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DASCA SDS

SDS

Exam Code: SDS

Exam Name: Senior Data Scientist

Updated: Sep 17, 2026

Q&A Number: 87 Q&As

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SDS Online Test Engine

Online SDS Test Engine supports Windows / Mac / Android / iOS, etc., because it is the software based on WEB browser.

DASCA SDS Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Machine Learning at Scale25-30%- Unsupervised Learning
  • 1. Dimensionality Reduction
  • 2. Anomaly Detection
  • 3. Clustering Algorithms
- Deep Learning Fundamentals
  • 1. Convolutional Networks
  • 2. Neural Networks
  • 3. Recurrent Networks
- Supervised Learning
  • 1. Support Vector Machines
  • 2. Time Series Forecasting
  • 3. Ensemble Methods
Topic 2: Big Data Engineering15-20%- Distributed Computing
  • 1. Hadoop Ecosystem
  • 2. Data Pipelines
  • 3. Apache Spark
- Cloud Computing for Data Science
  • 1. Serverless Architectures
  • 2. Containerization
  • 3. AWS/Azure/GCP Services
Topic 3: Advanced Statistical Modeling20-25%- Regression Analysis
  • 1. Regularization Techniques
  • 2. Generalized Linear Models
  • 3. Linear and Logistic Regression
- Statistical Inference
  • 1. Bayesian Methods
  • 2. Hypothesis Testing
  • 3. Confidence Intervals
Topic 4: Foundations of Data Science15-20%- Data Science Ethics
  • 1. Bias and Fairness
  • 2. Privacy and Confidentiality
  • 3. Transparency and Explainability
- Data Science Lifecycle
  • 1. Data Collection and Preparation
  • 2. Model Building and Evaluation
  • 3. Problem Formulation
  • 4. Deployment and Monitoring
Topic 5: Data Visualization and Communication10-15%- Visualization Principles
  • 1. Dashboard Design
  • 2. Storytelling with Data
- Tools and Technologies
  • 1. Python Visualization Libraries
  • 2. Tableau/Power BI

DASCA Senior Data Scientist Sample Questions:

Question #1
Which of the following statements is correct?

A. Apache claimed that Spark is able to run parallel jobs 1000 times faster in memory and 100 times faster on disk in comparison to the traditional Hadoop MapReduce
B. Apache claimed that Spark is able to run parallel jobs 50 times faster in memory and 5 times faster on disk in comparison to the traditional Hadoop MapReduce
C. Apache claimed that Spark is able to run parallel jobs 100 times faster in memory and 10 times faster on disk in comparison to the traditional Hadoop MapReduce
D. Apache claimed that Spark is able to run parallel jobs 10 times faster in memory and 100 times faster on disk in comparison to the traditional Hadoop MapReduce


Question #2
The aim of developing Scribe was to offer reliability with using:

A. High disk space usage
B. Complex protocols
C. Extensive protocols
D. None of the above


Question #3
ElementTree sub-library gives us direct access to:

A. Delete tree of the XML
B. Insert tree of the XML
C. Parse tree of the XML
D. None of the above
E. Copy tree of the XML


Question #4
Spark is written in:

A. Python
B. Java
C. C++
D. C
E. Scala


Question #5
What is the agenda of discussion at a "stand up" meeting of an Agile team?

A. What they accomplished the previous day
B. Any roadblocks they are running into
C. What they are planning to do today
D. Both A and B
E. All of the above


Solutions:

Question #1
Correct Answer: C
Question #2
Correct Answer: D
Question #3
Correct Answer: C
Question #4
Correct Answer: E
Question #5
Correct Answer: E

1184 Customer ReviewsCustomers Feedback (* Some similar or old comments have been hidden.)

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