Non-Brand Data

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October 2026

Build Your Own Practice Dataset in Python with Faker
Create fictional customer and transaction tables for your next Python and SQL exercise
 • Cornellius Yudha Wijaya
What Makes a Good Data Science Portfolio in the Age of AI?
Something you might overlook but important in the current era
 • Cornellius Yudha Wijaya
Building an Interactive Data Analysis Notebook With marimo and DuckDB
Learn to build modern dashboard in a simple way
 • Cornellius Yudha Wijaya
Building a Multi-Asset Market Monitor with TickerLayer
Understand market data and learn how to work with it in Python
 • Cornellius Yudha Wijaya
Getting Started With TimesFM-3 for Time-Series Forecasting
Learn how to use TimesFM-3 for time-series prediction with a Python example.
 • Cornellius Yudha Wijaya
Can TabPFN-3.5 Compete With Traditional Machine Learning Models?
Compare four models on two datasets to understand their prediction performance and runtime.
 • Cornellius Yudha Wijaya
Module 14: Writing the results and recommendations
A SQL result can be correct and still make a weak report. The table gives the numbers, but the reader still needs to know what they mean and what they…
 • Cornellius Yudha Wijaya
Module 13: When a SQL query needs optimization
In this module, we will learn how to read a PostgreSQL query plan and decide whether an index is worth keeping.
 • Cornellius Yudha Wijaya
Module 12: Checking whether your result is right
Let's learn how to check a SQL result before we use it in a report or recommendation.
 • Cornellius Yudha Wijaya
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