Boston SQL Saturday - Introduction to Data Science With Python

Are you going?

5 people going

Share:
Location image of event venue

Details

I am please to announce that I will be teaching a one day seminar at SQL SAT #813 - Boston BI on Friday, March 29th. You can register for the course using the following link -

https://www.eventbrite.com/e/introduction-to-data-science-with-python-tickets-56254091502?

“Python” and “R” are two well-known data science languages being used today. Both of these languages are part of the open source community and have many free modules available for your use.

Which one of the languages do you choose as an enterprise standard?

My money is on the “Python” language, due to the fact it can be used to solve business problems other than ones related to data science.

Python is a general purpose programming language created by Guido van Rossum in 1991. It was designed for readability and easy syntax by using significant whitespace. The main goal was to allow programmers to solve problems using fewer lines of code.

During this one day pre-conference course, I will be covering the following topics.

[Python Programming Basics]

Defining and working with variables.
Handling user input and output.
Controlling the program flow.
Structuring data with tuples, lists and dictionaries.
Defining and using functions.
Modeling objects with classes.
Reading and writing files.
Handling exceptions with try except blocks.
Some interesting community packages.

[Introduction to Data Science with Python]

Identifying the problems that can be solved.
Leveraging numpy package for N dimensional arrays.
Applying the scipy package for scientific computing.
Using pandas package to create data frames.
Plotting data with the matplotlib package.
Machine learning using the skikit-learn package.
Sharing research with Jupyter notebooks.
Placing your scoring model into production.

This course is meant for beginners who want to learn Python. At the end of the day, you will have a solid understanding of the language and an introduction to the data science libraries.