41. What is the purpose of a "post-mortem analysis" in the context of a data science capstone project? A. Visualize data distributions B. Model deployment C. Evaluate project successes and failures D. Data preprocessing Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option C No explanation is given for this question Let's Discuss on Board
42. Why is "communication" considered a critical skill in a data science capstone project? A. Replace data exploration B. Share findings with stakeholders C. Choose the mentor D. Replace data exploration Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option B No explanation is given for this question Let's Discuss on Board
43. What is the primary goal of "knowledge transfer" in a data science capstone project? A. Ensure others can continue the work B. Enhance model complexity C. Replace data exploration D. Speed up the project Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option A No explanation is given for this question Let's Discuss on Board
44. In a data science capstone project, what is the purpose of "scrum" or "agile" methodologies? A. Visualizing data distributions B. Selecting the mentor C. Writing the final report D. Manage project tasks and deadlines Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option D No explanation is given for this question Let's Discuss on Board
45. Why is it crucial to incorporate "feedback loops" and "continuous improvement" in a data science capstone project? A. Create more project documentation B. Replace data exploration C. Adapt to changing requirements D. Choose the mentor Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option C No explanation is given for this question Let's Discuss on Board
46. What is the primary purpose of "A/B testing" or "split testing" in a data science capstone project? A. Replace data exploration B. Compare the performance of two versions C. Choose the mentor D. Replace data exploration Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option B No explanation is given for this question Let's Discuss on Board
47. Why is it important to establish "data pipelines" or "data integration" in a data science capstone project? A. Simplify the project report B. Conduct data exploration C. Automate data collection and processing D. Create more project documentation Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option C No explanation is given for this question Let's Discuss on Board
48. In a data science capstone project, what is the role of "interpretation" and "business impact analysis"? A. Add complexity to the project B. Replace data exploration C. Choose the mentor D. Explain the implications of findings Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option D No explanation is given for this question Let's Discuss on Board
49. What does "scalability" refer to in the context of deploying machine learning models in a capstone project? A. Ability to handle increased workload B. Writing the project proposal C. Selecting the programming language D. Visualizing data distributions Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option A No explanation is given for this question Let's Discuss on Board
50. What is the primary goal of "stakeholder engagement" in a data science capstone project? A. Data preprocessing B. Model deployment C. Enhance model interpretability D. Collaborate and gather feedback Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option D No explanation is given for this question Let's Discuss on Board
