

·      Practical Exercise              

Lecture-17 Python Scatter Plot & Python BoxPlot 
·      What is Python Scatter & BoxPlot?

·      Create Python BoxPlot Using Matplotlib

·      Create a Python Scatter Plot

·      Practical Exercise              

Lecture-18 Python Charts 
·      Prerequisites for Python Charts

·      Bubble Charts

·      3D Charts

·      Python Charts Properties

·      Styling your Python Chart

·      How to Save Python Charts File?

·      Practical Exercise              

Lecture-19 Python Heatmap and Word Cloud 
·      What is Python Heatmap & Word Cloud?

·      Create a Heatmap in Python

·      Normalizing a column

·      Create a Word Cloud Python

·      Practical Exercise              

Lecture-20 Python Histogram and Python Bar Plot 
·      Introduction to Python Histogram

·      Displaying Histogram, Rug, and Kernel Density

·      Customizing the rug

·      Customizing the density distribution

·      Vertical Python Histogram

·      Python Histogram with multiple variables

·      Introduction to Python Bar Plot

·      Horizontal Python Bar Plot

·      Adding Title and Axis Labels

·      Practical Exercise              

Lecture-21 Geographic Maps & Graph Data 
·      Prerequisites for Python Geographic Maps and Graph Data

·      Python Geographic Maps

·      Python Graph Data

·      Sparse graphs

·      Practical Exercise              

Lecture-22 Python Time Series Analysis 
·      What is Time Series in Python?

·      Plotting a Python Histogram

·      Plotting a Density Plot in Python Time Series

·      Autocorrelation Plot in Python Time Series

·      Plotting a Lag Plot in Python Time Series

·      Practical Exercise              

Lecture-23 Python Linear Regression 
·      What is Python Linear Regression?

·      Chi-Square Test

·      Practical Exercise

  Part 3: Machine Learning
Lecture-24 Introduction to Machine Learning with Python 
·      Supervised Learning

·      Unsupervised Learning

·      Steps in Python Machine Learning

·      Applications of Python Machine Learning

·      Practical Exercise              

Lecture-25 Environment Setup and Installation Process 
·      How to Install Python?

·      Starting and Updating Anaconda

·      Installing Needed Python Libraries

·      Practical Exercise             

Lecture-26 Data Pre-processing, Analysis & Visualization 
·      Data Pre-processing in Python Machine Learning

·      Python Data Pre-processing Techniques

·      Analyzing Data in Python Machine Learning

·      Visualizing Data-Univariate Plots in Python Machine Learning

·      Visualizing Data-Multivariate Plots in Python Machine Learning

·      Practical Exercise              

Lecture-27 Train and Test Set 
·      Training and Test Data in Python Machine Learning

·      How to Split Train and Test Set in Python Machine Learning?

·      Plotting of Train and Test Set in Python

·      Practical Exercise              

Lecture-28 Machine Learning Techniques with Python 
·      Machine Learning Techniques vs. Algorithms

·      Machine Learning Regression

·      Linear Regression and Non-Linear Regression

·      Machine Learning Classification

·      Decision Tree Induction

·      Rule-based Classification

·      Classification by Back propagation

·      Lazy Learners

·      Clustering

·      Anomaly Detection

·      Practical Exercise              

Lecture-29 Machine Learning Algorithms in Python 
·      Linear Regression

·      Logistic Regression

·      Decision Tree

·      Support Vector Machines (SVM)

·      Naive Bayes

·      kNN (k-Nearest Neighbors)

·      Random Forest

·      Practical Exercise

  Part 4: Deep Learning
Lecture-30 Introduction to Deep Learning with Python 
·      What is Deep Learning with Python?

·      Characteristics of Deep Learning With Python

·      Deep Neural Networks

·      Deep Learning Applications

·      Practical Exercise              

Lecture-31 Python Deep Learning Environment Setup 
·      How to Install Python?

·      Python Libraries

·      Python Text Editor

·      Python Hardware

·      Practical Exercise              

Lecture-32 Libraries and Frameworks 
·      TensorFlow Python

·      Keras Python

·      Apache mxnet

·      Caffe

·      Theano Python

·      Microsoft Cognitive Toolkit

·      PyTorch

·      Eclipse DeepLearning4J

·      Lasagne

·      Nolearn

·      PyLearn2

·      Practical Exercise              

Lecture-33 Deep Neural Networks With Python 
·      Define Deep Neural Network with Python

·      Artificial Neural Networks

·      Deep Neural Networks

·      Structure of Deep Neural Network

·      Types of Deep Neural Networks with Python

·      Challenges to Deep Neural Networks

·      Deep Belief Networks

·      Practical Exercise              

Lecture-34 Computational Graphs 
·      Deep Learning Computational Graphs

·      Need of Computational Graph

·      Composite Function

·      Visualizing a Computation Graph in Python

·      Dynamic Deep Learning Python Computational Graphs

·      Forward and Backward Propagation in Computational Graphs

·      Practical Exercise

  Part 5: Artificial Intelligence
Lecture-35 Introduction to Artificial Intelligence with Python 
·      What is Artificial Intelligence?

·      Python AI–Approaches

·      Artificial Intelligence Tools

·      Search and Optimization

·      Logic

·      Probabilistic Methods for Uncertain Reasoning

·      Classifiers and Statistical Learning Methods

·      Artificial Neural Networks

·      Evaluating Progress

·      Applications of Artificial Intelligence

·      Practical Exercise              

Lecture-36 NLTK Python 
·      What is NLTK?

·      How to Install NLTK?

·      NLTK Tokenize Text

·      Find Synonyms From NLTK WordNet

·      Find Antonyms From NLTK WordNet

·      Stemming NLTK

·      Lemmatizing NLTK Using WordNet

·      NLTK Stop Words

·      Speech Tagging

·      Practical Exercise              

Lecture-37 Python Speech Recognition – Artificial Intelligence 
·      What is Python Speech Recognition?

·      Reading an Audio File in Python

·      Reading a Segment of Audio

·      Python Speech Recognition – Dealing with Noise

·      Working With Microphones

·      Practical Exercise              

Lecture-38 Natural Language Processing (NLP) 
·      Introduction to Natural Language Processing

·      Components of NLP

·      Benefits of NLP

·      Libraries for NLP

·      Glossary in NLP

·      Tasks in NLP

·      NLP Applications

·      Practical Exercise              

Lecture-39 Heuristic Search 
·      What is a Heuristic Search?

·      Heuristic Search Techniques in Artificial Intelligence

·      Hill Climbing in Artificial Intelligence

·      Features of Hill Climbing in AI

·      Types of Hill Climbing in AI

·      Problems with Hill Climbing in AI

·      Constraint Satisfaction Problems (CSP)

·      Simulated Annealing Heuristic Search

·      Best-First Search (BFS) Heuristic Search

·      Practical Exercise              

Lecture-40 Python Genetic Algorithms 
·      What are Genetic Algorithms With Python?

·      Operators of Python Genetic Algorithms

·      Benefits of Python Genetic Algorithms

·      Limitations of Python Genetic Algorithms

·      Applications of Python Genetic Algorithms

·      Practical Exercise

  Case Studies