Liam

Hi, I'm Liam! I'm a MEng Mechanical Engineering graduate from Imperial College London who currently works as a Data Science lecturer for apprenticeships. I have been professionally teaching academic subjects including Maths, Physics and Engineering since 2016. I believe my experience in teaching combined with my own passion for learning allows me to aid students in achieving excellent results. My background: I'm British by nationality but I gained fluency in Mandarin by going to a Taiwanese school for around 12 years. I continued on to achieve 4 A*s in A-levels for Physics, Maths, Biology and Chemistry. I achieved First Class Honours in my University degree. I have experience and a passion for teaching and therefore will do everything to ensure you have an effective yet enjoyable time in mastering your subject.

Tutoring Experience

I have been a Data Science instructor since April 2021. I have been tutoring academic subjects professionally since 2016. I currently tutor students in University level Mechanical Engineering, A-level + GCSE Maths & Physics and Programming. Aside from academics, I have also been a tap dance and hip hop instructor for the last 6 years, in which I have taught people of all ages and levels.

Tutoring Approach

Before the tutoring session, I will contact the tutee to evaluate which parts of the subject he/she needs help on, as well as any questions or problems sets that they want to discuss. I will prepare accordingly and cover this material in the tutoring session and ensure the tutee understands the chosen material by briefly testing them at the end of the session. For Physics and Maths, if requested, I can provide links to engineering applications that might pique the tutee's interest in the subject. If the tutee is not satisfied with my style of teaching, then I can adapt to the tutee's preferred method of learning as long as it proves effective.
CANCELLATION POLICY - Fee of half the hourly rate if class is cancelled within an hour of commencing, full hourly rate if cancelled within the scheduled timeslot.