PDF Version DemoPython Institute PCAD-31-02 Exam Overview:
| Certification Vendor: | Python Institute |
| Exam Name: | Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) |
| Exam Number: | PCAD-31-02 |
| Passing Score: | 70% |
| Exam Format: | Multiple Choice, Multiple Select, Fill in the Blank, Code Completion |
| Related Certifications: | PCEP - Certified Entry-Level Python Programmer PCAP - Certified Associate in Python Programming |
| Real Exam Qty: | 40 |
| Certificate Validity Period: | No expiration (lifetime validity) |
| Exam Price: | $295 USD |
| Exam Duration: | 65 minutes |
| Available Languages: | English |
| Sample Questions: | Python Institute PCAD-31-02 Sample Questions |
| Exam Way: | Online proctored exam through Pearson VUE testing centers |
| Pre Condition: | PCEP certification is recommended but not required. Basic Python programming knowledge is expected. |
| Official Syllabus URL: | https://pythoninstitute.org/certifications/pcad |
Python Institute PCAD-31-02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Working with Data Using Python Libraries | 30% | - Pandas Library
|
| Topic 2: Applied Data Analysis Projects | 20% | - Exploratory Data Analysis (EDA)
|
| Topic 3: Data Analysis Fundamentals | 20% | - Introduction to Data Analysis
|
| Topic 4: Python Programming for Data Analysis | 30% | - File Operations
|
Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions:
1. Which operation would most efficiently apply element-wise multiplication to two NumPy arrays of equal size?
A) numpy.outer()
B) array1.dot(array2)
C) array1 * array2
D) numpy.matrix()
2. Which method is best suited to transform inconsistent entries such as "N/A", "missing", and empty strings into a standard missing value representation in a Pandas DataFrame?
A) df.replace()
B) df.rename()
C) df.dropna()
D) df.sort_values()
3. Which practices are considered part of professional Python scripting standards?
(Choose two)
A) Avoiding use of modules and libraries
B) Using consistent indentation and naming conventions
C) Avoiding error handling to keep code clean
D) Including in-line comments and docstrings
4. Which Python feature allows the reuse of logic in different data processing steps, reducing duplication and improving maintainability?
A) Global variables
B) Tuple unpacking
C) Custom functions
D) Lambda functions
5. Which conditions typically necessitate data normalization or scaling before analysis?
(choose two)
A) Presence of duplicate data
B) Features with different units and scales
C) Distance-based modeling algorithms
D) Boolean feature encoding
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: A | Question # 3 Answer: B,D | Question # 4 Answer: C | Question # 5 Answer: B,C |
We are confident about the products and aim to help you pass with ease. In case of failure, we will provide a no hassle full money back guarantee for the purchasing fee.
978 Customer Reviews
Quality and ValueITbraindumps Practice Exams are written to the highest standards of technical accuracy, using only certified subject matter experts and published authors for development - no all study materials.
Tested and ApprovedWe are committed to the process of vendor and third party approvals. We believe professionals and executives alike deserve the confidence of quality coverage these authorizations provide.
Easy to PassIf you prepare for the exams using our ITbraindumps testing engine, It is easy to succeed for all certifications in the first attempt. You don't have to deal with all dumps or any free torrent / rapidshare all stuff.
Try Before BuyITbraindumps offers free demo of each product. You can check out the interface, question quality and usability of our practice exams before you decide to buy.