[Online] Python for Data Science Immersive

* THIS IS A PAID WORKSHOP.

One Week Paid Course, Total in class hours 35,

Mon, September 28th, 11:00 a.m. - 6:00 p.m. EDT
Tue, September 29th, 11:00 a.m. - 6:00 p.m. EDT
Wed, September 30th, 11:00 a.m. - 6:00 p.m. EDT
Thu, October 1st, 11:00 a.m. - 6:00 p.m. EDT
Fri, October 2nd, 11:00 a.m. - 6:00 p.m. EDT

RSVP and READ SYLLABUS HERE: https://pythonair.com/online-Python-for-Data-Science

During this course we solve many real-world financial, statistical, and analytical problems. This course is a MUST if you still use EXCEL.

ABOUT THE COURSE:
Data Science Immersive is a week-long comprehensive course with an emphasis on the practical application of Python to data analysis. In the first two days we cover Python s built-in data types, explaining differences in the behavior of data structures, laying a foundation for the more complex NumPy and Pandas structures.

A deep understanding of data types prepares users to solve real-life challenges with the right tools in the most efficient manner. Also, it is important to understand why some of the types are faster and some are just an extension of others.

In this course we are not covering in-depth mathematical and statistical concepts, rather we master practical usage of the Python programming language and its extensions NumPy and Pandas.

WHAT TO EXPECT FROM THIS COURSE:
When you sign up for this course, you should also be prepared to work hard. While we do explain all of the concepts thoroughly and have notes on each lesson that you can refer back to, we follow up each lesson with practice problems to reinforce the material. We code almost seven hours a day with breaks for lunch and coffee.

ONLINE PYTHON FOR DATA SCIENCE IMMERSIVE SYLLABUS:

Monday 11.00am - 6.00pm:
Variables
Numeric Data Types: Int & Float
Sequential Types: Str & List
Definite Loops: For loops
If-Elif-Else Statements
Data Types: Tuples
Practical Exercises

Tuesday 11.00am - 6.00pm:
Creating Custom Functions
Indefinite Loops: while loops
Data Types, Dictionary and Set
Slicing Data Types
Reading txt files with Python
Practical Exercises

Wednesday 11.00am - 6.00pm:
NumPy Array
Broadcasting and U-Functions
Introduction to Pandas
Series, DataFrame, Panel
Practical Exercises

Thursday 11.00am - 6.00pm:
5 ways to create a DataFrame
Slicing and Filtering DataFrame
Lambda
Run If and Else scenarios
Gather and Manipulate Data with Pandas
Practical Exercises

Friday 11.00am - 6.00pm:
Get live data from APIs
Plot data with Matplotlib
Merge and Concat Data
Groupby in Pandas
Final project
Review and Q&A

Prerequisites & Preparation:
Laptop or desktop computer & Internet Access

Check out Newsweek s article to learn about Practical Programming: https://www.newsweek.com/insights/the-top-online-coding-schools-of-2020/practical-programming