From Business Student to Self-Taught Tech Professional: A Learning Journey
My relationship with computers started way before I knew what a “tech career” even was. Growing up with financial constraints, Linux became my gateway to technology, teaching me to squeeze performance from limited resources. This journey from necessity-driven learning to business-grade technical skills shaped my approach to both technology and problem-solving.
From Business Student to Self-Taught Tech Professional: A Learning Journey
Growing up money was tight. When I wanted to run game servers or even run applications on the weak hardware I had, Linux became my best friend. It could squeeze performance out of old machines that Windows would kill, being extremely scalable, lightweight, and versatile. That necessity taught me terminal commands, bash scripting, and how to make computers do exactly what I needed with minimal resources.
Open source software stood not only as a philosophy, but also a form of survival for me. Can’t afford Adobe Creative Suite? Learn DaVinci Resolve and GIMP. Need vector graphics? Inkscape works just fine. Want to compress videos to save storage? FFmpeg and open source tools got the job done.
I’ve been embedded with computers my whole life. Building systems from scratch, even starting a small computer building service for people in my area. Hours spent on Linux ricing to get my desktop perfect, video editing and compression, working with music software, game server management, basically any creative or technical outlet I could find with a computer, I dove into.
So when I started my Commerce degree with an Entrepreneurship focus, I already had this foundation of making technology work on a budget, and had developed strong software literacy from youth to my adulthood. The difference was now I needed to turn hobbyist computer skills into actual business-grade infrastructure and development capabilities, and invest in stronger hardware beyond gaming or leisure. Here’s how I bridged that gap.
The Foundation: Books and Structured Learning
My technical journey began with carefully selected foundational texts that provided both theoretical understanding and practical application:
Programming Fundamentals
- “Python Crash Course” by Eric Matthes - My entry point into programming, providing solid foundations in Python syntax and project-based learning
- “Automate the Boring Stuff with Python” by Albert Sweigart - Practical automation skills that immediately improved my daily workflow
- “Microservices” by Chris Richardson - Advanced architectural concepts that informed my infrastructure decisions and inspired my sysadmin ambitions
- The ODIN Project - A free full stack web development course which had taught me about 70% of what built this website and all other web ventures
Systems Administration
- “Linux Administration: The Complete Linux Bootcamp” by Andrei Dumitrescu - Comprehensive Linux foundations course, showing various advanced Linux concepts like shortcuts and bash scripting
- “Linux Administration: Build 5 Hands-on Linux Projects for Real Jobs” - Project-based learning that translated directly to homelab implementation beyond bash scripting and CLI
Infrastructure and DevOps
- “Docker & Kubernetes” by Stephen Grider - Containerization concepts that became central to my homelab architecture
- CompTIA Network+ Course by Jason Dion - Networking fundamentals essential for proper infrastructure design
- Professor Messer’s Network+ training videos - Supplemental video content reinforcing networking concepts
Hands-On Implementation: The Homelab Laboratory
Reading provided the foundation, but real learning happened through building. My homelab became my primary learning environment, where I could experiment with enterprise technologies safely. Homelabbing required stringent research of documentation, and leveraging the man(manual), apropos commands, and the Arch Linux wiki along with StackOverflow. The prime appeal of Linux is the strong documentation, many users providing and requesting solutions, working as a large community that helps one-another learn and continuously improve the platform.
Infrastructure Evolution
Starting with a basic understanding of virtualization, I progressively built:
- Proxmox VE Deployment - Chose open-source hypervisor over expensive, proprietary VMware licensing
- TrueNAS Implementation - Learned storage management, RAID configurations, and network shares, the latter two learned from computer building
- Docker Service Stack - Deployed 8+ containerized services including Nextcloud, Pi-hole, and monitoring systems
- Network Security - Implemented WireGuard VPN with DNS filtering and SSL certificate management using DuckDNS, all free
Learning Through Problem-Solving
Every service deployment taught new skills:
- Storage Permissions: Solved complex Proxmox LXC mount point issues through forum research
- Network Security: Learned from DNS security incident that exposed my server to attacks
- Service Integration: Connected TrueNAS storage to Nextcloud containers with proper SMB configuration
Programming and Automation Skills
Python Development
Beyond basic syntax, I developed practical Python skills through:
- Excel Integration: Built PyXLL-based finance calculators and ribbon interfaces for personal usage and templating
- Web Scraping: Implemented Crawl4AI for research automation of all purposes
- Data Processing: Developed scripts for business analysis and market research, using Pandas and Numpy (which guided the PyXLL calculator)
Infrastructure as Code
- Docker Compose: Created maintainable service configurations
- Container Management: Learned Portainer for GUI-based container orchestration, as Docker Engine isn’t effective on a phone
- Backup Automation: Implemented automated backup systems with proper retention policies, focusing strongly on configuration files and data
AI and Machine Learning Integration
Local AI Deployment
- Ollama with Dolphin2: Successfully deployed local LLM on AMD 6900XT despite driver limitations
- Mobile AI: Implemented Deepseek model on Samsung S24 Ultra for mobile computing
- MCP Integration: Set up Serena and Context7 for enhanced development workflows
Research Automation
- Crawl4AI Implementation: Built intelligent web crawling system for standardized research output
- AI-Enhanced Design: Used Ideogram AI to enhance hand-crafted vector logos for LureMaps branding
The Business-Tech Integration
What makes my learning unique is the constant connection between technical skills and business applications:
Market Research Technology
- SurveyMonkey Integration: Collected and analyzed 60+ responses for LureMaps market validation
- Reddit Community Sampling: Leveraged r/fishingBC for niche market research
- Excel Financial Modeling: Built comprehensive financial models with sensitivity analysis
Project Management Integration
- n8n Workflows: Automated processes and data collection over API called AIs, which I primarily used for automating server update notifications
- Trello/Jira: Managed complex projects including venture concept development, and also throughout my life for personal management
- Freemind Mapping: Visual project planning and strategic thinking
Lessons from Self-Directed Learning
What Worked Well
- Project-Based Learning: Every book was immediately applied to real projects
- Documentation Habit: Maintained detailed notes and configuration files
- Community Engagement: Forums, YouTube and Reddit provided crucial problem-solving support
- Iterative Improvement: Constantly refined and rebuilt systems with new knowledge, learning as mistakes were made
Common Pitfalls
- Hardware Planning: Gaming hardware (AMD 6900XT) has significant limitations for AI/ML workloads
- Security First: Early DNS security incident taught importance of proper configuration from start
- Backup Everything: Non-ECC RAM requires enhanced backup and monitoring practices
- Documentation: Underdocumented early work created challenges for maintenance, which over the course of deployment improved
Current Technical Capabilities
After 2+ years of dedicated self-study, I now possess:
Infrastructure & DevOps
- Proxmox VE virtualization with LXC containers and VMs
- Docker orchestration with 8+ production services
- Network security with VPN, DNS filtering, and reverse proxy
- Automated backup systems with proper retention policies
Programming & Automation
- Python for automation, data processing, and API integration
- Basic Go understanding for DevOps applications
- HTML/CSS for web development and interface design
- Shell scripting for system administration
AI & Machine Learning
- Local LLM deployment and management
- AI-enhanced research automation with Crawl4AI
- Mobile AI implementation and optimization
- MCP server integration for enhanced development workflows
The Business Advantage
This technical foundation provides unique advantages in business contexts:
Informed Decision Making
- Understanding API costs and architectural implications for LureMaps
- Realistic technology timelines and resource requirements
- Security and privacy considerations for customer data
Rapid Prototyping
- Ability to build and test concepts quickly
- Direct communication with development teams
- Understanding of technical feasibility and constraints
Cost Optimization
- Self-hosting capabilities reducing SaaS costs
- Efficient resource utilization through proper architecture
- Understanding of scaling implications and cost structures
Looking Forward
The learning journey continues with planned expansions:
Immediate Goals
- NVIDIA 4XXX+ GPU upgrade for enhanced AI capabilities per CUDA
- Learning Kubernetes and Terraform skills to further widen my skillset in DevOps
- Advanced monitoring and alerting implementation, alongside security like Wazuh
Long-term Vision
- Integration of homelab infrastructure with business ventures to offset API/server hosting costs
- Development of proprietary Crawl4AI implementations for personal usage (which is in progress)
- Expansion into cloud architecture and multi-cloud deployments and larger scale server hardware
Advice for Other Self-Taught Learners
Start with Applicable Projects, and Open Source, Documented Solutions, Not Theory
Choose technologies that solve real problems in your life. My homelab addressed genuine needs for secure remote access and family cloud storage. It also untethers your life from subscriptions, and provides you means to understand the technologies running your IoT devices beyond.
Document Everything
Maintain detailed notes, configuration files, and decision rationales. Future you will thank present you. Creating audit logs actively, day by day, or even discussing changes or mistakes made will help you in the future, especially if issues re-arise with continuous deployments.
Embrace Failure as Learning
My DNS security incident was embarrassing but taught more about network security than any book could, and showcased how perpetually aware you have to be when dealing with your network topology, cybersecurity, among others. Diligence is key, but also understanding that you will make mistakes.
Connect Learning to Career Goals
Every technical skill should connect to your professional objectives. Business students learning tech have unique advantages in understanding practical applications, and it can save you money, allow you to be responsible for technical aspects most business owners shy away from, and glean insight on what runs your business’ infrastructure.
Community is Crucial
Forums, Reddit, and documentation are invaluable. Don’t hesitate to ask questions and share your solutions.
The combination of formal business education with self-taught technical skills creates unique opportunities in today’s technology-driven business environment. While the learning curve is steep, the ability to bridge business requirements with technical implementation provides significant competitive advantages in entrepreneurship and innovation. And as most of these services are free and open source, the bar of entry is only the time you are willing to commit.