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Module 3 challenge :Foundations of Data Science (Google Advanced Data Analytics Professional Certificate) Answers 2025

Question 1

Future trend in the organization of data-focused teams:

  • A consolidation into one generalist ❌

  • Increased specialization, with further subdivision of roles ✅

  • One all-star with small staff ❌

  • Shift away from using data analysis ❌

Explanation:
As data grows more complex, companies expand specialization (ML engineers, data engineers, analysts, etc.).


Question 2

Appropriate LLM use cases (Select all):

  • To bypass security systems ❌

  • Provide an outline for a report ✅

  • Generate code to visualize data ✅

  • Brainstorm ideas for approaching a problem ✅

Explanation:
LLMs must not be used for security evasion, but are excellent for ideation, templates, and assisting with code.


Question 3

Main activities in data professions (Select all):

  • Statistical inference ✅

  • Machine learning ✅

  • Data analytics ✅

  • Software development ❌ (not a core data-profession activity)

Explanation:
These three form the foundation of modern data work.


Question 4

Appropriate use of AI (Select all):

  • LLM retrieving internet data to fill spreadsheet ❌ (privacy + accuracy risk)

  • LLM assisting with complex regular expression code ✅

  • ML model setting insurance rates automatically ❌ (high-risk, needs human oversight)

  • LLM simplifying complex statistical concepts for communication ✅

Explanation:
LLMs are good for coding help and communication—not for automating high-risk decisions or unauthorized data collection.


Question 5

Tools commonly used by data professionals (Select all):

  • Kaggle ✅

  • GitHub ✅

  • Cedreo ❌

  • OctaneRender ❌

Explanation:
Kaggle + GitHub are standard in data work; the others are architecture/3D rendering tools.


Question 6

Best tool to store/manage millions of fast-query customer records:

  • Spreadsheet ❌

  • Dashboard ❌

  • Programming language ❌

  • A database ✅

Explanation:
Databases (SQL/NoSQL) support scalability, indexing, and fast retrieval for high-volume transactions.


Question 7

Data visualization tools (Select all):

  • Seaborn ✅

  • Tableau ✅

  • Matplotlib ✅

  • Oracle ❌ (a database / enterprise software suite, not a viz tool)

Explanation:
Seaborn and Matplotlib are Python libraries; Tableau is a standalone BI tool.


Question 8

Tool used by the air traffic controller:

  • Spreadsheet ❌

  • Programming language ❌

  • Dashboard ✅

  • Database ❌ (backend stores the data, but she directly interacts with a dashboard)

Explanation:
A dashboard provides interactive, real-time data views.


Question 9

Examples of LLMs (Select all):

  • Gemini ✅

  • Visual Studio Code ❌

  • Microsoft Office ❌

  • ChatGPT ✅

Explanation:
Gemini and ChatGPT are LLMs; VS Code and Office are software tools, not AI models.


Question 10

Best practices for writing LLM prompts (Select all):

  • Be precise. ✅

  • Include a description of the LLM’s role. ✅

  • Don’t provide background information ❌ (background is helpful)

  • Make sure there are no spelling errors ❌ (LLMs can handle minor spelling issues)

Explanation:
Good prompts include specificity and context; spelling errors rarely cause failures.


🧾 Summary Table

Q# Correct Answers Key Concept
1 Increased specialization Team evolution
2 Outline, code help, brainstorming Safe LLM usage
3 Statistical inference, ML, analytics Core data activities
4 Regex help, simplifying concepts Ethical AI
5 Kaggle, GitHub Common tools
6 Database Data storage needs
7 Seaborn, Tableau, Matplotlib Visualization tools
8 Dashboard Real-time interactive tool
9 Gemini, ChatGPT LLM examples
10 Be precise, define role Prompting best practices