Azure Machine Learning Certification

What is HTML

What is a Web Browser

What are Versions of HTML

What can you Do with HTML

HTML Development Environments

Writing Code with a Text Editor

Rules of Syntax

Making your Code Readable

Building a Document

Using Colors

Adding Color to your Page

Using Headings

Using Paragraphs

Aligning Block-Level Elements

Displaying Preformatted Text

Formatting with Inline Elements

Controlling Fonts

Introducing List Elements

Creating Unordered Lists

Creating Ordered Lists

Nesting Lists

Building a Table

Cell Padding and Cell Spacing

Controlling Table and Cell Width

Aligning a Table on the Page

Aligning Tables and Text

Aligning Table Data

Spanning Columns and Rows

Understanding and Using URLs

Linking to a Web Document

Linking to a Local Document

Linking to Anchors

Opening a New Browser Window

Inserting Inline Images

Aligning Images

Using Images to Anchor Links

Sizing Images

Using Transparent Images

Using GIF Animation

Forms and Form Elements

Form Actions, Form Methods, Form Design

Laying out a page with HTML5

Page Structure

New HTML5 Strutural Tags

Page Simplification

New Features of HTML5

The HTML5 Semantic Element

Current State of Browser Support

The section Tag

The article Tag

The header Tag

The Footer Tag

Supported Media Types

The audio Element

The video Element

New Input Types

autocomplete

novalidate

required

placeholder

autofocus

autocomplete

form

pattern

Inline

Internal

External

ID

Class

Attribute

Grouping

Universal

RGB Value

Hex Value

Color Name

background-color

background-repeat

background-attachement

background position

background-size

background-image

Margin-top

Margin-bottom

Margin-left

Margin-Right

Padding -top

Padding -bottom

Padding -left

Padding –Right

Outline-Style

Outline-color

Outline Width

Outline-Offset

Outline Shorthand Property

Border

border-radius

Text-shadow

Box-shadow

transition

transition - delay

transition - duration

transition - property

transform

matrix ()

translate (x,y)

scale(x,y)

rotate(angle)

Skew (x - angle, y-angle)

@keyframes

animation

animation-direction

animation-duration

animation-name

CSS combinations

Pseudo Elements

Linear Gradients

Radial Gradients

resize

box-sizing

outline-offset

Blur

Opacity

What is Responsive Web Design

Intro to the Viewport

The Viewport Tag

Media Queries

Tablet Styles

Mobile Styles

Making a Mobile Drop-down Menu

@font-face

font- family

src

font-stretch

font-Style

font-weight

flex - grow

flex - shrink

flex - basis

flex

flex - wrap

flex - direction

flex - flow

justify - content

align-items

order

What is a Framework

Introduction to Django

Django – Design Philosophies

History of Django

Why Django and Features

Environment setup

Web Server

MVC Pattern

MVC Architecture vs MVT Architecture

Django MVC – MVT Pattern

Creating the rst Project

Integrating the Project to sublime text

The Project Structure

Running the server

Solving the issues and Migrations

Database Setup

Setting Up Your Project.

What Django Follows

Structure of Django framework

Model Layer

What are models

Model elds

Query sets

Django – Admin Interface

Starting the Admin Interface

Migrations

Views Layer

Simple View

Basic view (displaying hello world)

Functional views, class based views

Organizing Your URLs

Role of URLs in Django

Working URLs

Forms

Sending Parameters to Views

Templates layer

The Render Function

Installation and Working with Python

Understanding Python variables

Python basic Operators

Understanding the Python blocks.

Python Keyword and Identiers

Python Comments, Multiline Comments.

Python Indentation

Understating the concepts of Operators

• Arithmetic

• Relational

• Logical

• Assignment

• Membership

• Identity

Variables, expression condition and function

Global and Local Variables in Python

Packing and Unpacking Arguments

Type Casting in Python

Byte objects vs. string in Python

Variable Scope

Declaring and using Numeric data types

Using string data type and string operations

Understanding Non-numeric data types

Understanding the concept of Casting and Boolean.

Strings

List

Tuples

Dictionary

Sets

Statements – if, else, elif

How to use nested IF and Else in Python

Loops

Loops and Control Statements.

Jumping Statements – Break, Continue, pass

Looping techniques in Python

How to use Range function in Loop

Programs for printing Patterns in Python

How to use if and else with Loop

Use of Switch Function in Loop

Elegant way of Python Iteration

Generator in Python

How to use nested Loop in Python

Use If and Else in for and While Loop

Examples of Looping with Break and Continue Statement

How to use IN or NOT IN keyword in Python Loop.

Python Syntax

Function Call

Return Statement

Arguments in a function – Required, Default, Positional, Variable-length

Write an Empty Function in Python –pass statement.

Lamda/ Anonymous Function

*args and **kwargs

Help function in Python

Scope and Life Time of Variable in Python Function

Nested Loop in Python Function

Recursive Function and Its Advantage and Disadvantage

Organizing python codes using functions

Organizing python projects into modules

Importing own module as well as external modules

Understanding Packages

Random functions in python

Programming using functions, modules & external packages

Map, Filter and Reduce function with Lambda Function

More example of Python Function

Day, Month, Year, Today, Weekday

IsoWeek day

Date Time

Time, Hour, Minute, Sec, Microsec

Time Delta and UTC

StrfTime, Now

Time stamp and Date Format

Month Calendar

Itermonthdates

Lots of Example on Python Calendar

Create 12-month Calendar

Strftime

Strptime

Format Code list of Data, Time and Cal

Locale’s appropriate date and time

What is List.

List Creation

List Length

List Append

List Insert

List Remove

List Append & Extend using “+” and Keyword

List Delete

List related Keyword in Python

List Revers

List Sorting

List having Multiple Reference

String Split to create a List

List Indexing

List Slicing

List count and Looping

List Comprehension and Nested Comprehension

What is Tuple

Tuple Creation

Accessing Elements in Tuple

Changing a Tuple

Tuple Deletion

Tuple Count

Tuple Index

Tuple Membership

TupleBuilt in Function (Length, Sort)

Dict Creation

Dict Access (Accessing Dict Values)

Dict Get Method

Dict Add or Modify Elements

Dict Copy

Dict From Keys.

Dict Items

Dict Keys (Updating, Removing and Iterating)

Dict Values

Dict Comprehension

Default Dictionaries

Ordered Dictionaries

Looping Dictionaries

Dict useful methods (Pop, Pop Item, Str , Update etc.)

What is Set

Set Creation

Add element to a Set

Remove elements from a Set

PythonSet Operations

Frozen Sets

What is Set

Set Creation

Add element to a Set

Remove elements from a Set

PythonSet Operations

Python Errors and Built-in-Exceptions

Exception handing Try, Except and Finally

Catching Exceptions in Python

Catching Specic Exception in Python

Raising Exception

Try and Finally

Opening a File

Python File Modes

Closing File

Writing to a File

Reading from a File

Renaming and Deleting Files in Python

Python Directory and File Management

List Directories and Files

Making New Directory

Changing Directory

SQL Database connection using

Creating and searching tables

Reading and Storing cong information on database

Programming using database connections

Installing SMTP Python Module

Sending Email

Reading from le and sending emails to all users

Working With Excel

Reading an excel le using Python

Writing to an excel sheet using Python

Python| Reading an excel le

Python | Writing an excel le

Adjusting Rows and Column using Python

ArithmeticOperation in Excel le.

Play with Workbook, Sheets and Cells in Excel using Python

Creating and Removing Sheets

Formatting the Excel File Data

More example of Python Function

Check Dirs. (exist or not)

How to split path and extension

How to get user prole detail

Get the path of Desktop, Documents, Downloads etc.

Handle the File System Organization using OS

How to get any les and folder’s details using OS

Categorical Data

Numerical Data

Mean

Median

Mode

Outliers

Range

Interquartile range

Correlation

Standard Deviation

Variance

Box plot

Read data from Excel File using Pandas More Plotting, Date Time Indexing and writing to les

How to get record specic records Using Pandas Adding & Resetting Columns, Mapping with function

Using the Excel File class to read multiple sheets More Mapping, Filling

Nonvalue’s

Exploring the Data Plotting, Correlations, and Histograms

Getting statistical information about the data Analysis Concepts, Handle the None Values

Reading les with no header and skipping records Cumulative Sums and Value Counts, Ranking etc

Reading a subset of columns Data Maintenance, Adding/Removing Cols and Rows

Applying formulas on the columns Basic Grouping, Concepts of Aggre

gate Function

Complete Understanding of Pivot Table Data Slicing using iLoc and Loc property (Setting Indices)

Under sting the Properties of Pivot Table in Pandas Advanced Reading

CSVs/HTML, Binning, Categorical Data

Exporting the results to Excel Joins:

Python | Pandas Data Frame Inner Join

Under sting the properties of Data Frame Left Join (Left Outer Join)

Indexing and Selecting Data with Pandas Right Join (Right Outer Join)

Pandas | Merging, Joining and Concatenating Full Join (Full Outer Join)

Pandas | Find Missing Data and Fill and Drop NA Appending DataFrame and Data

Pandas | How to Group Data How to apply Lambda / Function on Data

Frame

Other Very Useful concepts of Pandas in Python Data Time Property in Pandas (More and More)

Introduction to NumPy: Numerical Python

Importing NumPy and Its Properties

NumPy Arrays

Creating an Array from a CSV

Operations an Array from a CSV

Operations with NumPy Arrays

Two-Dimensional Array

Selecting Elements from 1-D Array

Selecting Elements from 2-D Array

Logical Operation with Arrays

Indexing NumPy elements using conditionals

NumPy’s Mean and Axis

NumPy’s Mode, Median and Sum Function

NumPy’s Sort Function and More

Bar Chart using Python MatPlotLib

Column Chart using Python MatPlotLib

Pie Chart using Python MatPlotLib

Area Chart using Python MatPlotLib

Scatter Plot Chart using Python MatPlotLib

Play with Charts Properties Using MatPlotLib

Export the Chart as Image

Understanding plt. subplots () notation

Legend Alignment of Chart using MatPlotLib

Create Charts as Image

Other Useful Properties of Charts.

Complete Understanding of Histograms

Plotting Different Charts, Labels, and Labels Alignment etc.

Introduction to Seaborn

Making a scatter plot with lists

Making a count plot with a list

Using Pandas with seaborn

Tidy vs Untidy data

Making a count plot with a Dataframe

Adding a third variable with hue

Hue and scattera plots

Hue and count plots

Introduction to relational plots and subplots

Creating subplots with col and row

Customizing scatters plots

Changing the size of scatter plot points

Changing the style of scatter plot points

Introduction to line plots

Interpreting line plots

Visualizing standard deviation with line plots

Plotting subgroups in line plots

Current plots and bar plots

Count plots

Bar plot with percentages

Customizing bar plots

Box plots

Create and interpret a box plot

Omitting outliers

Adjusting the whisk

Point plots

Customizing points plots

Point plot with subgroups

Changing plot style and colour

Changing style and palette

Changing the scale

Using a custom palette

Adding titles and labels: Part 1

Face Grids vs. Axes Subplots

Adding a title to a face Grid object

Adding title and labels: Part 2

Adding a title and axis labels

Rotating x-tics labels

Putting it all together

Box plot with subgroups

Bar plot with subgroups and subplots

Well done! What’s next

Installation and Working with Python

Understanding Python variables

Python basic Operators

Understanding the Python blocks.

Python Keyword and Identiers

Python Comments, Multiline Comments.

Python Indentation

Understating the concepts of Operators

• Arithmetic

• Relational

• Logical

• Assignment

• Membership

• Identity

Variables, expression condition and function

Global and Local Variables in Python

Packing and Unpacking Arguments

Type Casting in Python

Byte objects vs. string in Python

Variable Scope

Declaring and using Numeric data types

Using string data type and string operations

Understanding Non-numeric data types

Understanding the concept of Casting and Boolean.

• Strings

• List

• Tuples

• Dictionary

• Sets

Statements – if, else, elif

How to use nested IF and Else in Python

Loops

Loops and Control Statements.

Jumping Statements – Break, Continue, pass

Looping techniques in Python

How to use Range function in Loop

Programs for printing Patterns in Python

How to use if and else with Loop

Use of Switch Function in Loop

Elegant way of Python Iteration

Generator in Python

How to use nested Loop in Python

Use If and Else in for and While Loop

Examples of Looping with Break and Continue Statement

How to use IN or NOT IN keyword in Python Loop.

Python Syntax

Function Call

Return Statement

Arguments in a function – Required, Default, Positional, Variable-length

Write an Empty Function in Python –pass statement.

Lamda/ Anonymous Function

*args and **kwargs

Help function in Python

Scope and Life Time of Variable in Python Function

Nested Loop in Python Function

Recursive Function and Its Advantage and Disadvantage

Organizing python codes using functions

Organizing python projects into modules

Importing own module as well as external modules

Understanding Packages

Random functions in python

Programming using functions, modules & external packages

Map, Filter and Reduce function with Lambda Function

More example of Python Function

Day, Month, Year, Today, Weekday

IsoWeek day

Date Time

Time, Hour, Minute, Sec, Microsec

Time Delta and UTC

StrfTime, Now

Time stamp and Date Format

Month Calendar

Itermonthdates

Lots of Example on Python Calendar

Create 12-month Calendar

Strftime

Strptime

Format Code list of Data, Time and Cal

Locale’s appropriate date and time

What is List.

List Creation

List Length

List Append

List Insert

List Remove

List Append & Extend using “+” and Keyword

List Delete

List related Keyword in Python

List Revers

List Sorting

List having Multiple Reference

String Split to create a List

List Indexing

List Slicing

List count and Looping

List Comprehension and Nested Comprehension

What is Tuple

Tuple Creation

Accessing Elements in Tuple

Changing a Tuple

Tuple Deletion

Tuple Count

Tuple Index

Tuple Membership

TupleBuilt in Function (Length, Sort)

Dict Creation

Dict Access (Accessing Dict Values)

Dict Get Method

Dict Add or Modify Elements

Dict Copy

Dict From Keys.

Dict Items

Dict Keys (Updating, Removing and Iterating)

Dict Values

Dict Comprehension

Default Dictionaries

Ordered Dictionaries

Looping Dictionaries

Dict useful methods (Pop, Pop Item, Str , Update etc.)

What is Set

Set Creation

Add element to a Set

Remove elements from a Set

PythonSet Operations

Frozen Sets

What is Set

Set Creation

Add element to a Set

Remove elements from a Set

PythonSet Operations

Python Errors and Built-in-Exceptions

Exception handing Try, Except and Finally

Catching Exceptions in Python

Catching Specic Exception in Python

Raising Exception

Try and Finally

Opening a File

Python File Modes

Closing File

Writing to a File

Reading from a File

Renaming and Deleting Files in Python

Python Directory and File Management

List Directories and Files

Making New Directory

Changing Directory

SQL Database connection using

Creating and searching tables

Reading and Storing cong information on database

Programming using database connections

Installing SMTP Python Module

Sending Email

Reading from le and sending emails to all users

Working With Excel

Reading an excel le using Python

Writing to an excel sheet using Python

Python| Reading an excel le

Python | Writing an excel le

Adjusting Rows and Column using Python

ArithmeticOperation in Excel le.

Play with Workbook, Sheets and Cells in Excel using Python

Creating and Removing Sheets

Formatting the Excel File Data

More example of Python Function

Check Dirs. (exist or not)

How to split path and extension

How to get user prole detail

Get the path of Desktop, Documents, Downloads etc.

Handle the File System Organization using OS

How to get any les and folder’s details using OS

Categorical Data

Numerical Data

Mean

Median

Mode

Outliers

Range

Interquartile range

Correlation

Standard Deviation

Variance

Box plot

Read data from Excel File using Pandas More Plotting, Date Time Indexing and writing to les

How to get record specic records Using Pandas Adding & Resetting Columns, Mapping with function

Using the Excel File class to read multiple sheets More Mapping, Filling

Nonvalue’s

Exploring the Data Plotting, Correlations, and Histograms

Getting statistical information about the data Analysis Concepts, Handle the None Values

Reading les with no header and skipping records Cumulative Sums and Value Counts, Ranking etc

Reading a subset of columns Data Maintenance, Adding/Removing Cols and Rows

Applying formulas on the columns Basic Grouping, Concepts of Aggre

gate Function

Complete Understanding of Pivot Table Data Slicing using iLoc and Loc property (Setting Indices)

Under sting the Properties of Pivot Table in Pandas Advanced Reading

CSVs/HTML, Binning, Categorical Data

Exporting the results to Excel Joins:

Python | Pandas Data Frame Inner Join

Under sting the properties of Data Frame Left Join (Left Outer Join)

Indexing and Selecting Data with Pandas Right Join (Right Outer Join)

Pandas | Merging, Joining and Concatenating Full Join (Full Outer Join)

Pandas | Find Missing Data and Fill and Drop NA Appending DataFrame and Data

Pandas | How to Group Data How to apply Lambda / Function on Data

Frame

Other Very Useful concepts of Pandas in Python Data Time Property in Pandas (More and More)

Introduction to NumPy: Numerical Python

Importing NumPy and Its Properties

NumPy Arrays

Creating an Array from a CSV

Operations an Array from a CSV

Operations with NumPy Arrays

Two-Dimensional Array

Selecting Elements from 1-D Array

Selecting Elements from 2-D Array

Logical Operation with Arrays

Indexing NumPy elements using conditionals

NumPy’s Mean and Axis

NumPy’s Mode, Median and Sum Function

NumPy’s Sort Function and More

Bar Chart using Python MatPlotLib

Column Chart using Python MatPlotLib

Pie Chart using Python MatPlotLib

Area Chart using Python MatPlotLib

Scatter Plot Chart using Python MatPlotLib

Play with Charts Properties Using MatPlotLib

Export the Chart as Image

Understanding plt. subplots () notation

Legend Alignment of Chart using MatPlotLib

Create Charts as Image

Other Useful Properties of Charts.

Complete Understanding of Histograms

Plotting Different Charts, Labels, and Labels Alignment etc.

Introduction to Seaborn

Making a scatter plot with lists

Making a count plot with a list

Using Pandas with seaborn

Tidy vs Untidy data

Making a count plot with a Dataframe

Adding a third variable with hue

Hue and scattera plots

Hue and count plots

Introduction to relational plots and subplots

Creating subplots with col and row

Customizing scatters plots

Changing the size of scatter plot points

Changing the style of scatter plot points

Introduction to line plots

Interpreting line plots

Visualizing standard deviation with line plots

Plotting subgroups in line plots

Current plots and bar plots

Count plots

Bar plot with percentages

Customizing bar plots

Box plots

Create and interpret a box plot

Omitting outliers

Adjusting the whisk

Point plots

Customizing points plots

Point plot with subgroups

Changing plot style and colour

Changing style and palette

Changing the scale

Using a custom palette

Adding titles and labels: Part 1

Face Grids vs. Axes Subplots

Adding a title to a face Grid object

Adding title and labels: Part 2

Adding a title and axis labels

Rotating x-tics labels

Putting it all together

Box plot with subgroups

Bar plot with subgroups and subplots

Well done! What’s next

Articial Intelligence

Machine Learning

Machine Learning Algorithms

Algorithmic models of Learning

Applications of Machine Learning

Large Scale Machine Learning

Computational Learning theory

Reinforcement Learning

Supervised Learning

Unsupervised Learning

Semi-supervised and Reinforcement Learning

Bias and variance Trade-off

Representation Learning

Regression and its Types

Logistic Regression

Linear Regression

Polynomial Regression

Meaning and Types of Classification

Nearest Neighbor Classifiers

K-nearest Neighbors

Probability and Bayes Theorem

Support Vector Machines

Naive Bayes

Decision Tree Classifier

Random Forest Classifier

What are the Limitations of Machine Learning

What is Deep Learning

Advantage of Deep Learning over Machine learning

Reasons to go for Deep Learning

Real-Life use cases of Deep Learning

What is Deep Learning Networks

Why Deep Learning Networks

How Deep Learning Works

Feature Extraction

Working of Deep Network

Training using Backpropagation

Variants of Gradient Descent

Types of Deep Networks

Feed forward neural networks (FNN)

Convolutional neural networks (CNN)

Recurrent Neural networks (RNN)

Restrict Boltzman Machine (RBM)

Dene Keras

How to compose Models in Keras

Sequential Composition

Functional Composition

Predened Neural Network Layers

What is Batch Normalization

Saving and Loading a model with Keras

Customizing the Training Process

Intuitively building networks with Keras

Introduction to Convolutional Neural Networks

CNN Applications

Architecture of a Convolutional Neural Network

Convolution and Pooling layers in a CNN

Understanding and Visualizing CNN

Transfer Learning and Fine-tuning Convolutional Neural Networks

Introduction To Python

• Installation and Working with Python

• Understanding Python variables

• Python basic Operators

• Understanding the Python blocks.

Python Keyword and Identiers

• Python Comments, Multiline Comments.

• Python Indentation

• Understating the concepts of Operators
• Arithmetic
• Relational
• Logical
• Assignment
• Membership
• Identity

Introduction To Variables

• Variables, expression condition and function

• Global and Local Variables in Python

• Packing and Unpacking Arguments

• Type Casting in Python

• Byte objects vs. string in Python

• Variable Scope

Python Data Type

• Declaring and using Numeric data types

• Using string data type and string operations

• Understanding Non-numeric data types

• Understanding the concept of Casting and Boolean.

• Strings

• List

• Tuples

• Dictionary

• Sets

Control Structure & Flow

• Statements – if, else, elif

• How to use nested IF and Else in Python

• Loops

• Loops and Control Statements.

• Jumping Statements – Break, Continue, pass

• Looping techniques in Python

• How to use Range function in Loop

• Programs for printing Patterns in Python

• How to use if and else with Loop

• Use of Switch Function in Loop

• Elegant way of Python Iteration

• Generator in Python

• How to use nested Loop in Python

• Use If and Else in for and While Loop

• Examples of Looping with Break and Continue Statement

• How to use IN or NOT IN keyword in Python Loop.

Python Function, Modules and Packages

• Python Syntax

• Function Call

• Return Statement

• Arguments in a function – Required, Default, Positional, Variable-length

• Write an Empty Function in Python –pass statement.

• Lamda/ Anonymous Function

• *args and **kwargs

• Help function in Python

• Scope and Life Time of Variable in Python Function

• Nested Loop in Python Function

• Recursive Function and Its Advantage and Disadvantage

• Organizing python codes using functions

• Organizing python projects into modules

• Importing own module as well as external modules

• Understanding Packages

• Random functions in python

• Programming using functions, modules & external packages

• Map, Filter and Reduce function with Lambda Function

• More example of Python Function

Python Date Time and Calendar

• Day, Month, Year, Today, Weekday

• IsoWeek day

• Date Time

• Time, Hour, Minute, Sec, Microsec

• Time Delta and UTC

• StrfTime, Now

• Time stamp and Date Format

• Month Calendar

• Itermonthdates

• Lots of Example on Python Calendar

• Create 12-month Calendar

• Strftime

• Strptime

• Format Code list of Data, Time and Cal

• Locale’s appropriate date and time

List

• What is List.

• List Creation

• List Length

• List Append

• List Insert

• List Remove

• List Append & Extend using “+” and Keyword

• List Delete

• List related Keyword in Python

• List Revers

• List Sorting

• List having Multiple Reference

• String Split to create a List

• List Indexing

• List Slicing

• List count and Looping

• List Comprehension and Nested Comprehension

Tuple

• What is Tuple

• Tuple Creation

• Accessing Elements in Tuple

• Changing a Tuple

• Tuple Deletion

• Tuple Count

• Tuple Index

• Tuple Membership

• TupleBuilt in Function (Length, Sort)

Dictionary

• Dict Creation

• Dict Access (Accessing Dict Values)

• Dict Get Method

• Dict Add or Modify Elements

• Dict Copy

• Dict From Keys.

• Dict Items

• Dict Keys (Updating, Removing and Iterating)

• Dict Values

• Dict Comprehension

• Default Dictionaries

• Ordered Dictionaries

• Looping Dictionaries

• Dict useful methods (Pop, Pop Item, Str , Update etc.)

Sets

• What is Set

• Set Creation

• Add element to a Set

• Remove elements from a Set

• PythonSet Operations

• Frozen Sets

Strings

• What is Set

• Set Creation

• Add element to a Set

• Remove elements from a Set

• PythonSet Operations

Python Exception Handling

• Python Errors and Built-in-Exceptions

• Exception handing Try, Except and Finally

• Catching Exceptions in Python

• Catching Specic Exception in Python

• Raising Exception

• Try and Finally

Python File Handling

• Opening a File

• Python File Modes

• Closing File

• Writing to a File

• Reading from a File

• Renaming and Deleting Files in Python

• Python Directory and File Management

• List Directories and Files

• Making New Directory

• Changing Directory

Python Database Interaction

• SQL Database connection using

• Creating and searching tables

• Reading and Storing cong information on database

• Programming using database connections

Contacting user Through Emails Using Python

• Installing SMTP Python Module

• Sending Email

• Reading from le and sending emails to all users

Reading an excel

• Working With Excel

• Reading an excel le using Python

• Writing to an excel sheet using Python

• Python| Reading an excel le

• Python | Writing an excel le

• Adjusting Rows and Column using Python

• ArithmeticOperation in Excel le.

• Play with Workbook, Sheets and Cells in Excel using Python

• Creating and Removing Sheets

• Formatting the Excel File Data

• More example of Python Function

Complete Understanding of OS Module of Python

• Check Dirs. (exist or not)

• How to split path and extension

• How to get user prole detail

• Get the path of Desktop, Documents, Downloads etc.

• Handle the File System Organization using OS

• How to get any les and folder’s details using OS

Data Analysis and Visualization using Pandas.

• Statistics
• Categorical Data
• Numerical Data
• Mean
• Median
• Mode
• Outliers
• Range
• Interquartile range
• Correlation
• Standard Deviation
• Variance
• Box plot

• Pandas
• Read data from Excel File using Pandas More Plotting, Date Time Indexing and writing to les
• How to get record specic records Using Pandas Adding & Resetting Columns, Mapping with function
• Using the Excel File class to read multiple sheets More Mapping, Filling Nonvalue’s
• Exploring the Data Plotting, Correlations, and Histograms
• Getting statistical information about the data Analysis Concepts, Handle the None Values
• Reading les with no header and skipping records Cumulative Sums and Value Counts, Ranking etc
• Reading a subset of columns Data Maintenance, Adding/Removing Cols and Rows
• Applying formulas on the columns Basic Grouping, Concepts of Aggre gate Function
• Complete Understanding of Pivot Table Data Slicing using iLoc and Loc property (Setting Indices)
• Under sting the Properties of Pivot Table in Pandas Advanced Reading CSVs/HTML, Binning, Categorical Data
• Exporting the results to Excel Joins
• Python | Pandas Data Frame Inner Join
• Under sting the properties of Data Frame Left Join (Left Outer Join)
• Indexing and Selecting Data with Pandas Right Join (Right Outer Join)
• Pandas | Merging, Joining and Concatenating Full Join (Full Outer Join)
• Pandas | Find Missing Data and Fill and Drop NA Appending Data Frame and Data
• Pandas | How to Group Data How to apply Lambda / Function on Data Frame
• Other Very Useful concepts of Pandas in Python Data Time Property in Pandas (More and More)

Data Analysis and Visualization using NumPy and MatPlotLib

• NumPy
• Introduction to NumPy Numerical Python
• Importing NumPy and Its Properties
• NumPy Arrays
• Creating an Array from a CSV
• Operations an Array from a CSV
• Operations with NumPy Arrays
• Two-Dimensional Array
• Selecting Elements from 1-D Array
• Selecting Elements from 2-D Array
• Logical Operation with Arrays
• Indexing NumPy elements using conditionals
• NumPy’s Mean and Axis
• NumPy’s Mode, Median and Sum Function
• NumPy’s Sort Function and More

• MatPlotLib
• Bar Chart using Python MatPlotLib
• Column Chart using Python MatPlotLib
• Pie Chart using Python MatPlotLib
• Area Chart using Python MatPlotLib
• Scatter Plot Chart using Python MatPlotLib
• Play with Charts Properties Using MatPlotLib
• Export the Chart as Image
• Understanding plt. subplots () notation
• Legend Alignment of Chart using MatPlotLib
• Create Charts as Image
• Other Useful Properties of Charts.
• Complete Understanding of Histograms
• Plotting Different Charts, Labels, and Labels Alignment etc.

Introduction to Data Visualization with Seaborn

• Introduction to Seaborn
• Introduction to Seaborn
• Making a scatter plot with lists
• Making a count plot with a list
• Using Pandas with seaborn
• Tidy vs Untidy data
• Making a count plot with a Dataframe
• Adding a third variable with hue
• Hue and scattera plots
• Hue and count plots

• Visualizing Two Quantitative Variables
• Introduction to relational plots and subplots
• Creating subplots with col and row
• Customizing scatters plots
• Changing the size of scatter plot points
• Changing the style of scatter plot points
• Introduction to line plots
• Interpreting line plots
• Visualizing standard deviation with line plots
• Plotting subgroups in line plots

• Visualizing a Categorical and a Quantitative Variable
• Current plots and bar plots
• Count plots
• Bar plot with percentages
• Customizing bar plots
• Box plots
• Create and interpret a box plot
• Omitting outliers
• Adjusting the whisk
• Point plots
• Customizing points plots
• Point plot with subgroups

• Customizing Seaborn Plots
• Changing plot style and colour
• Changing style and palette
• Changing the scale
• Using a custom palette
• Adding titles and labels Part 1
• Face Grids vs. Axes Subplots
• Adding a title to a face Grid object
• Adding title and labels Part 2
• Adding a title and axis labels
• Rotating x-tics labels
• Putting it all together
• Box plot with subgroups
• Bar plot with subgroups and subplots
• Well done! What’s next

SQL Server Fundamentals

• SQL Server 2019 Installation

• Service Accounts & Use, Authentication Modes & Usage, Instance Congurations

• SQL Server Features & Purpose

• Using Management Studio (SSMS)

• Conguration Tools & SQLCMD

• Conventions & Collation

SQL Server 2019 Database Design

• SQL Database Architecture

• Database Creation using GUI

• Database Creation using T-SQL scripts

• DB Design using Files and File Groups

• File locations and Size parameters

• Database Structure modications

SQL Tables in MS SQL Server

• SQL Server Database Tables

• Table creation using T-SQL Scripts

• Naming Conventions for Columns

• Single Row and Multi-Row Inserts

• Table Aliases

• Column Aliases & Usage

• Table creation using Schemas

• Basic INSERT

• UPDATE

• DELETE

• SELECT queries and Schemas

• Use of WHERE, IN and BETWEEN

• Variants of SELECT statement

• ORDER BY

• GROUPING

• HAVING

• ROWCOUNT and CUBE Functions

Data Validation and Constraints

• Table creation using Constraints

• NULL and IDENTITY properties

• UNIQUE KEY Constraint and NOT NULL

• PRIMARY KEY Constraint & Usage

• CHECK and DEFAULT Constraints

• Naming Composite Primary Keys

• Disabling Constraints & Other Options

Views and Row Data Security

• Benets of Views in SQL Database

• Views on Tables and Views

• SCHEMA BINDING and ENCRYPTION

• Issues with Views and ALTER TABLE

• Common System Views and Metadata

• Common Dynamic Management views

• Working with JOINS inside views

Indexes and Query tuning

• Need for Indexes & Usage

• Indexing Table & View Columns

• Index SCAN and SEEK

• INCLUDED Indexes & Usage

• Materializing Views (storage level)

• Composite Indexed Columns & Keys

• Indexes and Table Constraints

• Primary Keys & Non-Clustered Indexes

Stored Procedures and Benets

• Why to use Stored Procedures

• Types of Stored Procedures

• Use of Variables and parameters

• SCHEMABINDING and ENCRYPTION

• INPUT and OUTPUT parameters

• System level Stored Procedures

• Dynamic SQL and parameterization

System functions and Usage

• Scalar Valued Functions

• Types of Table Valued Functions

• SCHEMABINDING and ENCRYPTION

• System Functions and usage

• Date Functions

• Time Functions

• String and Operational Functions

• ROW_COUNT

• GROUPING Functions

Triggers, cursors, memory limitations

• Why to use Triggers

• DML Triggers and Performance impact

• INSERTED and DELETED memory tables

• Data Audit operations & Sampling

• Database Triggers and Server Triggers

• Bulk Operations with Triggers

Cursors and Memory Limitations

• Cursor declaration and Life cycle

• STATIC

• DYNAMIC

• SCROLL Cursors

• FORWARD_ONLY and LOCAL Cursors

• KEYSET Cursors with Complex SPs

Transactions Management

• ACID Properties and Scope

• EXPLICIT Transaction types

• IMPLICIT Transactions and options

• AUTOCOMMIT Transaction and usage

• SAVEPOINT and Query Blocking

Introduction to Data Science

• What is Analytics & Data Science

• Common Terms in Data Science

• What is data

• Classication of data

• Relevance in industry and need of the hour

• Types of problems and business objectives in various industries

• How leading companies are harnessing the power of analytics

• Critical success drivers.

• Overview of Data Science tools & their popularity.

• Data Science Methodology & problem-solving framework.

• List of steps in Data Science projects

• Identify the most appropriate solution design for the given problem statement

• Project plan for Data Science project & key milestones based on effort estimates

• Build Resource plan for Data Science project

• Why Python for data science

Accessing/Importing and Exporting Data

• Importing Data from various sources (Csv, txt, excel, access etc)

• Database Input (Connecting to database)

• Viewing Data objects - sub setting, methods

• Exporting Data to various formats

• Important python modules Pandas

Data Manipulation Cleansing - Munging Using Python Modules

• Cleansing Data with Python

• Filling missing values using lambda function and concept of Skewness.

• Data Manipulation steps (Sorting, ltering, duplicates, merging, append ing, sub setting, derived variables, sampling, Data type conversions, renaming, formatting.

• Normalizing data

Feature Engineering in Data Science

• Feature Engineering

• Feature Selection

• Feature scaling using Standard Scaler/Min-Max scaler/Robust Scaler.

• Label encoding/one hot encoding

Data Analysis Visualization Using Python

• Introduction exploratory data analysis

• Descriptive statistics, Frequency Tables and summarization

• Univariate Analysis (Distribution of data & Graphical Analysis)

• Bivariate Analysis (Cross Tabs, Distributions & Relationships, Graphical Analysis)

• Creating Graphs- Bar/pie/line chart/histogram/ boxplot/ scatter/ densi ty etc.)

• Important Packages for Exploratory Analysis (NumPy Arrays, Matplotlib, seaborn, Pandas etc.)

Introduction to Statistics

• Descriptive Statistics

• Sample vs Population Statistics

• Random variables

• Probability distribution functions

• Expected value

• Normal distribution

• Gaussian distribution

• Z-score

• Spread and Dispersion

• Correlation and Co-variance

Introduction to Predictive Modelling

• Concept of model in analytics and how it is used

• Common terminology used in Analytics & Modelling process

• Popular Modelling algorithms

• Types of Business problems - Mapping of Techniques

• Different Phases of Predictive Modelling

EDA (Exploratory Data Analysis)

• Need for structured exploratory data

• EDA framework for exploring the data and identifying any problems with the data (Data Audit Report)

• Identify missing data

• Identify outliers’ data

• Imbalanced Data Techniques

Data Pre-Processing & Data Mining

• Data Preparation

• Feature Engineering

• Feature Scaling

• Datasets

• Dimensionality Reduction

• Anomaly Detection

• Parameter Estimation

• Data and Knowledge

• Selected Applications in Data Mining

Installation and Working with Python

Understanding Python variables

Python basic Operators

Understanding the Python blocks.

Variables, expression condition and function

Global and Local Variables in Python

Packing and Unpacking Arguments

Type Casting in Python

Byte objects vs. string in Python

Variable Scope

Declaring and usingNumeric data types

Using stringdata type and string operations

Understanding Non-numeric data types

Understanding the concept of Casting and Boolean.

Strings

List

Tuples

Dictionary

Sets

Python Keyword and Identifiers

Python Comments, Multiline Comments.

Python Indentation

Understating the concepts of Operators

List

• What is List.

• List Creation

• List Length

• List Append

• List Insert

• List Remove

• List Append & Extend using “+” and Keyword

• List Delete

• List related Keyword in Python

• List Revers

• List Sorting

• List having Multiple Reference

• String Split to create a List

• List Indexing

• List Slicing

• List count and Looping

• List Comprehension and Nested Comprehension

Dictionary

• Dict Creation

• Dict Access (Accessing Dict Values)

• Dict Get Method

• Dict Add or Modify Elements

• Dict Copy

• Dict From Keys.

• Dict Items

• Dict Keys (Updating, Removing and Iterating)

• Dict Values

• Dict Comprehension

• Default Dictionaries

• Ordered Dictionaries

• Looping Dictionaries

• Dict useful methods (Pop, Pop Item, Str , Update etc.)

Sets

• What is Set

• Set Creation

• Add element to a Set

• Remove elements from a Set

• PythonSet Operations

• Frozen Sets

Tuple

• What is Tuple

• Tuple Creation

• Accessing Elements in Tuple

• Changinga Tuple

• TupleDeletion

• Tuple Count

• Tuple Index

• TupleMembership

• TupleBuilt in Function (Length, Sort)

Control Flow

• Loops

• Loops and Control Statements (Continue, Break and Pass).

• Looping techniques in Python

• How to use Range function in Loop

• Programs for printing Patterns in Python

• How to use if and else with Loop

• Use of Switch Function in Loop

• Elegant way of Python Iteration

• Generator in Python

• How to use nested IF and Else in Python

• How to use nested Loop in Python

• Use If and Else in for and While Loop

• Examples of Looping with Break and Continue Statements

• How to use IN or NOTkeywordin Python Loop.

Python Exception Handling

• Python Errors and Built-in-Exceptions

• Exception handing Try, Except and Finally

• Catching Exceptions in Python

• Catching Specific Exception in Python

• Raising Exception

• Try and Finally

Python File Handling

• Opening a File

• Python File Modes

• Closing File

• Writing to a File

• Reading from a File

• Renaming and Deleting Files in Python

• Python Directory and File Management

• List Directories and Files

• Making New Directory

• Changing Directory

Python Function, Modules and Packages

• Python Syntax

• Function Call

• Return Statement

• Write an Empty Function in Python –pass statement.

• Lamda/ Anonymous Function

• *argsand **kwargs

• Help function in Python

• Scope and Life Time of Variable in Python Function

• Nested Loop in Python Function

• Recursive Function and Its Advantage and Disadvantage

• Organizing python codes using functions

• Organizing python projects into modules

• Importing own module as well as external modules

• Understanding Packages

• Programming using functions, modules & external packages

• Map, Filter and Reduce function with Lambda Function

• More example of Python Function

Python Object Oriented Programming—Oops

• Concept of Class, Object and Instances

• Constructor, Class attributes and Destructors

• Real time use of class in live projects

• Inheritance, Overlapping and Overloading operators

• Adding and retrieving dynamic attributes of classes

• Programming using Oops support

Python Database Interaction

• SQL Database connection using

• Creating and searching tables

• Reading and Storing configinformation on database

• Programming using database connections

Reading an excel

• Reading an excel file usingPython

• Writing toan excel sheet using Python

• Python| Reading an excel file

• Python | Writing an excel file

• Adjusting Rows and Column using Python

• ArithmeticOperation in Excel file.

• Plotting Pie Charts

• Plotting Area Charts

• Plotting Bar or Column Charts using Python.

• Plotting Doughnut Chartslusing Python.

• Consolidationof Excel File using Python

• Split of Excel File Using Python.

• Play with Workbook, Sheets and Cells in Excel using Python

• Creating and Removing Sheets

• Formatting the Excel File Data

• More example of Python Function

Working with PDF and MS Word using Python

• Extracting Text from PDFs

• Creating PDFs

• Copy Pages

• Split PDF

• Combining pages from many PDFs

• Rotating PDF’s Pages

Complete Understanding of OS Module of Python

• Check Dirs. (exist or not)

• How to split path and extension

• How to get user profile detail

• Get the path of Desktop, Documents, Downloads etc.

• Handle the File System Organization using OS

• How to get any files and folder’s details using OS

Pandas

• Read data from Excel File using Pandas More Plotting, Date Time Indexing and writing to files

• How to get record specific records Using Pandas Adding & Resetting Columns, Mapping with function

• Using the Excel File class to read multiple sheets More Mapping, Filling Nonvalue’s

• Exploring the Data Plotting, Correlations, and Histograms

• Getting statistical information about the data Analysis Concepts, Handle the None Values

• Reading files with no header and skipping records Cumulative Sums and Value Counts, Ranking etc

• Reading a subset of columns Data Maintenance, Adding/Removing Cols and Rows

• Applying formulas on the columns Basic Grouping, Concepts of Aggregate Function

• Complete Understanding of Pivot Table Data Slicing using iLocand Locproperty (Setting Indices)

• Under sting the Properties of Pivot Table in Pandas Advanced Reading CSVs/HTML, Binning, Categorical Data

• Exporting the results to Excel Joins:

• Python | Pandas Data Frame Inner Join

• Under sting the properties of Data Frame Left Join (Left Outer Join)

• Indexing and Selecting Data with Pandas Right Join (Right Outer Join)

• Pandas | Merging, Joining and Concatenating Full Join (Full Outer Join)

• Pandas | Find Missing Data and Fill and Drop NA Appending DataFrameand Data

• Pandas | How to Group Data How to apply Lambda / Function on Data Frame

• Other Very Useful concepts of Pandas in Python Data Time Property in Pandas (More and More)

NumPy

• Introduction to NumPy: Numerical Python

• Importing NumPy and Its Properties

• NumPy Arrays

• Creating an Array from a CSV

• Operations an Array from aCSV

• Operations with NumPy Arrays

• Two-Dimensional Array

• Selecting Elements from 1-D Array

• Selecting Elements from 2-D Array

• Logical Operation with Arrays

• Indexing NumPy elements using conditionals

• NumPy’sMean and Axis

• NumPy’sMode, Median and Sum Function

• NumPy’sSort Function and More

MatPlotLib

• Bar Chart using Python MatPlotLib

• Column Chart using Python MatPlotLib

• Pie Chart using Python MatPlotLib

• Area Chart using Python MatPlotLib

• Scatter Plot Chart using Python MatPlotLib

• Play with Charts Properties Using MatPlotLib

• Export the Chart as Image

• Understanding plt. subplots () notation

• Legend Alignment of Chart using MatPlotLib

• Create Charts as Image

• Other Useful Properties of Charts.

• Complete Understanding of Histograms

• Plotting Different Charts, Labels, and Labels Alignment etc.

Introduction to Seaborn

• Introduction to Seaborn

• Making a scatter plot with lists

• Making a count plot with a list

• Using Pandas with seaborn

• Tidy vs Untidy data

• Making a count plot with a Dataframe

• Adding a third variable with hue

• Hue and scattera plots

• Hue and count plots

Visualizing Two Quantitative Variables

• Introduction to relational plots and subplots

• Creating subplots with col and row

• Customizing scatters plots

• Changing the size of scatter plot points

• Changing the style of scatter plot points

• Introduction to line plots

• Interpreting line plots

• Visualizing standard deviation with line plots

• Plotting subgroups in line plots

Visualizing a Categorical and a Quantitative Variable

• Current plots and bar plots

• Count plots

• Bar plot with percentages

• Customizing bar plots

• Box plots

• Create and interpret a box plot

• Omitting outliers

• Adjusting the whiskers

• Point plots

• Customizing points plots

• Point plot with subgroups

Customizing Seaborn Plots

• Changing plot style and colour

• Changing style and palette

• Changing the scale

• Using a custom palette

• Adding titles and labels: Part 1

• Face Grids vs. Axes Subplots

• Adding a title to a face Grid object

• Adding title and labels: Part 2

• Adding a title and axis labels

• Rotating x-tics labels

• Putting it all together

• Box plot with subgroups

• Bar plot with subgroups and subplots

Introduction to MySQL

What is the MySQLdb

How do I Install MySQLdb

Connecting to the MYSQL

Selecting a database

Adding data to a table

Executing multiple queries

Exporting and Importing data tables.

SQL Functions

• Single Row Functions

• Character Functions, Number Function, Round, Truncate, Mod, Max, Min, Date

Count, Average, Sum, Now etc.

Obtaining data from Multiple Tables

Types of Joins (Inner Join, Left Join, Right Join & Full Join)

Sub-Queries Vs. Joins

Distinct, Order by, Group by, Equal to etc.

Not Null

Unique

Primary Key

Foreign Key

SQL Basic

• SQL Introduction

• SQL Syntax

• SQL Select

• SQL Distinct

• SQL Where

• SQL And & Or

• SQL Order By

• SQL Insert

• SQL Update

• SQL Delete

SQL Advance

• SQL Like

• SQL Wildcards

• SQL In

• SQL Between

• SQL Alias

• SQL Joins

• SQL Inner Join

• SQL Left Join

• SQL Right Join

• SQL Full Join

• SQL Union

SQL Functions

• SQL Avg()

• SQL Count()

• SQL First()

• SQL Last()

• SQL Max()

• SQL Min()

• SQL Sum()

• SQL Group By

What is Analytics & Data Science

Common Terms in Analytics

What is data

Classification of data

Relevance in industry and need of the hour

Types of problems and business objectives in various industries

How leading companies are harnessing the power of analytics

Critical success drivers

Overview of analytics tools & their popularity

Analytics Methodology & problem-solving framework

List of steps in Analytics projects

Identify the most appropriate solution design for the given problem statement

Project plan for Analytics project & key milestones based on effort estimates

Build Resource plan for analytics project

Why Python for data science

Importing Data from various sources (Csv, txt, excel, access etc)

Database Input (Connecting to database)

Viewing Data objects - sub setting, methods

Exporting Data to various formats

Important python modules: Pandas

Cleansing Data with Python

Filling missing values using lambda function and concept of Skewness.

Data Manipulation steps (Sorting, filtering, duplicates, merging, appending, sub setting, derived variables, sampling, Data type conversions, renaming, formatting.

Normalizing data

Feature Engineering

Feature Selection

Feature scaling using Standard Scaler/Min-Max scaler/Robust Scaler.

Label encoding/one hot encoding

Introduction exploratory data analysis

Descriptive statistics, Frequency Tables and summarization

Univariate Analysis (Distribution of data & Graphical Analysis)

Bivariate Analysis (Cross Tabs, Distributions & Relationships, Graphical Analysis)

Creating Graphs- Bar/pie/line chart/histogram/ boxplot/ scatter/ density etc.)

Important Packages for Exploratory Analysis (NumPy Arrays, Matplotlib, seaborn, Pandas etc.)

Descriptive Statistics

Sample vs Population Statistics

Random variables

Probability distribution functions

Expected value

Normal distribution

Gaussian distribution

Z-score

Central limit theorem

Spread and Dispersion

Inferential Statistics-Sampling

Hypothesis testing

Z-stats vs T-stats

Type 1 & Type 2 error

Confidence Interval

ANOVA Test

Chi Square Test

T-test 1-Tail 2-Tail Test

Correlation and Co-variance

Concept of model in analytics and how it is used

Common terminology used in Analytics & Modelling process

Popular Modelling algorithms

Types of Business problems - Mapping of Techniques

Different Phases of Predictive Modelling

Need for structured exploratory data

EDA framework for exploring the data and identifying any problems with the data (Data Audit Report)

Identify missing data

Identify outliers’ data

Imbalanced Data Techniques

Data Preparation

Feature Engineering

Feature Scaling

Datasets

Dimensionality Reduction

Anomaly Detection

Parameter Estimation

Data and Knowledge

Selected Applications in Data Mining

Artificial Intelligence

• AI overview

• Meaning, scope, and 3 stages of AI

• Decoding AI

• Features of AI

• Applications of AI

• Image recognition

• Effect of AI on society

• AI for industries

• Overview of machine learning

• ML and AI relationship

Machine Learning

Techniques of Machine Learning

Machine Learning Algorithms

Algorithmic models of Learning

Applications of Machine Learning

Large Scale Machine Learning

Computational Learning theory

Reinforcement Learning

Supervised Learning

• What is Supervised Learning

• Algorithms in Supervised learning

• Regression & Classification

• Regression vs classification

• Computation of correlation coefficient and Analysis

• Multivariate Linear Regression Theory

• Coefficient of determination (R2) and Adjusted R2

• Model Misspecifications

• Economic meaning of a Regression Model

• Bivariate Analysis

• Naive Bayes classifier, Model Training

• ANOVA (Analysis of Variance)

Semi-supervised and Reinforcement Learning

Bias and variance Trade-off

Representation Learning

Regression and its Types

Logistic Regression

Linear Regression

Polynomial Regression

Meaning and Types of Classification

Nearest Neighbor Classifiers

K-nearest Neighbors

Probability and Bayes Theorem

Support Vector Machines

Naive Bayes

Decision Tree Classifier

Random Forest Classifier

About Clustering

Clustering Algorithms

K-means Clustering

Hierarchical Clustering

Distribution Clustering

Ensemble approach

K-fold cross validation

Grid search cross validation

Ada boost and XG Boost

What are the Limitations of Machine Learning

What is Deep Learning

Advantage of Deep Learning over Machine learning

Reasons to go for Deep Learning

Real-Life use cases of Deep Learning

What is Deep Learning Networks

Why Deep Learning Networks

How Deep Learning Works

Feature Extraction

Working of Deep Network

Training using Backpropagation

Variants of Gradient Descent

Types of Deep Networks

Feed forward neural networks (FNN)

Convolutional neural networks (CNN)

Recurrent Neural networks (RNN)

Generative Adversal Neural Networks (GAN)

Restrict Boltzman Machine (RBM)

Define Keras

How to compose Models in Keras

Sequential Composition

Functional Composition

Predefined Neural Network Layers

What is Batch Normalization

Saving and Loading a model with Keras

Customizing the Training Process

Intuitively building networks with Keras

Introduction to Convolutional Neural Networks

CNN Applications

Architecture of a Convolutional Neural Network

Convolution and Pooling layers in a CNN

Understanding and Visualizing CNN

Transfer Learning and Fine-tuning Convolutional Neural Networks

Intro to RNN Model

Application use cases of RNN

Modelling sequences

Training RNNs with Backpropagation

Long Short-Term Memory (LSTM)

Recursive Neural Tensor Network Theory

Recurrent Neural Network Model

Time Series Forecasting

NLP with python

Bags of words

Stemming

Tokenization

Lemmatization

TF-IDF

Sentiment Analysis

Overview of Tensor Flow

Tensor Flow code-basics

Graph Visualization

Constants, Placeholders, Variables

Tensor flow Basic Operations

Linear Regression with Tensor Flow

Logistic Regression with Tensor Flow

K Nearest Neighbor algorithm with Tensor Flow

K-Means classifier with Tensor Flow

Random Forest classifier with Tensor Flow

Quick recap of Neural Networks

Activation Functions, hidden layers, hidden units

Illustrate & Training a Perceptron

Important Parameters of Perceptron

Understand limitations of A Single Layer Perceptron

Illustrate Multi-Layer Perceptron

Back-propagation – Learning Algorithm

Understand Back-propagation – Using Neural Network Example

TensorBoard

What is Big Data

Big Data Customer Scenarios

Understanding BIG Data: Summary

Few Examples of BIG Data

Why BIG data is a BUZZ

How Hadoop Solves the Big Data Problem

What is Hadoop

Hadoop’s Key Characteristics

Hadoop Cluster and its Architecture

Hadoop: Different Cluster Modes

Why Spark is needed

What is Spark

How Spark differs from other frameworks

Spark at Yahoo!

What is BIG data Analytics

Why BIG Data Analytics is a ‘need’ now

BIG Data: The Solution

Implementing BIG Data Analytics – Different Approaches

The Traditional Approach: Business Requirement Drives Solution Design

The BIG Data Approach: Information Sources drive Creative Discovery

Traditional and BIG Data Approaches

BIG Data Complements Traditional Enterprise Data Warehouse

Traditional Analytics Platform v/s BIG Data Analytics Platform

Scala

• What is Scala

• Scala in other Frameworks

• Introduction to Scala REPL

• Basic Scala Operations

• Variable Types in Scala

• Control Structures in Scala

• Understanding the constructor overloading,

• Various abstract classes

• The hierarchy types in Scala,

• For-each loop, Functions and Procedures

• Collections in Scala- Array

Spark

• Overview to Spark

• Spark installation, Spark configuration,

• Spark Components & its Architecture

• Spark Deployment Modes

• Limitations of Map Reduce in Hadoop

• Working with RDDs in Spark

• Introduction to Spark Shell

• Deploying Spark without Hadoop

• Parallel Processing

• Spark MLLib - Modelling Big Data with Spark

What is Kafka Why Kafka

Configuring Kafka Cluster

Kafka architecture

Producing and consuming messages

Operations, Kafka monitoring tool

Need of Apache Flume

What is Apache Flume

Understanding the architecture of Flume

Basic Flume Architecture

Background and Development

Three waves of Internet

Why IoT

Market Analysis & Investment In IoT

Industrial & Consumer IoT

M2M communication and automation history

Relation with embedded systems

General introduction to Arduino , Raspberry Pi and SmartWifi boards

How IoT Works

High level Data Flow in IoT

Technical Architecture

Description of all layers of IoT Architecture

Technologies for IoT

What is IoT application

What are basic elements / building blocks of IoT app

How are these blocks connected together

The systematic method to design IoT application

Architecting our hands-on project

Learning fundamentals of Raspberry Pi

Different types of pi boards.

Installation of OS in Raspberry Pi

Programming Raspberry Pi Using Python