Machine Learning Tutors : 1-1 Machine Learning Preparation

I’m a full-time private tutor with an extensive background in maths and data tech. I’ve been tutoring/taught for over twelve years, and worked in the data tech industry for six years. My academic background is from Sussex University. I completed my MMath degree with a 1st class honours in 2014 writing my dissertation on Bochner-Riesz summability and Strichartz estimates. I then completed my PhD in maths in 2019 under the Hirschfeld scholarship passing with minor corrections (2019); my thesis was titled “Topics in Geometric and Harmonic Analysis on Symmetric Spaces and Lie Groups”. I started tutoring as an A-level assistant at school helping GCSE students with maths work in the classroom. I picked it up again as a university undergraduate as a convenient way to fund my studies. I quickly realised that I had a knack for tutoring being able to get the best out of my students and consequently help them achieve their goals. Tutoring has since become my passion. From that point, I’ve had a range of tutoring positions including acting as a classroom assistant in a local school, one-on-one tutoring online and in person, leading university workshops, marking homework, being a university examiner, delivering lectures at universities, and leading technical training in industry. My PhD further enhanced my tutoring. I had regular contact with my research supervisor who had a remarkable ability to explain complex maths concepts in a simplified way unfolding the concepts as if he was telling a story. I integrated this into my tutoring technique. I constantly strive to develop this skill further and pass it onto my students to engender their enthusiasm. I entered the workforce following the completion of my PhD as a data specialist working in tech and applying maths to solve machine learning problems. An example was acting as an intermediary translating academic mathematical models into Python and PySpark code to improve the computation of aggregate functions. I continued teaching responsibilities being responsible for training work colleagues in data engineering skills and advanced machine learning. I’m now a full time tutor after spending six years in data tech. I have expanded my tutoring portfolio into further areas including: computer science, data engineering/science best practices, dissertation advice, maths entrance exams, mechanics, university application assistance, Python/SQL pair programming, statistics, and test preparation.

I obtained a PhD in Economics. I have over 20 years of experience in teaching Economics, Statistics, and Maths online, having helped over 500 students. The level of the students I have helped includes GCSE, IB, A level, undergraduate and postgraduate.

Academic Qualification
PhD (University of Leicester, UK)
MSc in Quantitative Finance (SOAS, University of London, UK)
Master of Statistics (University of Hong Kong, HK)
Master of Economics (University of Hong Kong, HK)
Professional Certificate in Data Science (Harvard University, USA)
BBA (Hons) in Economics (Hong Kong University of Science and Technology, HK)
Oxford Artificial Intelligence Programme (University of Oxford, UK)
Oxford Algorithmic Trading Programme (University of Oxford, UK)
Graduate Statistician (Royal Statistical Society, UK)
Advanced Certified Professional Forecaster (Institute of Business Forecasting and Planning, USA)

Dr Michael was a Honorary Research Fellow of the Department of Economics at the Kingston University. He was also an Associate Professor of Finance at the Richmond American University London and Associate Lecturer of Economics and Statistics at the Open University. Dr Michael specializes in applied econometrics, quantitative finance and labour economics. He published books in economics and statistics, and academic articles in international journal. He was invited by the International University of Applied Sciences to develop a series of economics distance learning modules.

Passionate professional with mathematical finance and everything utilising mathematics. I hold a CQF with Distinction, an MSc in Economics from LSE, and currently work in applied financial engineering advisory, where I benchmark and validate exotic derivatives pricing models daily — from Bermudan options and callable bonds to inflation-linked swaps and Monte Carlo simulations.
My work sits at the intersection of quantitative theory and real-world application: building independent pricing models, calibrating volatility surfaces, computing CVA/DVA adjustments, and stress-testing credit risk frameworks. I also code actively in Python, C++, and VBA, and pursue personal research in stochastic expansion methods for exotic option pricing.
In my courses, I bring this practitioner perspective directly into the classroom. If you want to understand not just the textbook formulas but how derivatives are actually priced, validated and risk-managed in industry, you’re in the right place.

I’m a full-time private tutor with an extensive background in maths and data tech. I’ve been tutoring/taught for over twelve years, and worked in the data tech industry for six years. My academic background is from Sussex University. I completed my MMath degree with a 1st class honours in 2014 writing my dissertation on Bochner-Riesz summability and Strichartz estimates. I then completed my PhD in maths in 2019 under the Hirschfeld scholarship passing with minor corrections (2019); my thesis was titled “Topics in Geometric and Harmonic Analysis on Symmetric Spaces and Lie Groups”. I started tutoring as an A-level assistant at school helping GCSE students with maths work in the classroom. I picked it up again as a university undergraduate as a convenient way to fund my studies. I quickly realised that I had a knack for tutoring being able to get the best out of my students and consequently help them achieve their goals. Tutoring has since become my passion. From that point, I’ve had a range of tutoring positions including acting as a classroom assistant in a local school, one-on-one tutoring online and in person, leading university workshops, marking homework, being a university examiner, delivering lectures at universities, and leading technical training in industry. My PhD further enhanced my tutoring. I had regular contact with my research supervisor who had a remarkable ability to explain complex maths concepts in a simplified way unfolding the concepts as if he was telling a story. I integrated this into my tutoring technique. I constantly strive to develop this skill further and pass it onto my students to engender their enthusiasm. I entered the workforce following the completion of my PhD as a data specialist working in tech and applying maths to solve machine learning problems. An example was acting as an intermediary translating academic mathematical models into Python and PySpark code to improve the computation of aggregate functions. I continued teaching responsibilities being responsible for training work colleagues in data engineering skills and advanced machine learning. I’m now a full time tutor after spending six years in data tech. I have expanded my tutoring portfolio into further areas including: computer science, data engineering/science best practices, dissertation advice, maths entrance exams, mechanics, university application assistance, Python/SQL pair programming, statistics, and test preparation.

I obtained a PhD in Economics. I have over 20 years of experience in teaching Economics, Statistics, and Maths online, having helped over 500 students. The level of the students I have helped includes GCSE, IB, A level, undergraduate and postgraduate.

Academic Qualification
PhD (University of Leicester, UK)
MSc in Quantitative Finance (SOAS, University of London, UK)
Master of Statistics (University of Hong Kong, HK)
Master of Economics (University of Hong Kong, HK)
Professional Certificate in Data Science (Harvard University, USA)
BBA (Hons) in Economics (Hong Kong University of Science and Technology, HK)
Oxford Artificial Intelligence Programme (University of Oxford, UK)
Oxford Algorithmic Trading Programme (University of Oxford, UK)
Graduate Statistician (Royal Statistical Society, UK)
Advanced Certified Professional Forecaster (Institute of Business Forecasting and Planning, USA)

Dr Michael was a Honorary Research Fellow of the Department of Economics at the Kingston University. He was also an Associate Professor of Finance at the Richmond American University London and Associate Lecturer of Economics and Statistics at the Open University. Dr Michael specializes in applied econometrics, quantitative finance and labour economics. He published books in economics and statistics, and academic articles in international journal. He was invited by the International University of Applied Sciences to develop a series of economics distance learning modules.

Passionate professional with mathematical finance and everything utilising mathematics. I hold a CQF with Distinction, an MSc in Economics from LSE, and currently work in applied financial engineering advisory, where I benchmark and validate exotic derivatives pricing models daily — from Bermudan options and callable bonds to inflation-linked swaps and Monte Carlo simulations.
My work sits at the intersection of quantitative theory and real-world application: building independent pricing models, calibrating volatility surfaces, computing CVA/DVA adjustments, and stress-testing credit risk frameworks. I also code actively in Python, C++, and VBA, and pursue personal research in stochastic expansion methods for exotic option pricing.
In my courses, I bring this practitioner perspective directly into the classroom. If you want to understand not just the textbook formulas but how derivatives are actually priced, validated and risk-managed in industry, you’re in the right place.

I’m a full-time private tutor with an extensive background in maths and data tech. I’ve been tutoring/taught for over twelve years, and worked in the data tech industry for six years. My academic background is from Sussex University. I completed my MMath degree with a 1st class honours in 2014 writing my dissertation on Bochner-Riesz summability and Strichartz estimates. I then completed my PhD in maths in 2019 under the Hirschfeld scholarship passing with minor corrections (2019); my thesis was titled “Topics in Geometric and Harmonic Analysis on Symmetric Spaces and Lie Groups”. I started tutoring as an A-level assistant at school helping GCSE students with maths work in the classroom. I picked it up again as a university undergraduate as a convenient way to fund my studies. I quickly realised that I had a knack for tutoring being able to get the best out of my students and consequently help them achieve their goals. Tutoring has since become my passion. From that point, I’ve had a range of tutoring positions including acting as a classroom assistant in a local school, one-on-one tutoring online and in person, leading university workshops, marking homework, being a university examiner, delivering lectures at universities, and leading technical training in industry. My PhD further enhanced my tutoring. I had regular contact with my research supervisor who had a remarkable ability to explain complex maths concepts in a simplified way unfolding the concepts as if he was telling a story. I integrated this into my tutoring technique. I constantly strive to develop this skill further and pass it onto my students to engender their enthusiasm. I entered the workforce following the completion of my PhD as a data specialist working in tech and applying maths to solve machine learning problems. An example was acting as an intermediary translating academic mathematical models into Python and PySpark code to improve the computation of aggregate functions. I continued teaching responsibilities being responsible for training work colleagues in data engineering skills and advanced machine learning. I’m now a full time tutor after spending six years in data tech. I have expanded my tutoring portfolio into further areas including: computer science, data engineering/science best practices, dissertation advice, maths entrance exams, mechanics, university application assistance, Python/SQL pair programming, statistics, and test preparation.

I obtained a PhD in Economics. I have over 20 years of experience in teaching Economics, Statistics, and Maths online, having helped over 500 students. The level of the students I have helped includes GCSE, IB, A level, undergraduate and postgraduate.

Academic Qualification
PhD (University of Leicester, UK)
MSc in Quantitative Finance (SOAS, University of London, UK)
Master of Statistics (University of Hong Kong, HK)
Master of Economics (University of Hong Kong, HK)
Professional Certificate in Data Science (Harvard University, USA)
BBA (Hons) in Economics (Hong Kong University of Science and Technology, HK)
Oxford Artificial Intelligence Programme (University of Oxford, UK)
Oxford Algorithmic Trading Programme (University of Oxford, UK)
Graduate Statistician (Royal Statistical Society, UK)
Advanced Certified Professional Forecaster (Institute of Business Forecasting and Planning, USA)

Dr Michael was a Honorary Research Fellow of the Department of Economics at the Kingston University. He was also an Associate Professor of Finance at the Richmond American University London and Associate Lecturer of Economics and Statistics at the Open University. Dr Michael specializes in applied econometrics, quantitative finance and labour economics. He published books in economics and statistics, and academic articles in international journal. He was invited by the International University of Applied Sciences to develop a series of economics distance learning modules.

Passionate professional with mathematical finance and everything utilising mathematics. I hold a CQF with Distinction, an MSc in Economics from LSE, and currently work in applied financial engineering advisory, where I benchmark and validate exotic derivatives pricing models daily — from Bermudan options and callable bonds to inflation-linked swaps and Monte Carlo simulations.
My work sits at the intersection of quantitative theory and real-world application: building independent pricing models, calibrating volatility surfaces, computing CVA/DVA adjustments, and stress-testing credit risk frameworks. I also code actively in Python, C++, and VBA, and pursue personal research in stochastic expansion methods for exotic option pricing.
In my courses, I bring this practitioner perspective directly into the classroom. If you want to understand not just the textbook formulas but how derivatives are actually priced, validated and risk-managed in industry, you’re in the right place.