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DASCA SDS Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Mathematics and Statistics for Data Science | - Probability and Statistical Inference - Linear Algebra and Optimization |
| Topic 2: Data Management and Governance | - Data Quality and Lifecycle Management - Data Privacy and Security Principles |
| Topic 3: Artificial Intelligence Applications | - NLP and Computer Vision Overview - Deep Learning Fundamentals |
| Topic 4: Machine Learning and Predictive Modeling | - Model Evaluation and Validation - Unsupervised Learning - Supervised Learning |
| Topic 5: Big Data Engineering and Technologies | - Data Pipelines and ETL - Distributed Computing Concepts |
DASCA Senior Data Scientist Sample Questions:
1. 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
2. What is Scrumban?
A) It combines the principles of Scrum and Kanban into a push-based system
B) It combines the principles of Scrum and Kanban into a pull-based system
C) It is Kanban
D) It is Scrum
3. Which of the following architectural techniques is used for parallel processing?
A) Both A and B
B) The SuperVector Technique
C) The Superscalar Technique
D) Very Long Instruction Words (VLIW) Technique
E) Both B and C
4. Which of these statements reflects a null hypothesis?
A) There will be a significant difference between group 1 and group 2
B) There will be no relationship between caffeine consumption and performance
C) Women will score higher than men on empathy
D) As temperature increases, so too will the level of aggression
E) Men will score higher than women on spatial awareness
5. Which of the following is a trend analysis component of time series decomposition?
A) Seasonal
B) All of the above
C) Cyclical
D) Both A and B
E) Irregular
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: B | Question # 3 Answer: A | Question # 4 Answer: B | Question # 5 Answer: B |
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