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DASCA SDS Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Machine Learning and Predictive Modeling | - Model Evaluation and Validation - Unsupervised Learning - Supervised Learning |
| Topic 2: Big Data Engineering and Technologies | - Data Pipelines and ETL - Distributed Computing Concepts |
| Topic 3: Mathematics and Statistics for Data Science | - Probability and Statistical Inference - Linear Algebra and Optimization |
| Topic 4: Data Management and Governance | - Data Privacy and Security Principles - Data Quality and Lifecycle Management |
| Topic 5: Artificial Intelligence Applications | - NLP and Computer Vision Overview - Deep Learning Fundamentals |
DASCA Senior Data Scientist Sample Questions:
1. Which of the following is the common evolutionary algorithm of neural networks?
A) All of the above
B) Genetic algorithm
C) Genetic programming
D) Evolution strategy
2. Tar is an example of:
A) Archive file format
B) CSV file format
C) Text file format
D) None of the above
E) ARV file format
3. Which of the following architectural techniques is used for parallel processing?
A) The Superscalar Technique
B) Very Long Instruction Words (VLIW) Technique
C) Both B and C
D) Both A and B
E) The SuperVector Technique
4. The aim of developing Scribe was to offer reliability with using:
A) High disk space usage
B) Complex protocols
C) Extensive protocols
D) None of the above
5. Which of the following phases is NOT a Big Data Business Model Maturity Index?
A) Data Monetization
B) Business Optimization
C) Business Monitoring
D) Business Strategy
E) Business Metamorphosis
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: D | Question # 4 Answer: D | Question # 5 Answer: D |
