Final Exam :What is Data Science? (IBM Data Science Professional Certificate) Answers 2025
1️⃣ Question 1
How can data science systems with predictive analytics benefit healthcare professionals?
-
✅ They recommend personalized treatment plans for patients.
-
❌ They prioritize specific diagnostic tests.
-
❌ They store a physician’s individual knowledge.
-
❌ They offer extra information to patients.
Explanation:
Predictive analytics helps create personalized treatment plans by analyzing patterns in patient data.
2️⃣ Question 2
Who coined the term “data science”?
-
❌ Andrew Gelman and John Doe
-
❌ Andrew Gelman and DJ Patil
-
❌ Ada Lovelace and John Doe
-
Correct Answer: NONE OF THESE OPTIONS ARE ACCURATE
But the closest common attribution in modern context is: -
❌ DJ Patil and Marjorie Lee Brown
Correct concept:
The term “data science” originated in the 1960s in academic discussions; it is not credited to a specific pair of individuals.
Explanation:
None of the provided combinations is historically correct.
3️⃣ Question 3
What does “The Sexiest Job of the 21st Century” say will happen when executives become versed in data analytics?
-
❌ They will change their field to data science.
-
❌ They will go back to school.
-
✅ Organizations will see real change in their businesses.
-
❌ They will retire.
Explanation:
When leaders understand analytics, they make better decisions, creating business transformation.
4️⃣ Question 4
What is an absolute must for new data scientists?
-
❌ Being argumentative
-
❌ Comfort with analytics platforms
-
✅ Curiosity
-
❌ Ability to tell a great story
Explanation:
Curiosity drives discovery, exploration, experimentation, and data-driven insights.
5️⃣ Question 5
What change did the Houston Rockets make after analyzing video tracking data?
-
✅ They increased the number of attempted three-point shots.
-
❌ New way to toss the ball
-
❌ Emphasized teamwork
-
❌ Focused more on passing
Explanation:
Analytics showed 3-pointers were more efficient, so they increased them dramatically.
6️⃣ Question 6
Three cloud deployment models?
-
❌ Infrastructure, Platform, Application
-
✅ Public, Private, Hybrid
-
❌ Open internet, Exclusive use, Mix of both
-
❌ Analytical, Efficient, Collaborative
Explanation:
These are the standard deployment models in cloud computing.
7️⃣ Question 7
Why have data science and business analytics become important?
-
❌ They require an MBA
-
❌ Availability of traditional techniques
-
❌ Advancements in statistics
-
✅ Emergence of new tools and abundance of data
Explanation:
Modern tools + massive data availability = rapid rise of data science.
8️⃣ Question 8
Which software provides distributed storage and processing of big data?
-
✅ Hadoop
-
❌ Python
-
❌ Salesforce
-
❌ Photoshop
Explanation:
Hadoop provides distributed storage via HDFS and processing via MapReduce.
9️⃣ Question 9
Which term describes: algorithms that learn and make decisions without explicit programming?
-
❌ Distributed network
-
❌ Data scientist
-
✅ Machine learning
-
❌ Big data
Explanation:
ML systems learn from data rather than following fixed rules.
🔟 Question 10
When data mining, which statement is true?
-
❌ Hypothesis depends on the data quality
-
❌ Programming language depends on data quality
-
❌ Statistics depend on data quality
-
✅ The success of a data mining exercise largely depends on the quality of the data.
Explanation:
Better data → better insights; poor data → poor results.
1️⃣1️⃣ Question 11
Primary focus of generative AI?
-
❌ Replace curiosity
-
❌ Determine business needs
-
❌ Create a story for stakeholders
-
✅ Create new instances that replicate the underlying distribution of data
Explanation:
Generative AI models (GANs, VAEs, LLMs) generate new data resembling the original.
1️⃣2️⃣ Question 12
Which is an example of a recommendation engine?
-
❌ Text messaging apps
-
❌ Google Chrome browser
-
✅ Software Facebook uses to deliver advertisements
-
❌ Spreadsheets
Explanation:
Facebook’s ad-targeting system recommends ads to the right users based on behavior.
🧾 Summary Table
| Q | Correct Answer | Key Concept |
|---|---|---|
| 1 | Personalized treatment plans | Predictive analytics in healthcare |
| 2 | None (no correct option provided) | History of “data science” term |
| 3 | Organizations see real change | Analytics-driven leadership |
| 4 | Curiosity | Essential DS quality |
| 5 | More 3-point shots | Sports analytics |
| 6 | Public, Private, Hybrid | Cloud deployment |
| 7 | New tools + lots of data | Rise of DS |
| 8 | Hadoop | Big data processing |
| 9 | Machine learning | Algorithms that learn |
| 10 | Success depends on data quality | Data mining principles |
| 11 | Generate new instances of data | Generative AI |
| 12 | Facebook ad recommendation | Recommendation systems |