Python Project for Data Science

Apply Python fundamentals, Python data structures, and working with data in Python. This mini-course is intended to for you to demonstrate foundational Python skills for working with data. This course primarily involves completing a project in which you will assume the role of a Data Scientist or a Data Analyst and be provided with a real-world data set and a real-world inspired scenario to identify patterns and trends.

What you’ll learn

1. Play the role of a Data Scientist / Data Analyst working on a real project.
2. Demonstrate your Skills in Python – the language of choice for Data Science and Data Analysis.
3. Apply Python fundamentals, Python data structures, and working with data in Python.
4. Build a dashboard using Python and libraries like Pandas, Beautiful Soup and Plotly using Jupyter notebook.

Crowdsourcing Short squeeze Dashboard

In this module, you will demonstrate your skills in Python – the language of choice for Data Science and Data Analysis. You will apply Python fundamentals, Python data structures, and work with data in Python. By working on a real project, you will model a Data Scientist or Data Analyst’s role, and build a dashboard using Python and popular Python libraries using Jupyter notebook.

1. HTML for Webscraping
2. Webscraping
3. Course Introduction
4. Intro to Web Scraping
5. Project Overview
6. Stock shares
7. Optional: Gamestop stock vs Tesla
8. (Optional)Jupyter Notebook to complete your final project
9. (Optional)Hands-on Lab: Analyzing Historical Stock/Revenue Data and Building a Dashboard
10. Extracting Stock Data Using a Python Library
11. Extracting Stock Data Using a Web Scraping
12. Analyzing Historical Stock/Revenue Data and Building a Dashboard
13. Intro to Web Scraping Using BeautifulSoup
14. Extracting Stock Data Using a Python Library
15. Extracting Stock Data Using Web Scraping
16. Hands-on Lab: Analyzing Historical Stock/Revenue Data and Building a Dashboard
17. (Optional)Obtain IBM Cloud Feature Code and Activate Trial Account
18. Reading: yfinance Library
19. (Optional)Hands-on Lab: Create IBMCloud account and Watson Studio instance
20. (Optional)Hands-on Lab: Add notebook to Watson Studio
21. (Optional)Hands-on Lab: Share your notebook from Watson Studio

Course is taught by Azim Hirjani. Azim Hirjani is a Data Scientist Intern at IBM and is pursuing a BS in Computer Science from the University of Toronto. He creates content for various IBM Data Science courses on platforms such as Coursera and Edx. He has worked as a Data Wrangler at Equifax, utilizing Big Data technologies and has interests in Reinforcement Learning and Real Estate.