What you will learn in Python Project for Data Science By IBM Course
- Apply foundational Python programming skills to real-world data analysis tasks.
- Extract stock and revenue data using APIs and web scraping techniques.
- Clean and manipulate data using Pandas
- Create compelling visualizations using Plotly.
- Build and present an interactive dashboard for data-driven storytelling.
Program Overview
Project-Based Learning with Python
⏱️ 6–8 weeks
- Retrieve stock price data for companies like Tesla and GameStop using APIs.
- Extract revenue data via web scraping using BeautifulSoup.
- Clean, transform, and structure the data using Pandas.
- Create interactive plots using Plotly to reveal data insights.
- Develop a dashboard in a Jupyter Notebook that summarizes your analysis.
- Submit your work for peer review to reinforce understanding and practical application.
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Job Outlook
Python is the top language used in data science roles globally.
Data Analysts and Scientists proficient in data wrangling and visualization are in high demand across sectors.
Entry-level analysts using Python and visualization libraries (Pandas, Plotly) can earn between $65K – $100K annually.
This project-based course enhances portfolio value for jobs requiring hands-on analytics experience.
Employers value candidates who demonstrate real-world data application through projects, especially for freelance, corporate, or startup roles.
Specification: Python Project for Data Science By IBM
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FAQs
- Focuses on practical projects using Python
- Covers data cleaning, analysis, and visualization
- Introduces popular libraries like Pandas, NumPy, and Matplotlib
- Helps learners apply Python skills to solve data problems
- Basic Python understanding is recommended
- Beginners can still follow with guided examples
- Teaches coding practices specific to data science
- Builds confidence through applied exercises
- Data manipulation with Pandas and NumPy
- Data visualization with Matplotlib and Seaborn
- Practical experience working with datasets
- Problem-solving using Python in a data science context
- Guided projects to practice coding skills
- Step-by-step exercises to build confidence
- Real-world datasets for exploration
- A capstone project to demonstrate learning
- Strengthens portfolio with project work
- Builds confidence for entry-level data science jobs
- Helps in interviews with hands-on project experience
- Adds valuable skills for careers in AI, ML, and analytics
