Augustina Ginikawa - MSc IT for the Oil and Gas Industry

Augustina Ginikawa
Augustina Ginikawa was strategic in her plans to progress her career – she knew she wanted to combine her passion for Information Technology with Engineering and decided to pursue a Masters.

Augustina’s love for technology started early when her mother procured her first mobile phone – an Alcatel. From that point, there was no looking back. When she applied to study at RGU, Augustina was already armed with a BSc in Computer Science and hands-on experience in Nigeria where she worked as an IT Service Desk Analyst and Systems Administrator for two years with International Breweries Plc., one of the largest breweries in Nigeria. “I was drawn to an MSc in Information Technology for the Oil and Gas Industry as it offered a wealth of academic resources about Information Technology and how it applies to the Oil and Gas Industry in Aberdeen - the Oil Capital of Europe.”

Augustina was very impressed by RGU’s teaching methods, ”The computing facilities were top-notch, and my lecturers delivered industry-relevant lectures flawlessly as well as in a highly interactive manner.”

After having attended a few job events and career fairs, Augustina was able to strengthen her interview and presentations skills. Thanks to her industry-relevant education and course modules about Petroleum Geoscience, Oil and Gas Engineering and Intranet Systems Development, Augustina was able to secure a job as an IT Engineer at BP and is making a smooth transition into her work life. “All of these aspects were covered during my onboarding activities at work. I simply smile from ear to ear each time I participate in any activity that involves working across various teams.”

She also graduated top of her class owing to her persistent focus and dedication. This was particularly useful during the pandemic which made completion of her thesis work appear arduous.

“I did not take virtual learning experience for granted, I had a focused mindset on achieving a Distinction regardless of the shock and transition that came with the pandemic, so much so that my Thesis was inspired by the pandemic – Integrating Supervised Machine Learning methods with Web Development to predict COVID-19.

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