Week 1 - Dec 22-28, 2025

📅 Week Overview

Week: 1 Dates: December 22 - December 28, 2025 Total Learning Hours: 12 hours Focus Area: Professional Development - Data Engineering Fundamentals Highlight: Successfully launched portfolio website and started structured data engineering education

📊 Progress This Week

Codecademy - Data Engineer Career Path

Overall Progress: 0% → 15% (+15%)

Modules Completed:

• ✅ Welcome to the Data Engineer Career Path (0.5 hours)
• ✅ Introduction to Data Engineering (1.5 hours)
• 🚧 Python Fundamentals (In progress - 70%)

Skills Practiced:

• Python basics (variables, data types, functions)
• Understanding ETL (Extract, Transform, Load) concepts
• Data pipeline fundamentals for workflow automation
• Version control with Git for code management

Key Takeaways:

• Data engineering bridges the gap between data science and infrastructure
• Python is a powerful tool for automating repetitive broadcast infrastructure tasks
• Clean code and documentation are essential for maintainable systems

Time Invested: 8 hours

🎯 Projects Worked On

Project 1: Data Engineering Portfolio (This Site!)

Status: ✅ Completed v1.0

This Week:

• Built Hugo static site for documenting professional development journey
• Customized with modern design and responsive layout
• Deployed to Cloudflare Pages with automatic deployment pipeline
• Created initial content structure and documentation

Tech Stack: Hugo, LoveIt theme, Cloudflare Pages, Git

Professional Value:

• Demonstrates continuous learning and professional development
• Provides platform for sharing technical knowledge
• Shows initiative in modern web technologies and DevOps practices

GitHub: https://github.com/BenWaraiotoko/Bwo_Portfolio

Time Invested: 10 hours

🚧 Blockers & Solutions

Blocker 1: Hugo Theme Customization

Issue: Struggled with Hugo template syntax and theme override mechanisms

Impact: Spent 3 hours debugging CSS and layout issues

Solution:

• ✅ Resolved by thoroughly reading Hugo documentation
• ✅ Created custom CSS in assets/ directory following Hugo conventions
• ✅ Learned about Hugo pipes and resource processing

Lesson Learned: Invest time upfront in understanding framework conventions rather than trial-and-error approach. Documentation is essential.

Blocker 2: Time Management

Issue: Balancing learning time with other commitments

Impact: Felt overwhelmed trying to cover too much too quickly

Solution:

• 🚧 Created structured weekly schedule with dedicated learning blocks
• 🚧 Prioritizing Codecademy modules on weekday evenings (2 hours)
• 🚧 Portfolio/project work on weekends (4-6 hours)
• 🚧 Setting realistic weekly goals rather than overcommitting

Lesson Learned: Consistent, focused study sessions are more effective than marathon learning sessions. Quality over quantity.

💡 Key Learnings & Insights

Technical Learnings

• Python Fundamentals: Variables, data types, and functions form the foundation for data engineering work
• Git Workflow: Version control is essential for code management and collaboration
• Static Site Generators: Hugo demonstrates modern build pipelines and deployment automation

Professional Development

• Time Management: Structured learning blocks (2-hour sessions) work better than unstructured study
• Study Techniques: Codecademy’s interactive approach is effective for hands-on learning
• Documentation: Writing about learnings reinforces concepts and creates reference material
• Consistency: Daily small progress beats sporadic intensive study

📈 Metrics & Analytics

✅ Goals for Next Week

Learning Goals

• Complete Codecademy Python Fundamentals module
• Study 10 hours on data engineering concepts
• Practice Python with hands-on coding exercises
• Read pandas documentation for data manipulation

Project Goals

• Write project setup documentation
• Create first technical blog post on Python fundamentals
• Explore application of learnings to broadcast workflows

Professional Development

• Document weekly learning progress
• Update portfolio with project progress
• Research broadcast automation opportunities
• Share learnings with team (where applicable)

📚 Resources Discovered

• Real Python - Excellent Python tutorials for data engineering work
• Pandas Documentation - Essential for data manipulation
• Hugo Documentation - Static site generator for portfolio
• Codecademy Data Engineer Path - Structured learning curriculum

🎯 Long-Term Progress Check

Professional Development Goals

Milestones:

• ✅ Started Codecademy Data Engineer path (Dec 2024) - DONE!
• 🚧 Complete Codecademy (Target: Q3 2025)
• 🎯 Build 5+ ETL projects applicable to broadcast technology
• 🎯 Apply data engineering skills to enhance current broadcast infrastructure work

Progress Indicators:

• Codecademy: 15% complete (on track for Q3 2025 completion)
• Portfolio projects: 1 completed (portfolio), 1 planned (ETL pipeline)
• Technical blog posts: 0 published (goal: 1 next week)
• Skills applicable to current work: Growing foundation

🔄 Reflection

What Went Well

• Successfully launched professional development portfolio
• Made solid progress on Codecademy (15% in Week 0 and 1)
• Development environment fully configured and ready
• Created structured learning schedule and workflow

What Could Be Improved

• Need more hands-on coding practice beyond tutorials
• Should document learnings while concepts are fresh
• Balance between learning and building needs refinement
• Time allocation could be more efficient
• Don’t really appreciate the codecademy coding module, so I do the exercises on Visual Studio Code instead

Professional Growth

This week marked the beginning of a structured approach to expanding data engineering skills. The fundamentals learned (Python, Git) are directly applicable to optimizing broadcast infrastructure workflows. Looking forward to applying these concepts to real-world media technology challenges in upcoming projects.

Key Insight: Data engineering skills complement broadcast infrastructure expertise, opening opportunities for workflow automation, infrastructure monitoring optimization, and data-driven decision making in media operations.

Overall Week Rating: ⭐⭐⭐⭐ (4/5) Next Review: December 29, 2025 Status: On track 🎯