Free Python Institute PCED-30-02 Exam Dumps Questions & Answers

You have collected sales data and want to compute the average using the NumPy library.
Which option correctly shows how to install NumPy and use it in your code to perform this task?

• A.To install NumPy:
  from pip install numpy
  Then run this code:
  import numpy as np
  data = np.array([10, 20, 30])
  print(np.mean(data))
• B.To install NumPy:
  pip install numpy as np
  Then run this code:
  import np
  data = np.array([10, 20, 30])
  print(np.mean(data))
• C.To install NumPy:
  pip install numpy
  Then run this code:
  import numpy as np
  data = numpy.arr([10, 20, 30])
  print(numpy.mean(data))

A healthcare provider analyzes patient records to determine that appointment cancellations spike during weather alerts and flu season.
What type of analytics is this?

• A.Descriptive analytics - it reports appointment numbers across past seasons.
• B.Prescriptive analytics - it automates patient rescheduling based on cancellation patterns.
• C.Diagnostic analytics - it identifies reasons behind patterns in patient behavior.
• D.Predictive analytics - it uses weather and illness trends to forecast future cancellations.

Which task is traditionally or typically performed by a data analyst, and not by a data scientist or analytics specialist? Select the best answer.

• A.Creating summary tables and charts to describe patterns in historical data.
• B.Developing machine learning algorithms to predict user behavior.
• C.Designing a data pipeline to ingest and process real-time sensor data.
• D.Recommending pricing strategies using predictive modeling and A/B testing.

You are developing a temperature control module for a laboratory incubator. Your objectives are to:
- generate timestamps every 10 minutes over a 3-hour span (i.e., 0 to 180 minutes), and
- simulate five evenly spaced target temperatures between 35.0°C and 37.0°C for system calibration.
Which code snippet correctly produces both sequences using NumPy? Select the best answer.
import numpy as np

• A.timestamps = np.arange(0, 180, 10)
  target_temps = np.linspace(35.0, 37.0, 4)
  import numpy as np
• B.timestamps = np.linspace(0, 181, 10)
  target_temps = np.arange(35.0, 37.0, 0.5)
  import numpy a3 np
• C.timestamps = np.arange(0, 181, 10)
  target_temps = np.linspace(35.0, 37.0, 5)
• D.timestamps = np.linspace(0, 180, 10)
  target_temps = np.arange(35.0, 37.0, 5)
  import numpy as np

An e-commerce site records every product view and purchase.
Which of the following best describes how these logs become marketing insights?

• A.Raw event logs are filtered, aggregated, and formatted into summaries - like total visits per category - which then provide traffic reports.
• B.Raw event logs are validated, organized, and compiled into datasets - like timestamped user actions - which then support system debugging.
• C.Raw event logs are structured, analyzed, and interpreted into information - like conversion rates by product - which then builds knowledge of customer preferences.
• D.Raw event logs are stored, archived, and indexed - like by user ID and session - which then facilitate audit trails.