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WorksheetsAI_Driven_Retail_Intelligence
Total questions: 20
Worksheet time: 10mins
I. Python & SQL Technical Skills
Which Pandas method is used to merge two DataFrames based on a common column?
A) concat()
B) join()
C) merge()
D) combine()
You need to extract daily sales data from an ERP database. Which SQL query achieves this?
A) SELECT * FROM sales WHERE date = '2023-10-01';
B) GET sales WHERE date IS '2023-10-01';
C) EXTRACT sales ON date='2023-10-01';
D) FILTER sales BY date='2023-10-01';
How would you handle missing values in a Pandas DataFrame df for the 'price' column?
A) df.dropna(subset=['price'])
B) df['price'].fillna(0)
C) df.delete('price')
D) df.replace('price', np.nan)
To connect Python to an Odoo ERP API, which library is most appropriate?
A) requests
B) odoo-client
C) sqlalchemy
D) tensorflow
What does this SQL clause do? GROUP BY category HAVING SUM(sales) > 1000
A) Filters categories before grouping
B) Groups sales by category and excludes sums ≤1000
C) Sorts categories by sales descending
D) Aggregates sales without filtering
A sudden 30% sales drop in a region is observed. What should you investigate first?
A) Train a new neural network
B) Check inventory stockouts and promotions
C) Rebuild the entire dashboard
D) Run a cluster analysis
Which metric best measures promotion effectiveness?
A) Total website visits
B) Margin per unit sold during promo
C) Social media likes
D) Employee overtime hours
What does "SKU rationalization" aim to optimize?
A) Warehouse temperature
B) Product assortment profitability
C) Customer service scripts
D) Delivery truck routes
III. Statistics & Machine Learning
In demand forecasting, which technique handles weekly seasonality?
A) K-means clustering
B) ARIMA models
C) Logistic regression
D) Decision trees
A model predicting "high-value customers" has 95% accuracy but misses 80% of actual high-value users. What is the issue?
A) High precision
B) Low recall
C) Overfitting
D) Perfect performance
Which test determines if a price change affected sales significantly?
A) Chi-square test
B) T-test
C) K-means clustering
D) PCA
How do you detect bias in an inventory allocation model?
A) Track API response times
B) Analyze stock distribution by store demographics
C) Monitor cloud compute costs
D) Count missing values
IV. Data Visualization & Communication
To show monthly sales trends and anomalies simultaneously, which PowerBI visual is ideal?
A) Pie chart
B) Scatter plot
C) Line chart with anomaly detection
D) Table
A stakeholder asks, "Why did loyalty program participation drop?" How should you respond?
A) Share raw SQL queries
B) Show a dashboard comparing participation pre/post policy changes
C) Email a Jupyter Notebook
D) Schedule a model retraining session
V. Critical Thinking & Problem Translation
"Reduce overstock costs" translates to which measurable AI task?
A) Build a chatbot
B) Predict demand elasticity for slow-moving items
C) Create employee training videos
D) Audit supplier contracts
A vague goal: "Improve customer experience." What data question aligns with this?
A) "Which store has the cheapest products?"
B) "What is the correlation between checkout wait times and repeat purchases?"
C) "How many employees work night shifts?"
D) "Calculate total annual revenue."
VI. Ethics & Deployment
An AI model recommends higher prices in low-income areas. What ethical risk exists?
A) Model drift
B) Bias in pricing
C) API latency
D) Cloud costs
To monitor a deployed demand forecasting model, you track:
A) User login counts
B) Prediction accuracy vs. actual sales over time
C) Dashboard color schemes
D) ERP license renewal dates
VII. Tool Proficiency
What does PromptBi simulate in this course?
A) ERP data extraction
B) AI model deployment pipelines
C) Payroll processing
D) Social media ads
In TensorFlow, what is the purpose of a Sequential model?
A) Process SQL joins
B) Handle time-series data
C) Build neural networks layer-by-layer
D) Clean retail datasets
