Mathematics, statistics, and data analysis become much easier when formulas, reasoning, computation, and real-world interpretation are connected clearly. I am a PhD-qualified engineer, university professor, researcher, and multidisciplinary tutor with more than 30 years of experience in teaching, quantitative methods, mathematical problem solving, statistical analysis, research, engineering, data analysis, and professional decision support. This class provides a structured and personalized learning pathway for school and university students, graduate researchers, engineers, professionals, and adult learners. Depending on your goals, we can focus on one specific area or connect several areas into a coherent program. MATHEMATICS • Arithmetic, fractions, ratios, percentages, and mathematical foundations • Algebraic expressions, equations, inequalities, and systems • Functions, graphs, and transformations • Geometry and analytic geometry • Trigonometry • Precalculus • Limits and continuity • Differential calculus and applications • Integral calculus and applications • Sequences and series • Multivariable calculus • Linear algebra, matrices, vectors, and systems • Differential equations • Numerical methods • Applied and engineering mathematics STATISTICS, PROBABILITY & ECONOMETRICS • Descriptive statistics • Probability rules and probabilistic reasoning • Random variables and probability distributions • Sampling and sampling distributions • Confidence intervals • Hypothesis testing • Correlation and regression • Multiple regression • ANOVA, ANCOVA, and MANOVA • Nonparametric methods • Multivariate statistical analysis • Econometrics and quantitative methods • Time-series analysis and forecasting • Mediation and moderation analysis • Statistical modelling and predictive analysis DATA ANALYSIS & VISUALIZATION • Data organization and quality assessment • Data cleaning and preparation • Missing values, duplicates, inconsistencies, and outliers • Exploratory data analysis • Summary tables and analytical reporting • PivotTables and aggregation • Data visualization and appropriate chart selection • Trend and pattern analysis • KPI development and performance analysis • Dashboard concepts and decision-support reporting • Research and survey data preparation • Interpretation and communication of analytical findings Depending on your needs, practical work may involve Excel, SPSS, Stata, R, SAS, Power BI, SQL, Python, or other relevant analytical tools. Software is never treated as a substitute for understanding: I explain the reasoning behind the method, the assumptions involved, the meaning of the output, and how to verify whether the conclusion is sound. My teaching approach follows a clear progression: understand the problem → identify the appropriate concept or method → develop the reasoning → calculate or analyze → verify the result → interpret it → communicate the conclusion We can work with your course syllabus, textbook, representative exercises, exam topics, dataset, statistical output, research question, spreadsheet, dashboard, engineering application, or professional analytical problem. Whether you are rebuilding mathematical foundations, preparing for an examination, studying advanced calculus, learning statistics, conducting econometric analysis, interpreting research data, or developing practical analytical skills, I will adapt the sessions to your level, objectives, and pace. My goal is not merely to help you obtain an answer, but to help you understand the reasoning, choose appropriate methods, verify results, interpret findings correctly, and solve new problems independently.

I have a dual degree in Mathematics and Physics, obtained at Université de Montréal in 2014. At the same university, I have pursued a Master's degree in Astronomy and Astrophysics. I have since been working as a Mathematics and Physics educator, with a particular affinity towards upper-year high school and undergraduate courses. J'enseigne en français aussi :)

Mathematics, statistics, and data analysis become much easier when formulas, reasoning, computation, and real-world interpretation are connected clearly. I am a PhD-qualified engineer, university professor, researcher, and multidisciplinary tutor with more than 30 years of experience in teaching, quantitative methods, mathematical problem solving, statistical analysis, research, engineering, data analysis, and professional decision support. This class provides a structured and personalized learning pathway for school and university students, graduate researchers, engineers, professionals, and adult learners. Depending on your goals, we can focus on one specific area or connect several areas into a coherent program. MATHEMATICS • Arithmetic, fractions, ratios, percentages, and mathematical foundations • Algebraic expressions, equations, inequalities, and systems • Functions, graphs, and transformations • Geometry and analytic geometry • Trigonometry • Precalculus • Limits and continuity • Differential calculus and applications • Integral calculus and applications • Sequences and series • Multivariable calculus • Linear algebra, matrices, vectors, and systems • Differential equations • Numerical methods • Applied and engineering mathematics STATISTICS, PROBABILITY & ECONOMETRICS • Descriptive statistics • Probability rules and probabilistic reasoning • Random variables and probability distributions • Sampling and sampling distributions • Confidence intervals • Hypothesis testing • Correlation and regression • Multiple regression • ANOVA, ANCOVA, and MANOVA • Nonparametric methods • Multivariate statistical analysis • Econometrics and quantitative methods • Time-series analysis and forecasting • Mediation and moderation analysis • Statistical modelling and predictive analysis DATA ANALYSIS & VISUALIZATION • Data organization and quality assessment • Data cleaning and preparation • Missing values, duplicates, inconsistencies, and outliers • Exploratory data analysis • Summary tables and analytical reporting • PivotTables and aggregation • Data visualization and appropriate chart selection • Trend and pattern analysis • KPI development and performance analysis • Dashboard concepts and decision-support reporting • Research and survey data preparation • Interpretation and communication of analytical findings Depending on your needs, practical work may involve Excel, SPSS, Stata, R, SAS, Power BI, SQL, Python, or other relevant analytical tools. Software is never treated as a substitute for understanding: I explain the reasoning behind the method, the assumptions involved, the meaning of the output, and how to verify whether the conclusion is sound. My teaching approach follows a clear progression: understand the problem → identify the appropriate concept or method → develop the reasoning → calculate or analyze → verify the result → interpret it → communicate the conclusion We can work with your course syllabus, textbook, representative exercises, exam topics, dataset, statistical output, research question, spreadsheet, dashboard, engineering application, or professional analytical problem. Whether you are rebuilding mathematical foundations, preparing for an examination, studying advanced calculus, learning statistics, conducting econometric analysis, interpreting research data, or developing practical analytical skills, I will adapt the sessions to your level, objectives, and pace. My goal is not merely to help you obtain an answer, but to help you understand the reasoning, choose appropriate methods, verify results, interpret findings correctly, and solve new problems independently.