Learning SQL on a Smartphone: My Journey to Becoming a Data Analyst Without a Laptop
Why I Refuse To Wait Until Graduation To Start Building My Future In Tech My name is Bassey. I'm a 300-level Microbiology student at the University of Uyo, Akwa Ibom State, Nigeria. Like many students, I started university with the hope of building a successful career after graduation. But as I progressed in my studies, I began thinking seriously about my future. I started asking myself difficult…
Bassey, a 300-level Microbiology student at the University of Uyo in Akwa Ibom State, Nigeria, is determined to pursue a career in tech despite the challenges posed by not having a laptop. His journey began when he discovered his passion for data analytics, a field that aligns with his love for research, problem-solving, and helping others.
To start his data analytics learning journey, Bassey chose to focus on SQL, using various online platforms like Mimo, SQLBolt, SQLZoo, and DataLemur. He has been practicing for about three months, despite the limitations of using a smartphone for technical learning. Bassey's ultimate goal is to transition from SQL exercises to building practical projects, mastering Excel, Power BI, and Python, and eventually using these skills to develop solutions to real-world problems.
However, he lacks the necessary laptop to effectively advance his skills. Bassey has applied for various technology opportunities and laptop-support programs but has not yet secured a suitable device. He is actively seeking assistance from individuals, technology companies, organizations, and data professionals who can help him obtain a laptop.
Bassey hopes to find a legitimate laptop donation or sponsorship program, an organization that supports aspiring data analysts, or someone who can provide guidance and mentorship. He has created a laptop-support campaign on Donate-ng, where every contribution will bring him closer to acquiring the laptop needed for his continued learning and career development.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
