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DASCA SDS Practice Q&A's

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DASCA SDS Exam Syllabus Topics:

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

DASCA Senior Data Scientist Sample Questions:

1. In regression, the principle of machine learning is used to optimize the parameters to:

A) Minimize the approximation error
B) Both A and B
C) Calculate the closest possible outcomes
D) None of the above


2. What is DevOps?

A) Software Development
B) Software Operations
C) Quality Assurance
D) All


3. Which of the following is correct about customer lifetime value (CLTV)?
i. Most organizations determine the current customer lifetime value (CLTV) based on historic sales over past
12 to 18 months
ii. The goal of the CLTV score is to help marketing and store personnel to determine the "value" of a customer

A) Both i and ii
B) Only i
C) Only ii


4. Which of the following is TRUE for "By" analysis?

A) Both B and C
B) "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.
C) All of the above
D) "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.
E) The "By" analysis technique reinforces the process of "thinking like a data scientist."


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) Agile
D) Waterfall


Solutions:

Question # 1
Answer: B
Question # 2
Answer: D
Question # 3
Answer: A
Question # 4
Answer: C
Question # 5
Answer: C

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