Workshop

We provide all-round approach in training in the background from Electronics to Computer Science. We teach you here to thrive not to survive. Comparing wouldn’t make any difference rather pushing up to the level where people admire you is our moto.

Topics

dataScience
machineLearning
cloudcomputing
BigData
Blockchain
gameDevelopment
imageProcessing
android
Iot
EmbeddedSystems
ArtificialIntelligence
Python
cybersecurity
dataScience
machineLearning
cloudcomputing
BigData
Blockchain
gameDevelopment
imageProcessing
android
Iot
EmbeddedSystems
ArtificialIntelligence
Python
cybersecurity

Two Days Workshop Content

Day 1 -(Session 1)/ 6-8 Hours

Section A : What is Data and Data Science?
  • AI vs ML vs DL vs Data Science
  • Data Science Scope, Applications
  • Data Science Introduction
  • Predictive v/s Descriptive Data Analysis
  • Data Science v/s Data Analytics
  • Regression & Classification Problems
  • What makes a Data Science Expert?
  • The art of making stories from Data
  • Use Cases and Case Studies
  • Critical success drivers
  • Why Python for data science?
Section B : Introduction of Python
  • Overview of Python- Starting with Python
  • Introduction to installation of Python
  • Understand Jupyter notebook & Customize Settings
  • Installing & loading Packages & Name Spaces
  • Variable & Value Labels – Date & Time Values
  • Basic Operations - Mathematical - string – date
  • Debugging & Code profiling
Section C : Data Science Fundamentals
  • Data Exploration
  • Visualization
  • Feature Engineering
  • Tools :R/Python
Section D : Data Analysis and visualization using Python
  • Introduction exploratory data analysis
  • Descriptive statistics, Frequency Tables and summarization
  • Univariate Analysis
  • Bivariate Analysis
  • Creating Graphs- Bar/pie/line chart/histogram/ boxplot/ scatter/ density etc

Day 2 -(Session 2)/ 6-8 Hours

Section A : Data Preparation
  • Need of Data preparation
  • Consolidation/Aggregation - Outlier treatment
  • Variable Reduction Techniques - Factor & PCA Analysis
Section B : Unsupervised Learning
  • What is segmentation & Role of ML in Segmentation?
  • Concept of Distance and related math background
  • K-Means Clustering
  • Expectation Maximization
  • Spectral Clustering
  • Principle component Analysis
Section C : Supervised Learning
  • Decision Trees - Introduction – Applications
  • Types of Decision Tree Algorithms
  • Construction of Decision Trees through Simplified Examples
  • Generalizing Decision Trees
  • Pruning a Decision Tree; Cost as a consideration; Unwrapping Trees as Rules
  • Decision Trees – Validation
Section D : Text Mining & Analytics
  • Taming big text, Unstructured vs. Semi-structured Data
  • Finding patterns in text: text mining, text as a graph
  • Natural Language processing (NLP)
  • Text Analytics – Sentiment Analysis using Python
  • Text Analytics – Word cloud analysis using Python

Day 1 -(Session 1)/ 6-8 Hours

Section A : Introduction to Machine Learning
  • Introduction to ML
  • Applications of Machine Learning
  • Supervised vs Unsupervised Learning
  • Python libraries suitable for Machine Learning
  • Role of Python and R programming in this domain
Section B : Basic of Python programming
  • Basic of python and why python for machine learning
  • Extracting data from a file
  • Function and module
  • Creating own modules / library
Section C : Introduction to Numpy & Matplotlib
  • Managing array with numpy
  • Multidimensional array with numpy
  • Unit matrix handling & creating
Section D : Regression
  • Linear Regression
  • Non-linear Regression
  • Model evaluation methods

Day 2 -(Session 2)/ 6-8 Hours

Section A : Introduction to iris Datasets
  • Understanding iris datasets
  • Separating data with numpy
  • Training classifier
  • Algo data process view
  • Decision Tree understanding
Section B : Unsupervised Learning
  • K-Means Clustering
  • Hierarchical Clustering
  • Density-Based Clustering
Section C : Projects:
  • Online/offline SMART Chatting Machine .
  • Face and expression recognition

Day 1 -(Session 1)/ 6-8 Hours

Section A : Introduction to Cloud Computing
  • What is the cloud?
  • History of Cloud Computing
  • How Cloud Computing Works
  • Advantages & Disadvantages
  • Applications for Businesses
  • Cloud Service Providers
Section B : What makes a cloud?
  • Storage Virtualization
  • Application virtualization
  • Server virtualization
  • Network virtualization
Section C : Hands-on demonstration of cloud computing
  • Creating an account on the cloud
  • Starting a server instance
  • Allocating storage and other resources
  • Deploying an application
Section D : Project
  • Cloud Architectures
  • Building Enterprise Cloud Computing Environment using a Network of Compute

Day 2 -(Session 2)/ 6-8 Hours

Section A : Cloud Computing Service Models
  • Infrastructure as a Service (IAAS)
  • Platform as a Service (PAAS)
  • Software as a Service (SAAS)
Section B : Cloud computing deployment models
  • Public Cloud
  • Private Cloud
  • Community Cloud
  • Hybrid Cloud
Section C : Data Center
  • Routing to the Data Center
  • Switching within the Data Center
Section D : Cloud providers and their offerings
  • Amazon
  • Microsoft
  • Google
  • Salesforce.com
  • Administering the Cloud
Section E : Projects
  • Application Case Studies in Engineering, Image Processing, and Media Rendering
  • Platform for building Clouds and their Innovative Application
  • Cloud Computing Platforms

Day 1 -(Session 1)/ 6-8 Hours

Section A : Introduction to Big data
  • What is Big data?
  • Black Box Data
  • Social Media Data
  • Stock Exchange Data
  • Power Grid Data
  • Transport Data
  • Search Engine Data
  • Benefits of Big data
Section B : Introduction to Big data Technology
  • Operational Big data
  • Analytical Big data
Section C : Introduction to Hadoop
  • What is Hadoop
  • Why is Hadoop
  • Difference between Hadoop and Traditional Approach
  • Hadoop Architecture
  • Hadoop Common
  • Hadoop yarn
  • HDFS
  • Hadoop Map Reduce
Section D : Introduction to Hbase
  • What is Hbase
  • Basic of Hbase
  • Need of Hbase
  • Purpose of Hbase

Day 2 -(Session 2)/ 6-8 Hours

Section A : Model of Hbase
  • Hbase Data Model
  • Hbase Read and Write
  • RDBMS and Hbase
  • Hbase Commands and example
Section B : Introduction to Data Analytics
  • What is Data Analytics
  • Types of Data Analytic
  • Descriptive Analytics
  • Diagnostic Analytics
  • Predictive Analytics
  • Prescriptive Analytics
  • Data Analytics Benefits Decision-Making
  • Data Analytics Benefits: Cost Reduction0
  • Data Analytics Benefits: Amazon Example
  • Data Analytics: Other Benefit
  • Key Takeaway
Section C : Dealing with Different type Data
  • Terminologies in Data Analytics
  • Types of Data
  • Qualitative and Quantitative Data
  • Data Levels of Measurement
  • Normal Distribution of Data
  • Statistical Parameters
Section D : Projects
  • Bitmap Based Encrypted Query Processing and Distributed Index Structure for Outsourcing Mobile Sensitive Data
  • Survey Large Scale Data Analytics Performance Using Disk Based and In-Memory Database Systems

Day 1 -(Session 1)/ 6-8 Hours

Section A : Introduction of Block Chain
  • Understanding Block Chain
  • Block chain Concepts
  • Block chain Features
  • Public VS private Block chain
  • Security of Block Chain
  • Block Chain Use Cases
Section B : Introduction of Cryptography
  • Crypto Currency
  • Basics of Cryptography
  • Smart Contract
  • Laws for cryptocurrency
Section C : Layers of a Block chain
  • Data Layer
  • Network Layer
  • Consensus Layer
Section D : Project
  • Securing the Supply Chain System
  • Industry – Logistics

Day 2 -(Session 2)/ 6-8 Hours

Section A : Development of Block Chain
  • Block chain Developing Client
  • Block chain Client Class
  • Block chain Transaction Class Creating Multiple Transactions
  • Block chain Block Class Creating Genesis Block Creating Block chain
  • Block chain Adding Genesis Block Creating Miners
  • Block chain Adding Blocks
Section B : Bitcoin Mining
  • Understand Economics of Bitcoin Define Bitcoin Mining
  • Describe Fabrication of a Block Header
  • Mining and consensus
  • Autonomous verification of mining
  • Independent verification of mining
Section C : Project
  • Auctioning of Rare Artifacts

Day 1 -(Session 1)/ 6-8 Hours

Section A : Introduction to Game Development
  • Physics involved in Game Development
  • Introduction to Unity
  • JavaScript for Unity
  • Controlling Characters
  • Developing a game using the above tools
  • Live demonstration and examples
  • 3D modelling
  • Animating the game character
  • Creating an environment for their game character
  • Scripting of the game character and the various objects in the Game
  • Creating a Finite State Machine
  • Code Optimization
  • Debugging
Section B : Development of 2D Game
  • Core gameplay
  • Editor setup
  • Single sprite configuration w/ colliders, Sprite sheet animations
  • Animator, Keyframed animations, Scripted animations
  • Player character
  • Win and lose settings
  • Collectibles
  • Publishing
  • And new Unity Editor capabilities and features like:
  • New Sprite Editor tools
  • Tilemap system
  • Cinemachine
  • Sprite masking system

Day 2 -(Session 2)/ 6-8 Hours

Section A : Development of 3D Game
  • Core gameplay
  • Character model, Character setup
  • Animation, Animator setup
  • Platform system
  • Lose settings
  • Collectibles
  • Publishing
  • And new Unity Editor capabilities and features like:
  • Cinemachine camera
Section B : Mobile Game Development
  • Distinguish features that enable mobile deployment versus other platforms
  • Navigate in the Unity Editor to create a simple mobile game
  • Use the Unity 2D toolset to set up characters and scenes
  • Create in-editor animations to generate animations for scene elements and the character
  • Build 2D game mechanics that enable mobile gameplay
  • Plan for using services to improve long term game play and build mobile monetization and business strategies
  • Prepare for mobile deployment

Day 1 -(Session 1)/ 6-8 Hours

Section A : Intro to Image Processing
  • What is an image?
  • What is Image Data
  • Image Processing Toolbox
  • Importing Image
  • How to build a matrix image
  • Image Display
  • Image Operations
  • Image Conversion
  • 3 steps of IP
  • Image as a matrix
  • Phrases of IP
  • Types
  • Application
Section B : Software Installation
  • Python Installation
  • Intro to OpenCv and python
Section C : Intro to numpy
  • Array and slicing
Section D : Image Basics with OpenCv
  • Load an Image and read conversion
  • Resizing
  • Flip
  • Display in windows
  • Draw using mouse
  • Draw rectangle
  • Color mapping

Day 2 -(Session 1)/ 6-8 Hours

Section A : Image Arithmetic
  • Adding Images
  • Subtracting Images
  • Multiplying Images
  • Dividing Images
  • Spatial Transformation
  • Resizing Images
  • Rotating Images
  • Cropping Images
Section B : Intro to Video Basics
  • Connect webcam
  • BW and color
  • Save video
  • Load video
  • Human speed playing video
  • Draw rectangle on video
  • Draw rectangle on live camera
Section C : Object detection
  • Template matching
  • Face detection

Day 1 -(Session 1)/ 6-8 Hours

Section A : Introduction to Android
  • Introduction to Android
  • History of Android
  • Android SDK
  • Android Studio
Section B : Basic of Java Programming Language
  • Introduction to Basic of java Programming
  • Feature of Java
  • Oops Concepts
  • Java Data type
  • Java Control Statement
  • Arrays
Section C : Core Topics of Android
  • Build First App
  • App Fundamentals
  • App Resources
  • App Manifest File
  • App Permissions
Section D : Core Topics of Android
  • Activities
  • Activity Lifecycle
  • Intents and intent filters
  • User Interface
  • Layouts
  • Widgets
  • Content Providers
  • Web View
  • Internet Connectivity
  • JSON and JSON parsing
  • Image and Media

Day 2 -(Session 2)/ 6-8 Hours

Section A : Advanced Topics of Android
  • Google MAPs SDK
  • Mobile Number OTP verification
  • Social Site integration – Facebook , Google etc.
  • Testing and Debugging
  • Firebase Authentication
Section B : Projects
  • Android Food order and delivery app
  • Android College Attendance System
  • Library Management System with SMS Autoreply

Day 1 -(Session 1)/ 6-8 Hours

Section A : Introduction to IoT & Raspberry_Pi
  • What is IoT
  • Historical Background, Features, Applications & Scope of Raspberry_Pi
  • Raspberry_Pi & its Various OS
  • Introduction to Raspbian
Section B : Basics of Python Programming
  • Features of Command Window & Script Window
  • Basic Python Commands & Keyboard Shortcuts
  • Defining Editing and Clearing Variables & Checking for Existence
  • My First Python Progra
Section C : High Level Programming and its Easy Interaction
  • Introduction to Arrays
  • Python Data Types and Basic I/O operations
  • Various Python Functions & their use
  • Creating & running User defined Functions
Section D : Project
  • ATM Machine Prototype
Section E : Getting Started with Raspberry_Pi
  • Raspbian – A Debian Derivative
  • The Concept of Open Source
  • Disk Fragmentation
  • Installing & Starting Raspberry_Pi
  • Understanding the Raspberry_Pi Desktop Layout
  • Command Window (Terminal), Editor Window, Workspace, Command
  • History, Graphic Window
Section F : Controlling I/O’s
  • Accessing GPIO Pins
Section G : Programming on Raspberry_Pi
  • Glowing multiple different pattern LED
  • Wide description about Software and Hardware Concerns of AI
  • Machine Learning and data interpretation
  • Introduction to Data Science
  • Memory Elements and Data Acquisition/Calling
  • Programming Languages used in AI

Day 2 -(Session 2)/ 6-8 Hours

Section A : Ultrasonic Sensor
  • Concept, Capabilities & limitations.
  • Applications
  • Practical: Interfacing Ultrasonic Sensor with Pi
Section B : Relays
  • Definition, Working Methodology,
  • Types, Advantages & Application Areas
  • Switching/Controlling of DC Relay using Pi
  • Practical: Interfacing Relay with AVR
Section C : IOT over cloud
  • What is cloud?
  • What are the features & scope of using IOT over cloud?
  • Data connectivity of IoT devices with open cloud.
  • Development of various applications in IoT.
Section D : Working with API
  • What is API
  • How to use API with Python
  • Controlling Raspberry_Pi with API
  • Practical: Smart parking system using IoTWhat is cloud?
  • What are the features & scope of using IOT over cloud?
  • Data connectivity of IoT devices with open cloud.
  • Development of various applications in IoT.
Section E : Projects
  • Distance measurement of an object using ultrasonic sensor
  • Seminar/Conference Hall Automation
  • IoT device for accident detection
  • IoT Controlling through Smart Phone over Wifi
  • Worldwide Accessing and controlling of IoT automation over Internet

Day 1 -(Session 1)/ 6-8 Hours

Section A : Introduction to Embedded System
  • Introduction to automation.
  • Future aspects.
  • Need of Microcontrollers in Robotics.
  • Wide description about Microcontrollers.
  • Input & Output peripherals in Microcontrollers.
  • Registers in Microcontrollers.
  • Programming of Microcontrollers.
Section B : Kits Distribution- Practical session
  • Interfacing of peripherals.
  • Output devices interfacings.
  • Programming for LED interfacing with Microcontrollers.
  • Display device introduction and Interfacing
  • Introduction to LCD.
  • Interfacing of LCD with Microcontroller.
  • Practical: Character, string and number display on LCD.
Section C : Relay Interfacing
  • Introduction to relay.
  • Types of relay and its working.
  • Introduction to ULN2803 IC.
  • Interfacing between controller and ULN2803.
Section D : Project
  • Digital clock on LCD
  • Development of an automation system

Day 2 -(Session 2)/ 6-8 Hours

Section A : IR Sensor
  • Working principle and concept
  • Interfacing of IR with Controller
Section B : Introduction to ADC
  • Accessing internal ADC of microcontroller.
  • Programming for analog to digital converter.
Section C : Introduction to LDR (Light Sensor) sensor
  • Introduction of LM 358 IC.
  • Interfacing of LDR sensor with Atmega8.
Section D : Touch Screen
  • Wide description of Touch screens.
  • Different type of touch screens.
  • Interfacing of Resistive Touch Screen with microcontroller
Section E : Projects & Practicals
  • Practical: displaying x & y axis touch values on LCD.
  • Co-ordinate distribution in touch panel.
  • Practical: Touch Screen control LED.
  • Project: Touch Screen control Home/office automation.

Day 1 -(Session 1)/ 6-8 Hours

Section A : Artificial Intelligence
  • Introduction of Artificial Intelligence
  • What is AI
  • History
  • Use Cases
  • Future Aspects of AI
  • Applications of Machine Learning
Section B : Introduction of Python Programming
  • Environment Setup
  • Setting up Software Installation
  • Installing Libraries
  • Basic of python
  • Oops Concept
  • Modules in Python
Section C : Introduction about API and Its Use
  • How API works in AI
  • Types of API in AI
Section D : Different forms of learning in Artificial Intelligence
  • Supervised Learning Introduction & Examples
  • Unsupervised Learning Introduction & Examples
  • Linear Regression & implementation
  • Introduction to Gradient Descent Algorithm
  • Linear Algebra review

Day 2 -(Session 2)/ 6-8 Hours

Section A : Neural Network in Artificial Intelligence
  • Introduction to Neuron
  • Introduction to Network Architecture
  • Designing Neural Network Model
  • Model Representation Methods
  • Single Layer Neural Network
  • Multilayer Neural Network Architecture
  • Training the Network
  • Backward Propagation Training
  • Importing & Exporting Network
  • Importing & Exporting Training Data
  • Introduction to Dynamic Neural Network
  • Neural Network Blocks in Simulin
Section B : Introduction of NLP
  • Basic uses of NLP in AI
  • Lexical Analysis
  • Syntactic Analysis
  • Semantic Analysis
  • Pragmatic Analysis
Section C : Projects
  • Case Study-Cancer Detection
  • Case Study- Case Study: Character Recognition

Day 1 -(Session 1)/ 6-8 Hours

Section A : Introduction to Python
  • What is Python?
  • What is future Scope?
  • Application Areas, Features, Advantages
  • Understanding the Command Window and Script Window
  • Environment Setup
Section B : Basic Concept of Python Programming Language
  • IDLE for Compiling & Running program
  • Basic Data Types and Assignments
  • Identifiers and Indentation
  • Data Operations
Section C : Introduction to Class of data Structure
  • Sequence Types, Tuples , Lists
  • Operators and Expressions
  • Dictionary and Sets
  • Variable Scope – Global, local and Non Local
Section D : Decision Making and Loop
  • Single Loop Statement
  • Loops
  • Loop Control Statements
  • Iterator and Generator
  • Defining a Function and Syntax
  • Calling a Function

Day 2 -(Session 2)/ 6-8 Hours

Section A : Emailing through Server
  • Configuring Pi for SMTP protocol
  • Connecting Pi to the internet
  • Allowing security to the email account
  • Sending mail to the recipient
Section B : Projects
  • Making your own Atm System
  • Accessing data stored MsExcel

Day 1 -(Session 1)/ 6 Hours

Section A :Introduction Cyber Security
  • Introduction to Ethical Hacking
  • Information Gathering
  • Attacks
  • Networking and Basics
  • Scanning
  • Computer Forensics-an Introductio
Section B : Basic Concept of Cyber Security
  • Own Viruses
  • Road sign hacking and Identify Theft
  • Google Hacking & Countermeasures
  • Stenography
  • SMS Forging
  • Call Forging

Day 2 -(Session 2)/ 6 Hours

Section A
  • Cryptography
  • Web Hacking and Counter Measures
  • Firewalls-An Introduction
  • Facebook Messenger Hacking
  • Password Cracking
  • Email Hacking
  • Whatsapp Hacking
  • LAN Hacking
  • Backtrack OS
Section B
  • Sniffing
  • Linux Hacking
  • D-Dos Attack
  • Trojans
  • DNS-Poisoning
  • Social Networking Sites Protection
  • WIFI Hacking
  • SQL Injection

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