Python Institute PCAD-31-02受験対策書、PCAD-31-02合格内容

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Python Institute PCAD-31-02 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Visualization and Communication	15%	- Visualization principles and best practices 1. Audience-focused presentation 2. Choosing appropriate chart types 3. Color, layout and clarity - Visualization with Matplotlib and Seaborn 1. Heatmaps, pair plots and correlation matrices 2. Customization and styling 3. Line, bar, scatter, histogram, box plots - Data storytelling and reporting 1. Structuring insights and conclusions 2. Written and verbal presentation techniques
Topic 2: Data Exploration and Statistical Analysis	25%	- Descriptive statistics 1. Correlation and covariance analysis 2. Frequency distributions and percentiles 3. Measures of central tendency and dispersion - Exploratory data analysis 1. Identifying patterns, trends and outliers 2. Feature selection and dimensionality reduction basics - Inferential statistics 1. Hypothesis testing and confidence intervals 2. Probability concepts and distributions 3. Statistical significance and interpretation
Topic 3: Data Acquisition and Preprocessing	30%	- Data collection, integration and storage 1. Data integration and merging 2. Data formats and storage systems 3. Data collection methods and sources - Data preparation with Pandas and NumPy 1. Data reshaping and aggregation 2. Data structures: Series, DataFrame, ndarray 3. Indexing, filtering, sorting and grouping - Data cleaning and validation 1. Handling missing, duplicate and invalid values 2. Quality assurance and validation techniques 3. Data standardization and transformation
Topic 4: Data Modeling and Machine Learning Basics	20%	- Supervised learning fundamentals 1. Classification: logistic regression, k-NN, decision trees 2. Model training, testing and evaluation 3. Regression: linear, multiple, polynomial - Model performance and optimization 1. Overfitting, underfitting and generalization 2. Hyperparameter tuning basics 3. Accuracy, precision, recall, F1-score
Topic 5: SQL and Database Integration	10%	- Relational database concepts 1. Tables, keys, relationships and normalization - Python-database connectivity 1. Error handling and best practices 2. Executing queries and retrieving results 3. Connecting to SQLite, MySQL or PostgreSQL - SQL querying 1. SELECT, WHERE, JOIN, GROUP BY, aggregate functions 2. Subqueries and filtering

>> Python Institute PCAD-31-02受験対策書 <<

信頼できるPCAD-31-02受験対策書 & 合格スムーズPCAD-31-02合格内容 | ユニークなPCAD-31-02テスト資料 Python Institute Certified Associate Data Analyst with Python (PCAD-31-02)

優れた学習プラットフォームには、豊富な学習リソースがあるだけでなく、最も本質的なものが非常に重要であり、ユーザーにとって最も直感的なものも不可欠です。 PCAD-31-02テスト資料はプロの編集チームであり、各テスト製品のレイアウトと校正の内容は経験豊富なプロが実施するため、細かい組版と厳格なチェックのエディターにより、最新のPCAD-31-02試験トレントが各ユーザーのページに表示されます更新し、あらゆる種類のPCAD-31-02学習教材の精度が非常に高いことを保証します。

Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) 認定 PCAD-31-02 試験問題 (Q144-Q149):

質問 # 144
Which actions are considered part of basic data validation tasks in Python using Pandas?
(Choose two)

A. Sorting the data frame by index
B. Confirming numeric columns contain only integers
C. Checking for duplicate rows
D. Replacing NULL values with placeholders

正解：B、C

質問 # 145
Which of the following improves the readability of a spreadsheet used for collaborative data analysis?

A. Adding freeze panes to lock header rows
B. Using colored fonts to highlight every cell
C. Removing gridlines from all sheets
D. Converting numeric values into images

正解：A

質問 # 146
Which Python control structures are commonly used for data filtering and iterative operations in real-world analytics tasks?
(Choose two)

A. match-case statements
B. while loops
C. list comprehensions
D. decorators

正解：B、C

質問 # 147
How would you extract the last three rows of a DataFrame df using position-based indexing?

A. df.loc[-3:]
B. df.iloc[-3:]
C. df[-3]
D. df.tail(3)

正解：B

質問 # 148
Which type of regression is most appropriate when the response variable is categorical, such as predicting customer churn (Yes/No)?

A. Polynomial regression
B. Decision tree regression
C. Linear regression
D. Logistic regression

正解：D

質問 # 149
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