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Python: Data Science Fundamentals


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/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.

Target Audience
Beginner Python developers, and developers with experience in other languages looking to start programming in Python.

Prerequisites
None

Expected Duration (hours)
1.7

Lesson Objectives

Python: Data Science Fundamentals

  • 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
  • perform basic data manipulation using pandas
  • Course Number:
    pg_pyth_a06_it_enus

    Expertise Level
    Everyone