For this project, I will assume the role of a Data Scientist working for a new startup investment firm that helps customers invest their money in stocks. My job is to extract financial data like historical share price and quarterly revenue reportings from various sources using Python libraries and webscraping on popular stocks. After collecting this data you will visualize it in a dashboard to identify patterns or trends. The stocks we will work with are Tesla, Amazon, AMD, and GameStop.
2. Extraction Assignment using Webscraping
4. Revenue Data and Building a Dashboard-v1
- Data extraction using the yfinance library
- Webscraping using the BeautifulSoup library
- Data Analysis
- Dashboard creation
The following tools were used to complete this certification:
The following Python libraries were used throughout the certification:
A dashboard often provides a view of key performance indicators in a clear way. Analyzing a data set and extracting key performance indicators will be practiced. Prompts will be used to support learning in accessing and displaying data in dashboards. Learning how to display key performance indicators on a dashboard will be included in this assignment. We will be using Plotly in this course for data visualization and is not a requirement to take this course.
In the Python for Data Science, AI and Development course you utilized Skills Network Labs for hands-on labs.
For this project I will use Skills Network Labs and Watson Studio. Skills Network Labs is a sandbox environment for learning and completing labs in courses. Whereas Watson Studio, a component of IBM Cloud Pak for Data, is a suite of tools and a collaborative environment for data scientists, data analysts, AI and machine learning engineers and domain experts to develop and deploy my projects.
To view the Certificate click on the image
