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DASCA SDS Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Advanced AI & Generative AI | 20% | - Responsible AI, ethics, fairness, transparency, and compliance - Generative AI techniques, use cases, and limitations - Deep learning, neural networks, and foundation models |
| Foundational Methods & Frameworks | 25% | - Data preparation, feature engineering, and quality assurance - Machine learning algorithms, selection, and evaluation - Advanced statistics, probability, and experimental design |
| MLOps & Production Deployment | 15% | - Model governance, security, and reliability - Model lifecycle management, monitoring, and maintenance - DevOps integration, automation, and CI/CD |
| Big Data Ecosystems & Scalable Systems | 20% | - Distributed computing frameworks and cloud platforms - Data storage, processing pipelines, and governance - Scalability, performance, and optimization |
| Data Science Applications in Business | 20% | - Data science strategy and enterprise alignment - Measuring and demonstrating ROI of data science initiatives - Translating business requirements into data science problems |
DASCA Senior Data Scientist Sample Questions:
1. Bernoulli random variable is a type of:
A) Sometimes Discrete or sometimes Continuous random variable
B) Continuous random variable
C) Both A and B
D) Discrete random variable
2. Which of the following is an example of graphical model?
A) Bayesian Networks
B) Markov Random Fields
C) Both A and B
D) Both A and C
E) Geographical Networks
3. Designing an algorithm to play chess is usually an example of which type of machine learning?
A) Pattern density
B) Supervised learning
C) Clustering
D) Reinforcement learning
4. Which of the following is True about Time Series Analysis?
A) Predicting when/whether an event will occur, such as a failure of the machine generating the data
B) All of the above
C) Both A and B
D) Projecting the value of the time series at future points in time, such as a stock whose price we want to predict
E) Identifying interesting patterns in a corpus of time series data that is too large for a human to comb through
5. The DevOps movement is an outgrowth of which of the following software development methodologies?
A) Test-driven development and model-driven development
B) Promise-based algorithms
C) Waterfall
D) Agile
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: C | Question # 3 Answer: D | Question # 4 Answer: B | Question # 5 Answer: D |
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