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DASCA SDS Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: MLOps & Production Deployment | 15% | - Model governance, security, and reliability - DevOps integration, automation, and CI/CD - Model lifecycle management, monitoring, and maintenance |
| Topic 2: Data Science Applications in Business | 20% | - Measuring and demonstrating ROI of data science initiatives - Translating business requirements into data science problems - Data science strategy and enterprise alignment |
| Topic 3: Big Data Ecosystems & Scalable Systems | 20% | - Scalability, performance, and optimization - Distributed computing frameworks and cloud platforms - Data storage, processing pipelines, and governance |
| Topic 4: Advanced AI & Generative AI | 20% | - Responsible AI, ethics, fairness, transparency, and compliance - Deep learning, neural networks, and foundation models - Generative AI techniques, use cases, and limitations |
| Topic 5: Foundational Methods & Frameworks | 25% | - Machine learning algorithms, selection, and evaluation - Advanced statistics, probability, and experimental design - Data preparation, feature engineering, and quality assurance |
DASCA Senior Data Scientist Sample Questions:
Which of the following is NOT an example of the applications of neural networks?
- A. Traveling salesman's problem
- B. Stock market prediction
- C. Character recognition
- D. None of the above
- E. Image compression
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Which of the following is NOT a valid section of Big Data Strategy document?
- A. Business strategy
- B. Key business initiatives
- C. Key decisions
- D. Business decisions
- E. Key business entities
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Which of the following is TRUE for "By" analysis?
- A. The "By" analysis technique reinforces the process of "thinking like a data scientist."
- B. Both B and C
- C. All of the above
- D. "By" analysis is used to create a collaborative technique to drive alignment between the business users and the data scientists to identify and brainstorm variables and metrics that might be better predictors of business performance.
- E. "By" analysis is a technique by which business subject matter experts (SMEs) and the Data Science team could collaborate to uncover new variables and metrics that might be better predictors of business performance.
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Spark is written in:
- A. Python
- B. Java
- C. Scala
- D. C
- E. C++
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Which of the following is NOT a process of Use Case?
- A. Capture the decisions that the key business stakeholders need to make in order to support the organization's key business initiatives
- B. Understand your organization's key business initiatives or business challenge
- C. Brainstorm the questions that the key stakeholders need to answer to facilitate making the decisions
- D. Brainstorm the outcomes that the key stakeholders need to answer to facilitate making the decisions
- E. Identify your key business stakeholders
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