Which of the following programming languages are most widely used by data scientists?
Correct Answer: B
Detailed Answer in Step-by-Step Solution: * Objective: Identify top languages for data science. * Evaluate Options: * A: C/C++-Low-level, less common for data tasks. * B: Python (ML, libraries), R (stats), SQL (data)-Industry standards. * C: Java (enterprise), JavaScript (web)-Not data-focused. * Reasoning: B aligns with data science tools (e.g., pandas, ggplot). * Conclusion: B is correct. OCI documentation highlights "Python, R, and SQL as the most widely used languages in Data Science for modeling, analysis, and data querying." C/C++ (A) and Java/JS (C) are less prevalent-B matches OCI's notebook support and industry trends. Oracle Cloud Infrastructure Data Science Documentation, "Supported Languages".
1z0-1110-25 Exam Question 67
Which OCI service provides a scalable environment for developers and data scientists to run Apache Spark applications at scale?
Correct Answer: D
Detailed Answer in Step-by-Step Solution: * Objective: Identify the OCI service for scalable Spark applications. * Evaluate Options: * A: Data Science-ML platform, not Spark-focused. * B: Anomaly Detection-Specific ML service, not general Spark. * C: Data Labeling-Annotation tool, not Spark-related. * D: Data Flow-Managed Spark service for big data. * Reasoning: Data Flow is OCI's Spark execution engine. * Conclusion: D is correct. OCI Data Flow "provides a fully managed environment to run Apache Spark applications at scale, ideal for data processing and ML tasks." Data Science (A) supports Spark in notebooks, but Data Flow (D) is the dedicated, scalable solution-B and C are unrelated. Oracle Cloud Infrastructure Data Flow Documentation, "Overview".
1z0-1110-25 Exam Question 68
You have just received a new dataset from a colleague. You want to quickly find out summary information about the dataset, such as the types of features, the total number of observations, and distributions of the data. Which Accelerated Data Science (ADS) SDK method from the ADSDataset class would you use?
Correct Answer: D
Detailed Answer in Step-by-Step Solution: * Objective: Get summary info from an ADSDataset object. * Evaluate Options: * A: Correlation matrix-Specific, not full summary. * B: Converts to XGBoost-Not for summary. * C: Executes computation-Not summary-focused. * D: Displays summary (types, counts, dist)-correct. * Reasoning: show_in_notebook() provides a comprehensive overview. * Conclusion: D is correct. OCI documentation states: "show_in_notebook() (D) from ADSDataset displays a summary of the dataset, including feature types, observation count, and distributions, in a notebook." A is partial, B and C are unrelated-only D meets the need per ADS SDK. Oracle Cloud Infrastructure ADS SDK Documentation, "ADSDataset Methods".
1z0-1110-25 Exam Question 69
What is the name of the machine learning library used in Apache Spark?
Correct Answer: A
Detailed Answer in Step-by-Step Solution: * Objective: Identify Apache Spark's ML library. * Understand Spark: A big data framework with specialized libraries. * Evaluate Options: * A: MLib (correctly MLlib)-Spark's machine learning library. * B: GraphX-Graph processing, not ML. * C: Structured Streaming-Streaming data, not ML. * D: HadoopML-Not a Spark library (Hadoop-related). * Reasoning: MLlib is Spark's official ML toolkit (e.g., regression, clustering). * Conclusion: A is correct (noting "MLib" should be "MLlib"). OCI Data Science supports Spark via Data Flow, where "MLlib (Machine Learning library) provides scalable ML algorithms." GraphX (B) and Structured Streaming (C) serve other purposes, and HadoopML (D) isn't real-MLlib (A) is the standard, despite the typo. Oracle Cloud Infrastructure Data Flow Documentation, "Apache Spark MLlib".
