Here are the key features of the Applied Data Science Capstone:

1. Practical Data Science Project: The capstone project is designed to provide hands-on experience in solving a real-world data science problem. Learners work on a substantial project that involves data analysis, machine learning, and data visualization.

2. Collaboration: The capstone project often encourages collaboration among learners, simulating real-world team dynamics. Learners work together to complete the project, reflecting the collaborative nature of data science in industry settings.

3. Diverse Data Sources: The project typically involves working with diverse datasets from various domains. This exposes learners to different types of data and challenges commonly encountered in data science projects.

4. End-to-End Process: Learners go through the entire data science project lifecycle, from problem formulation and data acquisition to data cleaning, exploratory data analysis, modeling, and presentation of results.

5. Use of Data Science Tools: Learners utilize popular data science tools and libraries such as Python, pandas, scikit-learn, and Jupyter notebooks to complete the project.

6. Business Context: The capstone project often requires learners to consider the business or practical context of their analysis. They must frame their findings in a way that is relevant and actionable for stakeholders.

7. Mentorship: Some capstone projects provide opportunities for mentorship and guidance from experienced data scientists, helping learners navigate challenges and make informed decisions during the project.

8. Peer Evaluation: Learners may engage in peer evaluation, where they review and provide feedback on their peers’ capstone projects. This fosters a sense of community and peer learning.

9. Portfolio Piece: Successful completion of the Applied Data Science Capstone results in a tangible project that learners can include in their data science portfolios, showcasing their skills to potential employers.

10. Certification: Upon successful completion of the capstone project and the entire Data Science Professional Certificate program, learners receive a certificate from IBM, which can be a valuable credential when seeking data science-related positions.