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DASCA SDS Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Advanced AI & Generative AI | 20% | - Generative AI techniques, use cases, and limitations - Responsible AI, ethics, fairness, transparency, and compliance - Deep learning, neural networks, and foundation models |
| Topic 2: MLOps & Production Deployment | 15% | - Model lifecycle management, monitoring, and maintenance - DevOps integration, automation, and CI/CD - Model governance, security, and reliability |
| Topic 3: Data Science Applications in Business | 20% | - Translating business requirements into data science problems - Data science strategy and enterprise alignment - Measuring and demonstrating ROI of data science initiatives |
| Topic 4: Foundational Methods & Frameworks | 25% | - Data preparation, feature engineering, and quality assurance - Advanced statistics, probability, and experimental design - Machine learning algorithms, selection, and evaluation |
| Topic 5: Big Data Ecosystems & Scalable Systems | 20% | - Scalability, performance, and optimization - Distributed computing frameworks and cloud platforms - Data storage, processing pipelines, and governance |
DASCA Senior Data Scientist Sample Questions:
Question #1
Which of the following architectural techniques is used for parallel processing?
A. The Superscalar Technique
B. Both B and C
C. Very Long Instruction Words (VLIW) Technique
D. The SuperVector Technique
E. Both A and B
Question #2
Which of the following is correct?
A. A data frame is a table with rows and columns
B. All of the above
C. The central object in Pandas is called a DataFrame
D. DataFrame is similar to SQL tables or R data frames
E. Both A and B
Question #3
Semi-structured data does NOT include:
A. Database system
B. File systems
C. Scientific data
D. Schema-full data
Question #4
Bernoulli random variable is a type of:
A. Discrete random variable
B. Continuous random variable
C. Sometimes Discrete or sometimes Continuous random variable
D. Both A and B
Question #5
Which of the following is correct for Markov chain?
A. A Markov chain is a sequence of random variables X1, X2
B. Both B and C
C. A Markov chain is the state of a system at sequential points in time
D. A Markov chain is a sequence of fixed variables X1, X2
E. Both A and B
Solutions:
| Question #1 Answer: E | Question #2 Answer: B | Question #3 Answer: D | Question #4 Answer: A | Question #5 Answer: B |
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