Python Project for Data Science By IBM Course Syllabus

Overview: This project-based course is designed to help learners apply Python programming skills to real-world data analysis tasks. Over 6–8 weeks, you'll gain hands-on experience retrieving, cleaning, analyzing, and visualizing financial data. The course emphasizes practical application through interactive tools and ends with a portfolio-ready project. Estimated time commitment is 6–8 hours per week, depending on prior experience.

Module 1: Introduction to the Data Science Project

Estimated time: 2 hours

• Understand the goals of the project
• Set up the Python environment using Jupyter Notebooks
• Review foundational Python concepts for data science
• Explore the structure of the final project deliverables

Module 2: Extracting Stock Data Using APIs

Estimated time: 3 hours

• Learn how to use APIs to retrieve real-time stock data
• Fetch historical stock prices for companies like Tesla and GameStop
• Parse JSON responses and convert them into structured data
• Store and inspect data using Pandas DataFrames

Module 3: Web Scraping Revenue Data with BeautifulSoup

Estimated time: 4 hours

• Extract company revenue data from web pages using web scraping
• Use BeautifulSoup to parse HTML content
• Handle common challenges in web scraping, such as dynamic content and table extraction
• Combine scraped data with API data for comprehensive analysis

Module 4: Data Cleaning and Manipulation with Pandas

Estimated time: 5 hours

• Identify and handle missing or inconsistent data
• Transform and standardize data types and formats
• Merge datasets from different sources (API and web scraping)
• Prepare clean, structured data for visualization

Module 5: Data Visualization with Plotly

Estimated time: 6 hours

• Create interactive line and bar charts using Plotly
• Visualize stock price trends and revenue changes over time
• Customize plots with titles, labels, and hover features
• Integrate visualizations into a Jupyter Notebook dashboard

Module 6: Final Project

Estimated time: 8 hours

• Build an interactive dashboard summarizing stock and revenue data
• Present insights through data storytelling using visualizations
• Submit your Jupyter Notebook for peer review and feedback

Prerequisites

• Familiarity with basic Python programming
• Understanding of variables, loops, and functions
• Basic knowledge of data structures like lists and dictionaries

What You'll Be Able to Do After

• Apply Python to real-world data analysis tasks
• Retrieve data from APIs and web sources
• Clean and manipulate data using Pandas
• Create interactive visualizations with Plotly
• Build and present a data-driven dashboard for storytelling