Course Description
Python is a high-level programming language that has code readability and simplicity as its primary design goals. Coupled with a few key APIs, it also becomes a very powerful data analysis tool. This course will cover basic data science fundamentals and apply them to Python.
Learning Objectives
Introduction to Data Science for Python
- start the course
- demonstrate how to set up and use Anaconda for Python
- describe the key features of Jupyter as well as how to install it
- work with the Notebook server and dashboard
- detail the key characteristics and how to install and use NumPy
- create an example that utilizes NumPy arrays
- detail the key characteristics and how to install pandas
- perform basic data manipulation using pandas
- create a data visualization using matplotlib
- use scikit-learn to perform data normalization
- perform supervised learning by using the scikit-learn library to perform optical recognition of hand-written digits
- install and use the ArcGIS Python API in a Python app
- use NLTK and Python to tokenize words and sentences
- analyze an ego network using Python and Networkx
- perform web scraping using BeautifulSoup 4 in Python
- install and configure PySpark for Python
Practice: Working with Python and Data Science
- perform basic data manipulation using pandas