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Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
Python Basics for Data Analysis32.5%- Introduction to NumPy
  • 1. Arrays, basic operations, indexing, slicing
- Core Python syntax and data types
  • 1. Lists, tuples, sets, dictionaries
  • 2. Variables, numbers, strings, booleans
- Built-in modules for data work
  • 1. math, statistics, datetime, collections, csv
- Control flow and functions
  • 1. Basic exception handling
  • 2. Conditional statements, loops, iteration
  • 3. Defining and calling functions, parameters, return values
Introduction to Data and Data Analysis Concepts22.5%- Definition and classification of data
  • 1. Difference between data, information, and knowledge
  • 2. Process of turning raw data into insights
  • 3. Role of data in decision-making and business
- Data types and measurement scales
  • 1. Qualitative vs quantitative data
  • 2. Nominal, ordinal, interval, ratio scales
- Basic statistical concepts
  • 1. Descriptive vs inferential statistics
  • 2. Population, sample, variable, observation
- Data lifecycle and ethical considerations
  • 1. Data collection, storage, processing, usage, and sharing
  • 2. Privacy, security, bias, and fairness in data
Data Visualization and Communication20%- Principles of effective data visualization
  • 1. Clarity, simplicity, and accuracy
  • 2. Choosing appropriate chart types
- Interpreting and presenting results
  • 1. Deriving conclusions and insights
  • 2. Reporting findings clearly and concisely
- Creating basic visualizations
  • 1. Line charts, bar charts, histograms, pie charts
  • 2. Using text and simple plotting tools
Working with Data and Performing Simple Analysis25%- Data cleaning and preparation
  • 1. Formatting and standardizing values
  • 2. Filtering, sorting, transforming data
  • 3. Handling missing values, duplicates, and errors
- Data acquisition and loading
  • 1. Importing data from external sources
  • 2. Reading text, CSV, and structured files
- Data aggregation and grouping
  • 1. Summarizing and grouping datasets
- Exploratory data analysis
  • 1. Identifying patterns, trends, and outliers
  • 2. Calculating mean, median, mode, range, variance, standard deviation

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q34-Q39):

NEW QUESTION # 34
A dictionary is defined as d = {"a":1, "b":2}. The programmer accesses d["c"]. What happens when this line executes?

Answer: C

Explanation:
Accessing a non-existent key using square brackets raises a KeyError. Python does not automatically create missing keys, so the program will terminate unless the exception is handled.


NEW QUESTION # 35
Which task is traditionally or typically performed by a data analyst, and not by a data scientist or analytics specialist? Select the best answer.

Answer: B

Explanation:
Creating summary tables and charts to describe patterns in historical data is a core responsibility of a data analyst, focusing on descriptive analytics and reporting rather than building predictive models, machine learning systems, or engineering data pipelines.


NEW QUESTION # 36
A program uses while False: followed by print statements inside the loop. The developer expects output. What will actually happen during execution?

Answer: C

Explanation:
The condition False is evaluated before entering the loop. Since it is always false, the loop body is never executed, and no output is produced.


NEW QUESTION # 37
A list is defined as [1, 2, 3]. The programmer uses the method .append([4, 5]). What will the resulting list look like after execution?

Answer: C

Explanation:
The append() method adds its argument as a single element. Therefore, the list [4, 5] is added as one nested list, resulting in [1, 2, 3, [4, 5]].


NEW QUESTION # 38
Which of the following code snippets will output Truefor both printfunctions by correctly identifying the type of each variable and performing valid operations?

Answer: C

Explanation:
Adding an integer and a float produces a float result, so checking that the type of the sum is float evaluates to True. The variable holding 3.0 is a float, so the isinstance check for float also evaluates to True.


NEW QUESTION # 39
......

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