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29 Jun 2020

Five days Online FDP on Data Science and Docker Technology

Resource Person : 1. Namasivayam Chockalingom
Designation – Enterprise application analyst
Companny – Fiserv

2. Girish Y T
Role: Programmer/Analyst.
Campany: NetApp india pvt ltd

Date : 29th June to 3rd July 2020

Time : 11:00 AM

Organized by : Department of CSE

Registration Link:

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About the Program

Department of Computer Science and Engineering has organized 5 Day Faculty Development Program (FDP) on “Data Science and Docker Technology” from 29th June to 3rd July 2020. Dr .V Mareeswari in her speech addressed all the audience by her precious words. She started with the evolution of computer hardware and software. She continued to revise the change in technology and its importance. Later she discussed the needs of latest programming languages such as Python, R-programming etc. And the later session was continued by Mr. Namasivayam Chockalingom, Enterprise Application Analyst, Fiserv, who started the FDP with the basics of Data Science.

About the FDP:-

The vision of this FDP is to enhance the quality of education imparted in institutions by providing faculty members with a platform to learn all they need to know about Data Science and Docker Technology. Educators will get to learn the best practices in these domains so that they can teach the future workforce the required skill sets.

Data Science:-

An interdisciplinary field, data science deals with processes and systems that are used to extract knowledge or insights from large amounts of data. Data extracted can be either structured or unstructured. Data science is a continuation of data analysis fields like data mining, statistics, predictive analysis. A vast field, data science uses a lot of theories and techniques that are a part of other fields like information science, mathematics, statics, chemometrics and computer science. Some of the methods used in data science include probability models, machine learning, signal processing, data mining, statistical learning, database, data engineering, visualization, pattern recognition and learning, uncertainty modeling, computer programming among others. With advancements of so much of data, many aspects of data science are gaining immense importance, especially big data. Data science is not restricted to big data, which in itself is a big field because big data solutions are more focused on organizing and pre-processing the data rather than analyzing the data. In addition, machine learning has enhanced the growth and importance of data science in the last few years. Data has real value and every information extracted from it can make or break businesses. Analytics is the intersection of business and data science, offering new opportunities for a competitive advantage. It unlocks the predictive potential of data analysis to improve financial performance, strategic management, and operational efficiency. Data analytics can lead to valuable insights that can determine leads to increase sales, fraud detection, pattern recognition and risk prediction in various domains. As part of this initiative, a Faculty Development Programme (FDP) is conducted to focus on the fundamentals of data science with hands-on sessions on every topic handled using python.


Docker is an open platform for developing, shipping, and running applications. Docker enables you to separate your applications from your infrastructure so you can deliver software quickly. With Docker, you can manage your infrastructure in the same ways you manage your applications. By taking advantage of Docker’s methodologies for shipping, testing, and deploying code quickly, you can significantly reduce the delay between writing code and running it in production.


The principal purpose of Data Science is to find patterns within data. It uses various statistical techniques to analyze and draw insights from the data. From data extraction, wrangling and pre-processing, a Data Scientist must scrutinize the data thoroughly. And Docker is a set of platform as a service product that uses OS-level virtualization to deliver software in packages called containers. Containers are isolated from one another and bundle their own software, libraries and configuration files; they can communicate with each other through well defined channels.

Program Schedule:-

Day and Date

Course Contents

Day1: Monday, 29/6/2020

EMV tokenization, Data Science analyst

Day2: Tuesday, 30/6/2020

The Challenge: Matrix from hell

Day 3: Wednesday, 01/7/2020

Containers and Docker, Docker Installation, Docker Architecture, Docker Images, Containerizing an Application

Day 4: Friday, 02/7/2020

Docker Networking, Docker Compose, Case Study

Day 5: Saturday, 03/7/2020

Assignment Session