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DASCA SDS Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Foundations of Data Science | 15-20% | - Data Science Lifecycle
|
| Topic 2: Advanced Statistical Modeling | 20-25% | - Statistical Inference
|
| Topic 3: Data Visualization and Communication | 10-15% | - Tools and Technologies
|
| Topic 4: Big Data Engineering | 15-20% | - Cloud Computing for Data Science
|
| Topic 5: Machine Learning at Scale | 25-30% | - Unsupervised Learning
|
DASCA Senior Data Scientist Sample Questions:
1. ARIMA model is:
A) Autoregressive moving average
B) All of the above
C) Autointeractive moving average
D) Autoreactive moving average
E) Autoresponsive moving average
2. Which of the following is a Python library for fitting Bayesian networks to real data?
A) SciLib
B) PyMC
C) MyLib
D) MCMC
E) SCIMC
3. Which of the following is TRUE for "By" analysis?
A) All of the above
B) The "By" analysis technique reinforces the process of "thinking like a data scientist."
C) "By" analysis is a technique by which business subject matter experts (SMEs) and the Data Science team could collaborate to uncover new variables and metrics that might be better predictors of business performance.
D) "By" analysis is used to create a collaborative technique to drive alignment between the business users and the data scientists to identify and brainstorm variables and metrics that might be better predictors of business performance.
E) Both B and C
4. The grid computing environment uses a middleware to:
A) None of the above
B) Combine computing resources
C) Divide computing resources
D) Both A and B
5. What is TRUE for "rehashing"?
A) It requires a new hash function, which maps values into a larger range of integers
B) All of the above
C) Allocate a new, larger hash table in memory
D) Both A and B
E) Key/value pairs from the original table can be inserted into the new, larger one
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: B | Question # 3 Answer: A | Question # 4 Answer: D | Question # 5 Answer: B |
