Events Calendar

Introduction to Python Data Analytics

NOTE: We are at capacity of the room. If you are interest in attending, please email Sai Ramadugu (saikumar-ramadugu@uiowa.edu) to secure a spot.

 

 

This introductory course will cover the basic elements in Python data analytics. The topics to be covered the class include a brief introduction to data science and data analytics framework/tools/libraries, data handling with Python, and data analysis and visualization with Python and running some examples using Jupyter Notebook. No prior experience with Python is necessary for this course.

The course is taught by our Staff Data Scientist, Kang Lee. The room size is restricted to 16 attendees, so please click on "I'm Interested" and sending an email to Sai Ramadugu will help us to track the attendees.

Agenda/Curriculum:

  • Basic Concepts of Python (Data Analytics)
  • Demonstration of Python Data Analytics
  • Jupyter Notebook and code examples

Requirements for the class:

Please install Jupyter Notebook prior if you are bringing your own laptop. The computers in the Training Room will already be preinstalled with Jupyter Notebook. The installation notes can be found here.

Thursday, September 14 at 12:00pm to 3:00pm

University Capitol Centre, 2523 (Training Room)
200 South Capitol Street, Iowa City, Iowa

Event Type

Conference/Workshop, Training

Audience

Students, Faculty/Staff

Departments

Information Technology Services, Research Services, High Performance Computing

General Interest

Informatics

Tags

Research Data

Cost

Free to attend

Contact Name

Sai Ramadugu

Contact Email

saikumar-ramadugu@uiowa.edu

Contact Phone Number

3193355330

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Recent Activity

Landon Evans

Landon Evans left a positive review 9/13/2017

Good class for a quick summary of a lot of options within Python. As a R user looking to possibly make some move to Python, it was helpful to see how it could possibly replace some of my workflow. The only criticism is that some of the packages/modules that were covered, it may be best to have separate courses for them as individuals that didn't have much background in python or data analytics, the pace was probably too fast.