IBM Data Engineering: Relational Database Administration
My archived summary notes from the IBM Relational Database Administration course. Covers DBA roles, backups, security, monitoring, and automation using PostgreSQL, MySQL, and Db2. While it's not my specialty, this was a useful deep dive into the systems side of working with relational databases
IBM Data Engineering: Hands-on Introduction to Linux Commands and Shell Scripting
Structured notes from IBM’s "Hands-on Introduction to Linux Commands and Shell Scripting" course. Covers terminal navigation, system commands, scripting logic, filters, redirection, environment variables, and cron job scheduling.
IBM Data Engineering: Databases and SQL for Data Science with Python
Hands-on SQL practice with real-world use cases — from basic queries to joins, views, and transactions — integrated with Python and Jupyter for data science workflows.
IBM Data Engineering: Introduction to Relational Databases
A structured summary of the IBM “Introduction to Relational Databases” course, including key takeaways, ERD design, normalization, and practical notes on MySQL and PostgreSQL. Written as personal study notes for future reference.
IBM Data Engineering: Python
Structured course notes from IBM’s Python for Data Science and AI. Includes syntax basics, functions, pandas, NumPy, file I/O, REST APIs, and web scraping. Focus on practical reference and tools for real-world data projects.
IBM Data Engineering: Introduction
A practical, high-level walkthrough of modern data engineering: tools, architecture, pipelines, wrangling, security, governance, and real-world practices. Based on the IBM Introduction to Data Engineering course, this post distills key lessons for both beginners and transitioning professionals.