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DASCA SDS Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Advanced Statistical Modeling | 20-25% | - Statistical Inference
|
| Topic 2: Machine Learning at Scale | 25-30% | - Deep Learning Fundamentals
|
| Topic 3: Data Visualization and Communication | 10-15% | - Visualization Principles
|
| Topic 4: Foundations of Data Science | 15-20% | - Data Science Lifecycle
|
| Topic 5: Big Data Engineering | 15-20% | - Distributed Computing
|
DASCA Senior Data Scientist Sample Questions:
1. Data wrangling is the process of getting the data from:
A) Both A and B
B) Its modified meaning format into something suitable for more conventional analytics
C) Its raw format into something suitable for more conventional analytics
D) None of the above
2. In regression, the principle of machine learning is used to optimize the parameters to:
A) Both A and B
B) Calculate the closest possible outcomes
C) Minimize the approximation error
D) None of the above
3. Which of the following is NOT a valid section of Big Data Strategy document?
A) Business strategy
B) Business decisions
C) Key business initiatives
D) Key business entities
E) Key decisions
4. ElementTree sub-library gives us direct access to:
A) Copy tree of the XML
B) Delete tree of the XML
C) Parse tree of the XML
D) None of the above
E) Insert tree of the XML
5. Which of the following is correct about customer lifetime value (CLTV)?
i. Most organizations determine the current customer lifetime value (CLTV) based on historic sales over past
12 to 18 months
ii. The goal of the CLTV score is to help marketing and store personnel to determine the "value" of a customer
A) Only i
B) Only ii
C) Both i and ii
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: A | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: C |
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