Python Learning Roadmap
A focused Python path with Boot.dev chapters, ITI Arabic, Harvard CS50P, original exercises and three data project briefs.
Explore the resourceMy learning hubs, labs, and technical notes. A growing collection of the ideas I want to understand well enough to explain.
A focused Python path with Boot.dev chapters, ITI Arabic, Harvard CS50P, original exercises and three data project briefs.
Explore the resourceA personal 24-week path from Python, SQL, BI, and n8n to customer-facing engineering delivery. Interactive skill map, weekly plans, projects, and architecture diagrams.
Explore the resourceA connected Excel learning hub with lessons, practice, Power Query, formulas, and resources.
Explore the resourceA data-career and learning project built around practical roadmaps and resources.
Explore the resourceA self-paced route through SQL, Python, analytics engineering, pipelines, and portfolio practice.
Explore the resourceNotes on macros, debugging, UserForms, Office integration, and automation architecture.
Explore the resourceA course-based lab repository exploring protocols, TLS, Docker, and database access.
Explore the resourceHands-on exploration of processes, virtual memory, caches, buffers, and copy-on-write.
Explore the resourceAn interactive learning roadmap for AI automation, featuring n8n and adjacent automation tools as structured data-tea products. · Built with Manus
Explore the resourceAn end-to-end data engineering pipeline that scrapes real-time job market data across multiple platforms, extracts technical skills using Gemini 2.0 Flash, and powers an interactive Serverless Next.js web application to generate sequential learning roadmaps. Includes a GitHub Actions cron job for daily market data updates across 15+ job profiles.
Explore the resourceRevisited Excel fundamentals and passed the course exam on a second attempt. First taken during the 2025 free-access period; retaken in 2026 as structured revision.
Essentials, Integrations, and In Practice: AI, Testing & Best Practices.
Completed course with practical networking labs.
28 sessions covering data analytics.
AI-focused training.
Web Scraping and API Fundamentals in Python; Introduction to Jupyter, Data Warehousing, and Databricks.
Business intelligence training.
SQL for Data Science; Relational Database Basics; Python Basics for Data Science; Analyzing Data with Excel; Data Engineering Basics for Everyone; Data Analytics Basics for Everyone.