Data Science Fundamentals

Python 3
  • 16 Videos | 1h 43m 34s
  • Includes Assessment
  • Earns a Badge
Likes 57 Likes 57
Code readability and simplicity are the primary design goals of the Python language. Add a few key APIs and it becomes a powerful data analysis tool. Examine basic data science fundamentals and how to apply them to Python.

WHAT YOU WILL LEARN

  • 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 and ggplot2
    demonstrate how to set up and use Anaconda for Python in Eclipse
  • provide a basic overview of scikit-learn and create a basic sample to show its use
    use the scikit-image package to perform image processing in Python
    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 the BeautifulSoup Parser for Python
    install and configure PySpark for Python
    perform basic data manipulation using pandas

IN THIS COURSE

  • Playable
    1. 
    Introduction to Jupyter/IPython
    10m 22s
    UP NEXT
  • Playable
    2. 
    Working with Jupyter/IPython
    5m 30s
  • Locked
    3. 
    Introduction to NumPy
    5m 12s
  • Locked
    4. 
    Working with NumPy Arrays
    5m 34s
  • Locked
    5. 
    Introduction to Pandas
    5m 46s
  • Locked
    6. 
    Data Manipulation with Pandas
    8m 19s
  • Locked
    7. 
    Data Visualization with Matplotlib,Ggplot2
    3m 34s
  • Locked
    8. 
    Introduction to Anaconda
    5m 16s
  • Locked
    9. 
    Python and Scikit-learn
    2m 25s
  • Locked
    10. 
    Image Processing in Python
    6m 4s
  • Locked
    11. 
    Geospatial Analysis Using ArcGIS
    5m 28s
  • Locked
    12. 
    Text Analytics with NLTk
    6m 7s
  • Locked
    13. 
    Social Network Analysis using Networkx
    6m 40s
  • Locked
    14. 
    The BeautifulSoup Parser for Python
    8m 57s
  • Locked
    15. 
    Working with PySpark for Big Data
    7m 42s
  • Locked
    16. 
    Exercise: Working with Pandas
    3m 8s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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