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DASCA SDS Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Advanced AI & Generative AI | 20% | - Deep learning, neural networks, and foundation models - Responsible AI, ethics, fairness, transparency, and compliance - Generative AI techniques, use cases, and limitations |
| Topic 2: Foundational Methods & Frameworks | 25% | - Machine learning algorithms, selection, and evaluation - Data preparation, feature engineering, and quality assurance - Advanced statistics, probability, and experimental design |
| Topic 3: MLOps & Production Deployment | 15% | - DevOps integration, automation, and CI/CD - Model lifecycle management, monitoring, and maintenance - Model governance, security, and reliability |
| Topic 4: Big Data Ecosystems & Scalable Systems | 20% | - Distributed computing frameworks and cloud platforms - Scalability, performance, and optimization - Data storage, processing pipelines, and governance |
| Topic 5: 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 |
DASCA Senior Data Scientist Sample Questions:
1. Which of the following is NOT an example of the applications of neural networks?
A) Character recognition
B) None of the above
C) Stock market prediction
D) Traveling salesman's problem
E) Image compression
2. The spokes of the "Hub and Spoke" analytics architecture are the analytic use cases or applications that help the organization to optimize:
A) All of the above
B) Key business processes
C) Uncover new monetization opportunities
D) Both A and B
E) Deliver a more compelling customer experience
3. The grid computing environment uses a middleware to:
A) Combine computing resources
B) None of the above
C) Both A and B
D) Divide computing resources
4. A burn down chart shows:
A) The volume of work and features completed
B) The rate of reduction of budget for a project
C) The number of hours worked after dark
D) The declining energy of the team
5. OCR (Optical Character Recognition) is an application used for:
A) Big Data Analytics
B) Data mining
C) Machine learning
D) MapReduce
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: C |
