Python: Data Science Fundamentals

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

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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
Intermediate