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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: Artificial Intelligence Applications | - NLP and Computer Vision Overview - Deep Learning Fundamentals |
| Topic 3: Machine Learning and Predictive Modeling | - Model Evaluation and Validation - Unsupervised Learning - Supervised Learning |
| Topic 4: Data Management and Governance | - Data Privacy and Security Principles - Data Quality and Lifecycle Management |
| Topic 5: Big Data Engineering and Technologies | - Distributed Computing Concepts - Data Pipelines and ETL |
DASCA Senior Data Scientist Sample Questions:
1. Which of the following is a Python library for fitting Bayesian networks to real data?
A) MCMC
B) PyMC
C) SciLib
D) MyLib
E) SCIMC
2. Tar is an example of:
A) ARV file format
B) Archive file format
C) Text file format
D) CSV file format
E) None of the above
3. HDFS supports which quotas?
A) Space quotas
B) None of the above
C) Both A and B
D) Name quotas
4. 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
5. Which of the following is correct for Markov chain?
A) Both B and C
B) A Markov chain is the state of a system at sequential points in time
C) A Markov chain is a sequence of random variables X1, X2
D) Both A and B
E) A Markov chain is a sequence of fixed variables X1, X2
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: B | Question # 3 Answer: C | Question # 4 Answer: D | Question # 5 Answer: A |
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