Python Institute PCAD-31-02 Questions & Answers - in .pdf
- Vendor: Python Institute
- Exam Code: PCAD-31-02
- Exam Name: Python Institute Certified Associate Data Analyst with Python (PCAD-31-02)
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- Exam Code: PCAD-31-02
- Exam Name: Python Institute Certified Associate Data Analyst with Python (PCAD-31-02)
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Python Institute PCAD-31-02 Exam Overview:
| Certification Vendor: | Python Institute |
|---|---|
| Exam Name: | Python Institute Certified Associate Data Analyst with Python |
| Exam Number: | PCAD-31-02 |
| Passing Score: | 75% |
| Exam Format: | Multiple-select questions, Single-select questions |
| Exam Price: | $195 USD |
| Related Certifications: | PCAP – Certified Associate in Python Programming PCED – Certified Associate in Python Engineering PCEP – Certified Entry-Level Python Programmer |
| Exam Duration: | 60 minutes |
| Certificate Validity Period: | 6 years |
| Real Exam Qty: | 48 |
| Available Languages: | Spanish, German, Japanese, French, English |
| Recommended Training: | Edube Interactive Learning Platform PCAD Official Syllabus and Resources |
| Exam Registration: | Python Institute Official Registration |
| Sample Questions: | Python Institute PCAD-31-02 Sample Questions |
| Exam Way: | Online proctored or onsite at authorized test centers |
| Pre Condition: | No mandatory prerequisites; recommended: PCAP – Certified Associate in Python Programming or equivalent knowledge, basic understanding of statistics and data concepts |
| Official Syllabus URL: | https://pythoninstitute.org/pcad |
Python Institute PCAD-31-02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Exploration and Statistical Analysis | 25% | - Inferential statistics
|
| Topic 2: Data Modeling and Machine Learning Basics | 20% | - Model performance and optimization
|
| Topic 3: Data Acquisition and Preprocessing | 30% | - Data cleaning and validation
|
| Topic 4: SQL and Database Integration | 10% | - SQL querying
|
| Topic 5: Data Visualization and Communication | 15% | - Visualization principles and best practices
|
Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions:
Question 1
Which of the following is the most suitable data structure in Python for representing a tabular row with column names?
A. list
B. set
C. tuple
D. dictionary
Question 2
What is a key assumption of linear regression that distinguishes it from logistic regression?
A. Predictors must be independent
B. The relationship between predictors and the outcome is linear
C. Output values must be binary
D. The target variable is unordered categorical
Question 3
What result will the following Pandas expression return: df['Age'].notnull().all()?
A. Returns True if at least one value in 'Age' is not NULL
B. Returns the number of NULL values in 'Age'
C. Returns True if all values in 'Age' are not NULL
D. Returns True if all values in 'Age' are NULL
Question 4
When merging two Pandas DataFrames using a common key, which parameters are essential to ensure accurate and conflict-free results?
(Choose two)
A. suffixes
B. ignore_index
C. dropna
D. on
Question 5
Which term best describes the process of combining customer data from multiple systems into a single unified dataset?
A. Data warehousing
B. Data normalization
C. Data binning
D. Data integration
Solutions:
| Question 1 Answer: D | Question 2 Answer: B | Question 3 Answer: C | Question 4 Answer: A,D | Question 5 Answer: D |
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