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One day in Python: Applications in Life Science
Where: Innoplexus
7th Floor, Midas Tower,
Beside STPI Building, Rajiv Gandhi Infotech Park,
Phase-1, Hinjewadi, Pune
When: Saturday, 23rd February 2019, At : 10:00 am to 5:30 pm
About the workshop
Why Python……?
Python is a great way to start your programming journey. It is an awesome language for working with
Big Data and use when sorting data sets and analyzing trends. It has a readable syntax, it is object
oriented, and it is used on the backend of lot of cool web apps like Youtube, Google, and Pinterest.
Why Innoplexus….?
At Innoplexus we harness the power of Python to solve complex research problems everyday. Python
helps us to effectively deal with large unstructured biological data, perform data retrieval and parsing,
automation, data manipulation as well as simulation of biological systems. As the core business of
Innoplexus is in Life sciences, we have lots of biological examples of Python usage to share with you all.
Learning objectives
The learning objective of today’s workshop is to provide a bird’s eye view to Python language, while
showcasing the capabilities of this versatile language with use cases and demonstrations, both within the
domain of Life science and outside.
The workshop is aimed at programming naive audience and hence will cover topics from basics of
language to application case studies.
Workshop Facilitator:
Speakers
Rutuja Viregaonkar
Associate Data Scientist
Apurva Naik
Data Scientist
Akshita Negi
Associate Data Analyst
Swati Saini
Associate Data Scientist
Agenda:
(10:00 am – 10:30 am) – Registration formalities |
(10:30 am – 10:40 am) – Welcome note by CTO |
(10:40 am – 10:45 am) – Workshop kick off |
(10:45 am – 11:00 am) – Ice breaker and Day’s agenda |
(11:00 am – 12:15 pm)
Session 1: Just Enough Python Basics
|
(12:15 pm – 12:45 pm) – Activity Break for Session 1 |
(12:45 pm – 1:00 pm) – Lunch |
(1:00 pm – 2:15 pm) –
Session 2: A guide to Data Science pipeline
|
(2:30 pm – 3:45 pm) –
Session 3: Data Visualization using Python and D3
|
(3:45 pm – 4:00 pm) – Tea break |
(4:00 pm – 5:00 pm) –
Session 4: Big data using Python
|
(5:00 pm – 5:15 pm) – Learnings and Take home |