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Python Institute PCED-30-02 Exam Syllabus Topics:
Section
Objectives
Topic 1: Python Programming Fundamentals
- Basic syntax and data types
1. Variables and operators
2. Control flow basics
Topic 2: Basic Statistics for Data Analysis
- Descriptive statistics
1. Variance and standard deviation
2. Mean, median, mode
Topic 3: Data Handling and Processing with Python
- Working with data structures
1. Iterating and transformations
2. Lists, tuples, dictionaries
- Data manipulation libraries
1. NumPy basics
2. Pandas fundamentals
Topic 4: Data Analysis and Visualization
- Data visualization
1. Matplotlib basics
2. Plot interpretation
- Data cleaning and preprocessing
1. Data transformation techniques
2. Missing values handling
Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions:
A Python script evaluates the expression len(" "). The programmer assumes it might be zero because it looks empty. What will the actual result be?
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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. Predictive analytics - it uses weather and illness trends to forecast future cancellations.
B. Prescriptive analytics - it automates patient rescheduling based on cancellation patterns.
C. Diagnostic analytics - it identifies reasons behind patterns in patient behavior.
D. Descriptive analytics - it reports appointment numbers across past seasons.
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You are creating a presentation slide to communicate findings about student stress levels across four categories over a six-month period. You include the following line graph in your presentation: Your goal is to help your audience clearly understand trends in stress levels over time. What is the highest problem with this visual presentation? Select the best answer.
A. The graph doesn't explain what each stress level means or show exact values for each month, which limits interpretation.
B. The chart should be in 3D format to show depth and highlight differences more clearly.
C. The lines are too light and similar in color, making it difficult to distinguish between trends.
D. The months should be replaced with week numbers to provide more detailed insight.
E. The font used in the chart is hard to read; using larger, uppercase text would improve clarity.
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A Python script checks membership using "a" in "apple". The developer wants to understand how membership works for strings. What result will this expression produce?
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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: pip install numpy as np Then run this code: import np data = np.array([10, 20, 30]) print(np.mean(data))
B. 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))
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))
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discussion
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