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C Language
C Language

About C-Language Training:

C is a basic building block for every language. It is a general Purpose Language.  To develop the programming skills ‘C’ is the only platform to develop programming techniques for any type of language. It is a Mid-level programming language for systems programming very widely used, relatively low-level, weakly typed, systems programming language associated with Unix, and through that with Linux and the open-source movement Performance becomes somewhat portable. Many Applications Like System Software, Application Software, Embedded Systems, Cool Games, Mobile applications, Device Drivers Programming, etc of the World applications written in C and the List continues…C Designed and implemented by Dennis Ritchie 1972.

C Training Course Objective:

This Course's main objective for the student to develop primary programming skills up to the higher end in order to solve the different programming logic. The student can able write a different type of logic at the end of the sessions. After learning the C  course the student can able get all the fundamental knowledge in all the languages. After Completion the student can able to attend any MNC Company interview and can solve the technical rounds both theoretically and Practically. We Provide a lot of logical examples to make it as good as.

Antennas

C  Training Course Overview:

Fundamentals in C

  • Program

  • Programming

  • Programming Languages

  • Types of software

  • Introduction to C

  • History of C

  • Features of C

  • Applications of C

  • Character set, ASCII Table

  • Tokens

  • Keywords

  • Identifiers & Naming Rules

  • constants

  • Data Types

  • Type Qualifiers

  • How does the data stored in Computers Memory

  • Variables

  • Variable Declaration

  • Variable Assignment

  • Variable Initialization

  • Comments

  • Defining Constants

  • MCQs

Operators and Expressions

  • Arithmetic operators

  • Arithmetic expressions

  • Evaluation of expressions

  • Relational operators

  • Logical operators

  • Assignment operators

  • Increment & decrement operators

  • Conditional operator

  • Bitwise operators

  • Type casting

  • Sizeof operator

  • Comma operator

  • Operators Precedence and Associativity

  • Expressions

  • Evaluation of Expressions

  • MCQs

Input-Output Functions

  • Input-Output Library Functions

  • Non-formatted Input and Output

  • Character oriented Library functions

  • Compiler, Linker and Loader

  • Program execution phases

  • Formatted Library Functions

  • Mathematical Library Functions

  • Structure of a C Program

  • IDE

  • Basic programs

  • MCQs

Control Statements

  • Conditional Control Statements

    • if

    • if-else

    • nested if-else

    • if-else-if ladder

  • Multiple Branching Control Structure

    • switch-case

  • Loop Control statements

    • while

    • do-while

    • for

  • Nested Loops

  • Jump Control structures

  • break

  • continue

  • goto

  • return

  • Programs

  • MCQs

Arrays

  • Arrays

  • One dimensional arrays

  • Declaration of 1D arrays

  • Initialization of 1D arrays

  • Accessing element of 1D arrays

  • Reading and displaying elements

  • Programs on 1D Arrays

  • Two dimensional arrays

  • Declaration of 2D arrays

  • Initialization of 2D arrays

  • Accessing element of 2D arrays

  • Reading and displaying elements

  • Programs on 2D Arrays

  • Three dimensional arrays

  • MCQs

Strings

  • String Concept

  • Introduction to String in C

  • Storing Strings

  • The string Delimiter

  • String Literals (String Constants)

  • Strings and Characters

  • Declaring Strings

  • Initializing Strings

  • Strings and the Assignment Operator

  • String Input Functions / Reading Strings

  • String Output Functions / Writing Strings

  • String Input-Output using fscanf() and fprintf() Functions

  • Single Character Library Functions / Character Manipulation in the String

  • String Manipulation Library Functions

  • Programs Using Character Arrays

  • Array of Strings (2D Character Arrays)

  • Programs Using Array of Strings

  • MCQs

Pointers

  • Understanding Memory Addresses

  • Pointer Operators

  • Pointer

  • Pointer Advantages and Disadvantages

  • Declaration of Pointer Variables

  • Initialization of Pointer Variables

  • Dereferencing / Redirecting Pointer Variables

  • Declaration versus Redirection

  • Void Pointer

  • Null Pointer

  • Compatibility

  • Array of Pointers

  • Pointer to Pointer

  • Pointer Arithmetic

  • Dynamic Memory Allocation Functions

Functions

  • Functions

  • Advantages of using functions

  • Defining a function

  • Calling a function

  • Return statement

  • Function Prototype

  • Basic Function Designs

  • Programs Using Functions

  • Scope

  • Recursion

  • Iteration vs Recursion

  • Nested functions

  • Variable Length Number of Arguments

  • Parameter Passing Techniques – Call by value & Call by Address

  • Functions Returning Pointers

  • Pointers and One-Dimensional Arrays

  • Pointers and Two-Dimensional Arrays

  • Passing 1D arrays to Functions

  • Passing 2D arrays to Functions

  • Pointers and Strings

  • Passing Strings to Functions

  • Pointer to Function

  • MCQs

Storage Classes

  • Object Attributes

  • Scope

  • Extent

  • Linkage

  • auto

  • static

  • extern

  • register

  • MCQs

Preprocessor Directives

  • The #include Preprocessor Directive & User defined header files

  • The #define Preprocessor Directive: Symbolic Constants

  • The #define Preprocessor Directive: Macros

  • Conditional Compilation Directives

  • #if

  • #else

  • #elif

  • #endif

  • #ifdef

  • #ifndef

  • #undef

  • #error

  • #line

  • #pragma

  • MCQs

Structures, Unions, Enumerations and Typedef

  • Structures

  • Structure Type Declaration

  • Structure Variable Declaration

  • Initialization of Structure

  • Accessing the members of a structure

  • Programs Using Structures

  • Operations on Structures (Copying and Comparing Structures)

  • Nested structures (Complex Structures)

  • Structures Containing Arrays (Complex Structures)

  • Array of Structures (Complex Structures)

  • Pointer to Structure

  • Accessing structure member through pointer using dynamic memory allocation

  • Pointers within Structures

  • Self-referential structures

  • Passing Structures to Functions

  • Functions returning Structures

  • Unions

  • Differences between Structures & Unions

  • Enumerated Types / enum keyword

  • The Type Definition / typedef keyword

  • Bit fields

  • MCQs

Command Line Arguments

Files

  • Concept of a file

  • Streams

  • Text File and Binary Files

  • State of a File

  • Opening and Closing Files

  • File Input / Output Functions

  • Formatted Input-Output Functions

  • Character Input-Output Functions

  • Line Input-Output Functions

  • Block Input-Output Functions

  • File Status Functions (Error Handling)

  • Positioning Functions

  • System File Operations

  • MCQs

Graphics

  • Initialization of graphics

  • Drawing shapes using pre-defined functions

  • Finding the resolution of screen

  • Setting colors to text and window

  • Font settings

  • Fill styles

  • Basic GUI applications

Core Java 

Core Java Training Overview:

This Core Java Training is by the Real-Time Professionals and Teaching Experts.

  • The entire SCJP syllabus will be covered

  • Every program execution will be explained with Compiler and JVM Architectures

  • Every program memory diagram will be clearly explained with JVM Architecture

  • 1000+ Programs will be covered in training as well as in practice material

  • The entire list of interview questions will be covered on every concept

  • Every concept will be clearly explained with real-time project scenarios

  • Every concept will be explained with MVC and LC-RP Architectures

  • Therefore you will get good knowledge in designing and developing projects

  • So that you can clear all interviews as a fresher or as an experienced

Core Java 

Core Java Training Content Overview:

Java Language, OOPS, Programming

  • Introduction to Java and OOPS

  • Java Tokens- Comments, Identifiers, Keywords, Separators

  • Working with Java Editor Softwares – Editplus, NetBeans, Eclipse

  • Packages with static imports

  • Working with jar

  • Modifiers – File level, Access level, and Non-access level

  • Datatypes, Literals, Variables, Type Conversion, Casting & Promotion

  • Reading runtime values from keyboard and Properties File

  • Operators and Control Statements

  • Method and Types of methods

  • Variable and Types of Variables

  • Constructor and Types of constructors

  • Block and Types of Blocks

  • Declarations, Invocations, and Executions

  • Compiler & JVM Architecture with Reflection API

  • Static Members and their execution control flow

  • Non-Static Members and their execution control flow

  • Final Variables and their rules

  • Classes and Types of classes

  • OOPS- Fundamentals, Models, Relations, and Principles

  • Coupling and Cohesion (MVC and LCRP Architectures)

  • Types of objects & Garbage Collection

  • Arrays and Var-arg types

  • Enum and Annotation

  • Design PatternsJava API and Project

  • API and API Documentation

  • Fundamental Classes – Object, Class, System, Runtime

  • String Handling

  • Exception Handling and Assertions

  • Multithreading with JVM Architecture

  • IO Streams (File IO)

  • Networking (Socket Programming)

  • Wrapper Classes with Autoboxing and unboxing

  • Collections with Generics

  • Java 5, 6, 7, 8 new features

  • Inner classes

  • AWT, Swings, Applet

  • Regular Expressions

  • Formatting date, time (java.text package)

Python Training
Python Training

Python Training Overview:

Python is a general-purpose interpreted, interactive, object-oriented, and high-level programming language. Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis

What are the Python Course Pre-requisites:

There are no hard pre-requisites. A basic understanding of Computer Programming terminologies is sufficient. Also, basic concepts related to Programming and Database is beneficial but not mandatory.

Objectives of the Course:

  • To understand the concepts and constructs of Python

  • To create own Python programs, know the machine learning algorithms in Python, and work on a real-time project running on Python

Python Course Content:

Core Python

Introduction to Languages

  • What is Language?

  • Types of languages

  • Introduction to Translators

    • Compiler

    • Interpreter

  • What is Scripting Language?

  • Types of Script

  • Programming Languages v/s Scripting Languages

  • Difference between Scripting and Programming languages

  • What is a programming paradigm?

  • Procedural programming paradigm

  • Object-Oriented Programming paradigm

Introduction to Python

  • What is Python?

  • WHY PYTHON?

  • History

  • Features – Dynamic, Interpreted, Object-oriented, Embeddable, Extensible, Large standard libraries, Free and Open source

  • Why Python is General Language?

  • Limitations of Python

  • What is PSF?

  • Python implementations

  • Python applications

  • Python versions

  • PYTHON IN REALTIME INDUSTRY

  • Difference between Python 2.x and 3.x

  • Difference between Python 3.7 and 3.8

  • Software Development Architectures

Python Software’s

  • Python Distributions

  • Download &Python Installation Process in Windows, Unix, Linux, and Mac

  • Online Python IDLE

  • Python Real-time IDEs like Spyder, Jupyter NoteBook, PyCharm, Rodeo, Visual Studio Code, ATOM, PyDevetc

Python Language Fundamentals

  • Python Implementation Alternatives/Flavors

  • Keywords

  • Identifiers

  • Constants / Literals

  • Data types

  • Python VS JAVA

  • Python Syntax

Different Modes of Python

  • Interactive Mode

  • Scripting Mode

  • Programming Elements

  • Structure of Python program

  • First Python Application

  • Comments in Python

  • Python file extensions

  • Setting Path in Windows

  • Edit and Run python program without IDE

  • Edit and Run python program using IDEs

  • INSIDE PYTHON

  • Programmers View of Interpreter

  • Inside INTERPRETER

  • What is Byte Code in PYTHON?

  • Python Debugger

Python Variables

  • bytes Data Type

  • byte array

  • String Formatting in Python

  • Math, Random, Secrets Modules

  • Introduction

  • Initialization of variables

  • Local variables

  • Global variables

  • ‘global’ keyword

  • Input and Output operations

  • Data conversion functions – int(), float(), complex(), str(), chr(), ord()

Operators

  • Arithmetic Operators

  • Comparison Operators

  • Python Assignment Operators

  • Logical Operators

  • Bitwise Operators

  • Shift operators

  • Membership Operators

  • Identity Operators

  • Ternary Operator

  • Operator precedence

  • Difference between “is” vs “==”

Input & Output Operators

  • Print

  • Input

  • Command-line arguments

Control Statements

  • Conditional control statements

  • If

  • If-else

  • If-elif-else

  • Nested-if

  • Loop control statements

  • for

  • while

  • Nested loops

  • Branching statements

  • Break

  • Continue

  • Pass

  • Return

  • Case studies

Data Structures or Collections

  • Introduction

  • Importance of Data structures

  • Applications of Data structures

  • Types of Collections

  • Sequence

  • Strings, List, Tuple, range

  • Nonsequence

  • Set, Frozen set, Dictionary

  • Strings

  • What is string

  • Representation of Strings

  • Processing elements using indexing

  • Processing elements using Iterators

  • Manipulation of String using Indexing and Slicing

  • String operators

  • Methods of the String object

  • String Formatting

  • String functions

  • String Immutability

  • Case studies

List Collection

  • What is List

  • The need of List collection

  • Different ways of creating List

  • List comprehension

  • List indices

  • Processing elements of List through Indexing and Slicing

  • List object methods

  • List is Mutable

  • Mutable and Immutable elements of List

  • Nested Lists

  • List_of_lists

  • Hardcopy, shallow copy and DeepCopy

  • zip() in Python

  • How to unzip?

  • Python Arrays:

  • Case studies

Tuple Collection

  • What is a tuple?

  • Different ways of creating Tuple

  • Method of Tuple object

  • Tuple is Immutable

  • Mutable and Immutable elements of Tuple

  • Process tuple through Indexing and Slicing

  • List v/s Tuple

  • Case studies

Set Collection

  • What is set?

  • Different ways of creating a set

  • Difference between list and set

  • Iteration Over Sets

  • Accessing elements of the set

  • Python Set Methods

  • Python Set Operations

  • Union of sets

  • functions and methods of set

  • Python Frozen set

  • Difference between set and frozenset ?

  • Case study

Dictionary Collection

  • What is a dictionary?

  • Difference between list, set, and dictionary

  • How to create a dictionary?

  • PYTHON HASHING?

  • Accessing values of the dictionary

  • Python Dictionary Methods

  • Copying dictionary

  • Updating Dictionary

  • Reading keys from Dictionary

  • Reading values from Dictionary

  • Reading items from Dictionary

  • Delete Keys from the dictionary

  • Sorting the Dictionary

  • Python Dictionary Functions and methods

  • Dictionary comprehension

Functions

  • What is Function?

  • Advantages of functions

  • Syntax and Writing function

  • Calling or Invoking the function

  • Classification of Functions

    • No arguments and No return values

    • With arguments and No return values

    • With arguments and With return values

    • No arguments and With return values

    • Recursion

  • Python argument type functions :

    • Default argument functions

    • Required(Positional) arguments function

    • Keyword arguments function

    • Variable arguments functions

  • ‘pass’ keyword in functions

  • Lambda functions/Anonymous functions

    • map()

    • filter()

    • reduce()

  • Nested functions

  • Non-local variables, global variables

  • Closures

  • Decorators

  • Generators

  • Iterators

  • Monkey patching

Advanced Python

Python Modules

  • Importance of modular programming

  • What is module

  • Types of Modules – Predefined, User-defined.

  • User-defined modules creation

  • Functions based modules

  • Class-based modules

  • Connecting modules

  • Import module

  • From … import

  • Module alias / Renaming module

  • Built-In properties of the module

Packages

  • Organizing python project into packages

  • Types of packages – pre-defined, user-defined.

  • Package v/s Folder

  • py file

  • Importing package

  • PIP

  • Introduction to PIP

  • Installing PIP

  • Installing Python packages

  • Uninstalling Python packages

OOPs

  • Procedural v/s Object-oriented programming

  • Principles of OOP – Encapsulation, Abstraction (Data Hiding)

  • Classes and Objects

  • How to define a class in python

  • Types of variables – instance variables, class variables.

  • Types of methods – instance methods, class method, static method

  • Object initialization

  • ‘self’ reference variable

  • ‘cls’ reference variable

  • Access modifiers – private(__) , protected(_), public

  • AT property class

  • Property() object

  • Creating object properties using setaltr, getaltr functions

  • Encapsulation(Data Binding)

  • What is polymorphism?

  • Overriding

  1. i) Method overriding

  2. ii) Constructor overriding

  • Overloading

  1. i) Method Overloading

  2. ii) Constructor Overloading

iii)  Operator Overloading

  • Class re-usability

  • Composition

  • Aggregation

  • Inheritance – single , multi level, multiple, hierarchical and hybrid inheritance and Diamond inheritance

  • Constructors in inheritance

  • Object class

  • super()

  • Runtime polymorphism

  • Method overriding

  • Method resolution order(MRO)

  • Method overriding in Multiple inheritance and Hybrid Inheritance

  • Duck typing

  • Concrete Methods in Abstract Base Classes

  • Difference between Abstraction & Encapsulation

  • Inner classes

  • Introduction

  • Writing inner class

  • Accessing class level members of inner class

  • Accessing object level members of inner class

  • Local inner classes

  • Complex inner classes

  • Case studies

Exception Handling & Types of Errors

  • What is Exception?

  • Why exception handling?

  • Syntax error v/s Runtime error

  • Exception codes – AttributeError, ValueError, IndexError, TypeError…

    • Handling exception – try except block

    • Try with multi except

    • Handling multiple exceptions with single except block

  • Finally block

    • Try-except-finally

    • Try with finally

    • Case study of finally block

  • Raise keyword

    • Custom exceptions / User defined exceptions

    • Need to Custom exceptions

  • Case studies

Regular expressions

  • Understanding regular expressions

  • String v/s Regular expression string

  • “re” module functions

  • Match()

  • Search()

  • Split()

  • Findall()

  • Compile()

  • Sub()

  • Subn()

  • Expressions using operators and symbols

  • Simple character matches

  • Special characters

  • Character classes

  • Mobile number extraction

  • Mail extraction

  • Different Mail ID patterns

  • Data extraction

  • Password extraction

  • URL extraction

  • Vehicle number extraction

  • Case study

File &Directory handling

  • Introduction to files

  • Opening file

  • File modes

  • Reading data from file

  • Writing data into file

  • Appending data into file

  • Line count in File

  • CSV module

  • Creating CSV file

  • Reading from CSV file

  • Writing into CSV file

  • Object serialization – pickle module

  • XML parsing

  • JSON parsing

Python Logging

  • Logging Levels

  • implement Logging

  • Configure Log File in over writing Mode

  • Timestamp in the Log Messages

  • Python Program Exceptions to the Log File

  • Requirement of Our Own Customized Logger

  • Features of Customized Logger

Date & Time module

  • How to use Date & Date Time class

  • How to use Time Delta object

  • Formatting Date and Time

  • Calendar module

  • Text calendar

  • HTML calendar

OS module

  • Shell script commands

  • Various OS operations in Python

  • Python file system shell methods

  • Creating files and directories

  • Removing files and directories

  • Shutdown and Restart system

  • Renaming files and directories

  • Executing system commands

Multi-threading & Multi Processing

  • Introduction

  • Multi tasking v/s Multi threading

  • Threading module

  • Creating thread – inheriting Thread class , Using callable object

  • Life cycle of thread

  • Single threaded application

  • Multi threaded application

  • Can we call run() directly?

  • Need to start() method

  • Sleep()

  • Join()

  • Synchronization – Lock class – acquire(), release() functions

  • Case studies

Garbage collection

  • Introduction

  • Importance of Manual garbage collection

  • Self reference objects garbage collection

  • ‘gc’ module

  • Collect() method

  • Threshold function

  • Case studies

Python Data Base Communications(PDBC)

  • Introduction to DBMS applications

  • File system v/s DBMS

  • Communicating with MySQL

  • Python – MySQL connector

  • connector module

  • connect() method

  • Oracle Database

  • Install cx_Oracle

  • Cursor Object methods

  • execute() method

  • executeMany() method

  • fetchone()

  • fetchmany()

  • fetchall()

  • Static queries v/s Dynamic queries

  • Transaction management

  • Case studies

Python – Network Programming

  • What is Sockets?

  • What is Socket Programming?

  • The socket Module

  • Server Socket Methods

  • Connecting to a server

  • A simple server-client program

  • Server

  • Client

Tkinter & Turtle

  • Introduction to GUI programming

  • Tkinter module

  • Tk class

  • Components / Widgets

  • Label , Entry , Button , Combo, Radio

  • Types of Layouts

  • Handling events

  • Widgets properties

  • Case studies

Data analytics modules

  • Numpy

  • Introduction

  • Scipy

  • Introduction

  • Arrays

  • Datatypes

  • Matrices

  • N dimension arrays

  • Indexing and Slicing

  • Pandas

  • Introduction

  • Data Frames

  • Merge , Join, Concat

  • MatPlotLib introduction

  • Drawing plots

  • Introduction to Machine learning

  • Types of Machine Learning?

  • Introduction to Data science

DJANGO

  • Introduction to PYTHON Django

  • What is Web framework?

  • Why Frameworks?

  • Define MVT Design Pattern

  • Difference between MVC and MVT

PANDAS

Pandas – Introduction

Pandas – Environment Setup

Pandas – Introduction to Data Structures

  • Dimension & Description

  • Series

  • DataFrame

  • Data Type of Columns

  • Panel

Pandas — Series

  • Series

  • Create an Empty Series

  • Create a Series f

  • rom ndarray

  • rom dict

  • rom Scalar

  • Accessing Data from Series with Position

  • Retrieve Data Using Label (Index)

Pandas – DataFrame

  • DataFrame

  • Create DataFrame

  • Create an Empty DataFrame

  • Create a DataFrame from Lists

  • Create a DataFrame from Dict of ndarrays / Lists

  • Create a DataFrame from List of Dicts

  • Create a DataFrame from Dict of Series

  • Column Selection

  • Column Addition

  • Column Deletion

  • Row Selection, Addition, and Deletion

Pandas – Panel

  • Panel()

  • Create Panel

  • Selecting the Data from Panel

Pandas – Basic Functionality

  • DataFrame Basic Functionality

Pandas – Descriptive Statistics

  • Functions & Description

  • Summarizing Data

Pandas – Function Application

  • Table-wise Function Application

  • Row or Column Wise Function Application

  • Element Wise Function Application

Pandas – Reindexing

  • Reindex to Align with Other Objects

  • Filling while ReIndexing

  • Limits on Filling while Reindexing

  • Renaming

Pandas – Iteration

  • Iterating a DataFrame

  • iteritems()

  • iterrows()

  • itertuples()

Pandas – Sorting

  • By Label

  • Sorting Algorithm

Pandas – Working with Text Data

Pandas – Options and Customization

  • get_option(param)

  • set_option(param,value)

  • reset_option(param)

  • describe_option(param)

  • option_context()

Pandas – Indexing and Selecting Data

  • .loc()

  • .iloc()

  • .ix()

  • Use of Notations

Pandas – Statistical Functions

  • Percent_change

  • Covariance

  • Correlation

  • Data Ranking

Pandas – Window Functions

  • .rolling() Function

  • .expanding() Function

  • .ewm() Function

Pandas – Aggregations

  • Applying Aggregations on DataFrame

Pandas – Missing Data

  • Cleaning / Filling Missing Data

  • Replace NaN with a Scalar Value

  • Fill NA Forward and Backward

  • Drop Missing Values

  • Replace Missing (or) Generic Values

Pandas – GroupBy

  • Split Data into Groups

  • View Groups

  • Iterating through Groups

  • Select a Group

  • Aggregations

  • Transformations

  • Filtration

Pandas – Merging/Joining

  • Merge Using ‘how’ Argument

Pandas – Concatenation

  • Concatenating Objects

  • Time Series

Pandas – Date Functionality

Pandas – Timedelta

Pandas – Categorical Data

  • Object Creation

Pandas – Visualization

  • Bar Plot

  • Histograms

  • Box Plots

  • Area Plot

  • Scatter Plot

  • Pie Chart

Pandas – IO Tools

  • csv

Pandas – Sparse Data

Pandas – Caveats & Gotchas

Pandas – Comparison with SQL

NUMPY

 NUMPY − INTRODUCTION

NUMPY − ENVIRONMENT

NUMPY − NDARRAY OBJECT

NUMPY − DATA TYPES

  • Data Type Objects (dtype)

NUMPY − ARRAY ATTRIBUTES

  • shape

  • ndim

  • itemsize

  • flags

NUMPY − ARRAY CREATION ROUTINES

  • empty

  • zeros

  • ones

NUMPY − ARRAY FROM EXISTING DATA

  • asarray

  • frombuffer

  • fromiter

NUMPY − ARRAY FROM NUMERICAL RANGES

  • arange

  • linspace

  • logspace

NUMPY − INDEXING & SLICING

NUMPY − ADVANCED INDEXING

  • Integer Indexing

  • Boolean Array Indexing

NUMPY − BROADCASTING

NUMPY − ITERATING OVER ARRAY

  • Iteration

  • Order

  • Modifying Array Values

  • External Loop

  • Broadcasting Iteration

NUMPY – ARRAY MANIPULATION

  • reshape

  • ndarray.flat

  • ndarray.flatten

  • ravel

  • transpose

  • ndarray.T

  • swapaxes

  • rollaxis

  • broadcast

  • broadcast_to

  • expand_dims

  • squeeze

  • concatenate

  • stack

  • hstack and numpy.vstack

  • split

  • hsplit and numpy.vsplit

  • resize

  • append

  • insert

  • delete

  • unique

NUMPY – BINARY OPERATORS

  • bitwise_and

  • bitwise_or

  • invert()

  • left_shift

  • right_shift

NUMPY − STRING FUNCTIONS

NUMPY − MATHEMATICAL FUNCTIONS

  • Trigonometric Functions

  • Functions for Rounding

NUMPY − ARITHMETIC OPERATIONS

  • reciprocal()

  • power()

  • mod()

NUMPY − STATISTICAL FUNCTIONS

  • amin() and numpy.amax()

  • ptp()

  • percentile()

  • median()

  • mean()

  • average()

  • Standard Deviation

  • Variance

NUMPY − SORT, SEARCH & COUNTING FUNCTIONS

  • sort()

  • argsort()

  • lexsort()

  • argmax() and numpy.argmin()

  • nonzero()

  • where()

  • extract()

NUMPY − BYTE SWAPPING

  • ndarray.byteswap()

NUMPY − COPIES & VIEWS

  • No Copy

  • View or Shallow Copy

  • Deep Copy

NUMPY − MATRIX LIBRARY

  • empty()

  • matlib.zeros()

  • matlib.ones()

  • matlib.eye()

  • matlib.identity()

  • matlib.rand()

NUMPY − LINEAR ALGEBRA

  • dot()

  • vdot()

  • inner()

  • matmul()

  • Determinant

  • linalg.solve()

NUMPY − MATPLOTLIB

  • Sine Wave Plot

  • subplot()

  • bar()

NUMPY – HISTOGRAM USING MATPLOTLIB

  • histogram()

  • plt()

NUMPY − I/O WITH NUMPY

  • save()

  • savetxt()

IoT Training

IoT Training

Internet of Things (IoT) Training Overview:

This IoT Training is provided by Real-Time Expert with in-depth analysis and real-time examples. The IoT  (Internet of Things) Used to enable the Collection and Exchanging the Data between the Connected Devices, Smart Devices, sensors, software, and Other things embedded with electronics. Attend a free demo by real-time experts and join IoT Course today…

Introduction

  • What is IoT?

  • How IoT is applied in different domains?

  • Use cases ranging from Smart Cities to IIoT

  • How large is the IoT Market in different domains?

IoT Architecture

  • IoT Technology stack

  • Sensors & Actuators

  • Hardware Platforms

  • Wireless Communication Protocols

  • Network communication Protocols

  • Cloud, its components, and IoT

  • Data Streaming in IoT

  • Data Store and IoT

  • Analytics & Visualization for IoT

Sensor & Actuator

  • What is Sensor & Actuator?

  • What is a good sensor?

  • Sensor properties and their classification

  • Types of Sensors & Actuators

  • Working of typical Sensors and Actuators

  • Categories of sensors Commercial/Industrial/Military/Medical/Food grade sensors

  • Selecting a sensor for your use case

  • IoT Hardware Platform & comparison

  • Criteria for selecting a Hardware platform

Raspberry Pi and Arduino Hardware Overview

  • The Raspberry Pi and Arduino Open Source Microcontroller Platform

  • Schematics, PCB Design Tools and prototype steps

  • Raspberry Pi and Arduino Board Layout & Architecture

  • Why Raspberry Pi and Arduino?

Arduino Programming fundamentals

  • How to program Arduino with Arduino IDE

  • How to make your Arduino respond to sensors and actuators

  • Reading data from analog/Digital Sensors

  • Writing data to analog (PWM)/Digital actuators

Interfacing Sensors and Actuators with Hardware

  • Connecting sensors to Arduino to read data from sensor and display on serial monitor (Temperature, Humidity, Distance, Light, Moisture, Gas (Methane/Alcohol), Proximity, Motion).

  • Connecting actuator to Arduino and controlling Actuator (LED, Relay, Pushbutton, Buzzer) Controlling a motor (actuator) by sensing Temperature

  • Controlling a buzzer using Ultrasonic ranger

  • PIR (Human presence) (Combining sensors to avoid false alarms)

  • Controlling sprinklers using relay by sensing the moisture in the soil using a moisture sensor

Program Raspberry Pi board

  • Working with Raspberry Pi 3 Model

  • Installing OS and Designing Systems using Raspberry pi

  • Configuring Raspberry Pi for VNC Connection

  • Getting introduced to Linux OS

  • Basic Linux commands and uses

  • Getting Started with Python

  • Variables, Functions, and control Structure

  • File Handling in Python & Importing or Exporting Data

  • Interface sensor and Actuator with Raspberry Pi.

IoT Communication Protocol

IoT Wireless Protocols

  • RFID, NFC, Blue Tooth, BLE, ZigBee, Zwave Mesh network

  • Comparison of Wireless Protocols

  • How to select a wireless Protocol based on the use case

IoT Communication Channels

  • Wi-Fi, GSM/GPRS, 2G, 3G, LTE

  • Comparison of Communication Channels

  • How to select a Communication Channels based on Use Case

IoT Network Protocols

  • MQTT/MQTTS, CoAP, 6LoWPAN, TCP, UDP, HTTP/s

Comparison of the Network protocols

  • How to select a Network Protocol based on Use Case

Introduction to IPv4 and IPv6

  • Issues with IPv4 in IoT

  • How IPv6 solves the issues with IPv4

  • Application issues with RF protocol

  • power consumption, LOS, reliability, Security aspects

TCP/UDP Transport layer Protocol

  • Introduction of TCP & UDP

  • Difference between TCP/UDP Transport layer protocol

  • Practically testing the TCP v/s UDP by python socket programming

HTTP Application layer IoT Protocol

  • Introduction and structure of HTTP protocol

  • Start with HTTP protocol GET/POST Method

  • Work on Python Flask library design web page

  • Control thing from the webpage using the HTTP protocol

  • Publish sensor data over the webserver

MQTT IoT Protocol

  • Introduction to MQTT

  • Why MQTT?

  • Features of MQTT

  • MQTT Subscribe/Publish

  • MQTT Broker

  • MQTT QoS

  • MQTT Security

MQTT with Raspberry Pi

  • Installation of Mosquito MQTT broker

  • Publish and Subscriber test on local server broker

  • Start with Paho MQTT

  • Publish/subscribe test on iot.eclipse platform

CoAP IoT Protocol

  • Introduction of CoAP

  • The architecture of the CoAP IoT protocol

  • Difference between HTTP & COAP

  • Implement CoAP using CoAPthon Python library

  • Design server and client using Python

IoT Cloud Platform(Ubidot)

  • Read data from sensors,

  • Create JSON Object

  • Establish HTTPS connection using Wi-Fi

  • Send JSON data to Ubidot Rest API over HTTPS

  • Create business rules in Ubidot for alarms

  • Send Data to Ubidot platform

  • Create a rule and configure an Alarm(SMS/Email) for your device

  • Send data to Ubidot which will trigger the alarm

  • Create and configure Chart/Graph for visualization

  • Control the actuator from Ubidot using a polling technique

 Theory Introduction to the Big Data and Big data technologies

Cloud Computing

  • What is the cloud?

  • What is cloud computing?

  • Benefits of the cloud.

  • Deployment Models.

  • Top cloud providers.

  • Service Models

  • Service Catalogue

  • Advantages for different offerings

  • Introduction to AWS

  • Service provided by AWS E2C, SimpleDB RDS, Dynamo DB, Elastic Beanstalk, SNS, Cloud Watch, Route 53, VPC, Elastic Load Balancing, S3, EBS, IAM

BigData

  • Cloud data storage

  • Introduction to Big Data

  • BigData Definition and Characteristics

  • Who is Generating Big Data

  • Big Data Analytics

  • Why Big Data Analytics

  • Applications of Big Data Analytics

  • Different Data Stores

  • Big Data Technologies CouchDB, MongoDB, Node4J

AWS IoT Setup for Application Development

  • Introduction to AWS IoT

  • Creating a Thing in AWS IoT

  • Downloading SDK and configuring RaspberryPi

Preparing the RaspberryPi to connect to AWS IoT

  • Downloading Certificates from AWS IoT console

  • Installing certificate in RaspberryPi

  • Connecting Sensors to RaspberryPi II.

Connecting to AWS IoT

  • Configuring RaspberryPi sketch to connect to AWS IoT through Wi-Fi

  • Establishing MQTT Connection

  • Publishing Sensor data to AWS IoT Thing Shadow

  • Subscribing MQTT Topic and controlling actuator from Thing shadow

Send Data from raspberry Pi to AWS IoT

  • Run Ultrasonic ranger sketch in RaspberryPi and check

  • Updating of data from RaspberryPi to AWS Thing Shadow

Dynamo DB

  • Configuration of Dynamo DB

  • Create a table in Dynamo DB

  • Create rule link dynamo DB with AWS IoT

  • Store sensor data From AWS IoT in Dynamo DB

SNS

  • Setup SNS service

  • Test SNS service by publishing/subscribe

  • Create a rule and link with AWS IoT

  • Notify through mail when Publisher publish data

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