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DASCA SDS Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Artificial Intelligence Applications | - NLP and Computer Vision Overview - Deep Learning Fundamentals |
| Big Data Engineering and Technologies | - Data Pipelines and ETL - Distributed Computing Concepts |
| Mathematics and Statistics for Data Science | - Probability and Statistical Inference - Linear Algebra and Optimization |
| Data Management and Governance | - Data Privacy and Security Principles - Data Quality and Lifecycle Management |
| Machine Learning and Predictive Modeling | - Supervised Learning - Unsupervised Learning - Model Evaluation and Validation |
DASCA Senior Data Scientist Sample Questions:
1. Which of these statements reflects a null hypothesis?
A) There will be no relationship between caffeine consumption and performance
B) Women will score higher than men on empathy
C) As temperature increases, so too will the level of aggression
D) There will be a significant difference between group 1 and group 2
E) Men will score higher than women on spatial awareness
2. Maximum Likelihood Estimation (MLE) is a way to frame:
A) Small class of problems in Data Science
B) Large class of problems in HDFS
C) Small class of problems in HDFS
D) Both A and C
E) Large class of problems in Data Science
3. The main purpose of a Statement Of Work (SOW) is to get:
A) All of the above
B) Everybody on the same page about what work should be done
C) None of the above
D) What expectations are realistic
E) What the priorities are
4. Which of the following is an example of NLP?
A) Using Twitter to assess public sentiment
B) All of the above
C) Finding which text documents are about similar topics
D) Flagging e-mails as spam
E) Both A and C
5. What is DevOps?
A) Software Development
B) Software Operations
C) Quality Assurance
D) All
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: E | Question # 3 Answer: A | Question # 4 Answer: B | Question # 5 Answer: D |
