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
  • Infrastructure as a Service
  • Other XaaS's

Cloud Deployment Models

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


  • 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)


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


  • 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 Merit 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: It's a basic level workshop so there are no prerequisites. Any one interested, can join this workshop.

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