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DASCA SDS Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Big Data Engineering and Technologies | - Data Pipelines and ETL - Distributed Computing Concepts |
| Topic 2: Mathematics and Statistics for Data Science | - Linear Algebra and Optimization - Probability and Statistical Inference |
| Topic 3: Artificial Intelligence Applications | - Deep Learning Fundamentals - NLP and Computer Vision Overview |
| Topic 4: Machine Learning and Predictive Modeling | - Model Evaluation and Validation - Supervised Learning - Unsupervised Learning |
| Topic 5: Data Management and Governance | - Data Privacy and Security Principles - Data Quality and Lifecycle Management |
DASCA Senior Data Scientist Sample Questions:
1. OCR (Optical Character Recognition) is an application used for:
A) Machine learning
B) Big Data Analytics
C) Data mining
D) MapReduce
2. Which of the following is NOT a main data container in Python?
A) Tuples
B) Lists
C) LinkedList
D) Dict
3. Exploratory analytic algorithms help the Data Science team to better:
A) Understand the data content
B) Understand patterns in the data
C) Both A and B
D) Gain a high-level understanding of relationships
E) All of the above
4. ARIMA model is:
A) Autointeractive moving average
B) All of the above
C) Autoreactive moving average
D) Autoresponsive moving average
E) Autoregressive moving average
5. Spark should be used when:
A) Data is massive
B) Both A and B
C) None of the above
D) Data is not massive
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: E | Question # 4 Answer: E | Question # 5 Answer: A |






