Industry 4.0 Workhop

Industry 4.0 is the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of things and cloud computing. Industry 4.0 creates what has been called a "smart factory".

Topics to be covered in Workshop

Introduction to Industry 4.0

Introduction to Cloud Computing 

• A short history
• Client Server Computing Concepts
• Challenges with Distributed Computing
• Introduction to Cloud Computing
• Why Cloud Computing?
• Benefits of Cloud Computing

 Networking Basics

• Understanding Networking Concepts
• TCP/IP
• Application Protocols
• Understanding Linux Files and Network Tooling
• ifconfig
• dig
• ping
• traceroute
• netstat
• tcpdump
• resolv.conf
• ssh
• scp/rsync

Characteristics of Cloud Computing

• API based access
• Cost
• Device independence
• Virtualization
• Multitenancy

Types of Cloud Computing

• Software as a Service
• Platform as a Service
• CLOUD COMPUTING – BASIC AND ADVANCED
• Infrastructure as a Service
• Other XaaS's

Cloud Deployment Models

• Public Cloud
• Private Cloud
• Hybrid Cloud
• When to choose what?

Virtualization

• Introduction to Virtualization
• Role of Virtualization in Cloud Computing
• Types of Virtualization
• Examples of Virtualization
• Benefits of Virtualization
• Amazon Web Services (AWS)
• Introduction to the AWS products
• Amazon Elastic Compute Cloud (EC2)
• Amazon Simple Storage Service (S3)

BigData/Hadoop

What is Big Data & Why Hadoop?

• What is Big Data? 
• Traditional data management systems and their limitations 
• What is Hadoop? 
• Why is Hadoop used? 
• The Hadoop eco-system 
• Big data/Hadoop use cases 

HDFS (Hadoop Distributed File System) 

• HDFS Architecture 
• Namenode memory concerns 
• Secondary namenode 
• Basic Hadoop commands 

PIG and HIVE Programming

Data Science

Introduction to R

• History of R
• An Insight into R
• Data Structure and Data Type

Data Management and Data Cleaning

• Missing Value Treatment
• Outlier Treatment
• Sorting Datasets
• Merging Datasets
• Creating new variables
• Binning variables
• Reading datasets from other environments into R ( importing )
• Writing datasets from R environment to other environments (exporting ) 

Data Visualization in R 

• Bar Chart
• Dot Plot
• Scatter Plot ( 3D )
• Spinning Scatter Plots
• Pie Chart
• Histogram ( 3D ) [including colourful ones ]
• Overlapping Histograms
• Boxplot
• Plotting with Base and Lattice Graphics

 IOT (NODE RED) 

• A brief introduction to Node-RED 
• Building your first flows 
• Basic nodes and flows  A tour of the core nodes 
• The Node-RED programming model 
•  Intermediate flows 
• Dashboards and UI techniques.  
• Node-RED, the cloud and IoT platforms 
• Advanced flows  

Duration: The duration of this workshop will be two consecutive days, with eight hour session each day in a total of sixteen hours properly divided into theory and hands on sessions.

Certification Policy:

• Certificate of Participation for all the workshop participants.
• At the end of this workshop, a small competition will be organized among the participating students and winners will be awarded with a 'Certificate of Excellence'.
• Certificate of Coordination for the coordinators of the campus workshops.

Eligibility: There are no prerequisites. Anyone interested, can join this workshop.