[Hourly Lessons] IBDP Mathematics AIHL｜1-on-1 Tutoring with Tim

About Course

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If you’re looking for clear, personalized help in math or physics, this is a live 1-on-1 lesson with me, Tim Chen. I work with students from a wide range of programs. Whether you’re preparing for big exams, tackling tough topics, or aiming for top scores and universities.

Lessons are always tailored to your pace, your goals, and your learning style. I’ll help you build a solid understanding, improve problem-solving, and feel more confident step by step.

Subjects I Teach

Standardized Tests
- SAT math
- ACT math

AP Courses
- AP Calculus AB / BC
- AP Physics 1 / 2 / CM / CEM
- AP Statistics
- AP Precalculus

IBDP
- IB Mathematics AA / AI
- IB Physics
- IB Internal Assessment (IA) Guidance

A-Level Subjects
- A-Level Mathematics
- A-Level Physics

Other Subjects
- Algebra 1 / 2
- Geometry
- Precalculus
- Physics
- Functions / Advanced Functions
- Integrated Math (IM1 – IM4)

About Me

I’ve worked with students from all over the world, helping them get through challenging material, prepare for competitive exams, and feel more confident in math and physics. I focus on clear explanations, strong fundamentals, and real progress.

Lesson Format

Live 1-on-1 via Zoom
Flexible scheduling
Lessons in English or Mandarin
Optional whiteboard, handouts, or recordings based on your preference

If you’re serious about improving or want to feel more in control of your learning, let’s work together. Book a trial or message me with any questions.

Break down tough math and physics concepts into simple, logical steps
Build strong foundations in calculus, mechanics, statistics, and algebra
Prepare effectively for standardized exams like SAT, ACT, AP, IB, and A-Level
Improve your problem-solving strategy and accuracy under time pressure
Learn how to recognize patterns, organize your thoughts, and tackle unfamiliar problems with confidence
Get step-by-step guidance on Internal Assessments (IA) for IB Physics and Math

Course Content

Measuring Space: Accuracy and Geometry
Learn how to represent quantities precisely and understand the geometric principles that describe two- and three-dimensional space. This chapter introduces exact and approximate numbers, angle relationships, and geometric solids.

Representing Numbers Exactly and Approximately
Angles and Triangles
Three-Dimensional Geometry

Representing and Describing Data: Descriptive Statistics
This chapter develops skills in collecting, organizing, and interpreting data. Students learn measures of central tendency, variability, and graphical methods for data presentation.

Coordinate Geometry, Voronoi Diagrams, and Vectors
Explore how space can be divided and represented mathematically using coordinates, vectors, and diagrams. The focus is on modeling spatial relationships and lines in 2D and 3D.

Linear Functions and Constant Rates of Change
Learn to model relationships with constant rates of change through linear functions, inverse functions, and arithmetic sequences. Regression techniques are introduced for analyzing real data.

Probability and Quantifying Uncertainty
An introduction to the mathematics of chance. Students learn how to calculate, represent, and interpret probabilities using diagrams, formulas, and systematic reasoning.

Power and Polynomial Functions
Explore how quadratic, cubic, and power functions model different real-world patterns. Emphasis is placed on interpreting graphs, solving equations, and understanding functional relationships.

Exponential and Logarithmic Models
Discover how exponential growth, decay, and logarithmic relationships describe processes such as population growth, finance, and natural phenomena.

Trigonometric and Complex Number Models
This chapter unites trigonometric and complex number concepts to model periodic behavior and extend the number system beyond the real line.

Matrices and Data Analysis
Learn how matrices can represent and solve systems of equations, model transformations, and analyze steady-state systems in data and applied contexts.

Differential Calculus: Analyzing Change
Understand how derivatives measure change and describe motion, growth, and optimization. Students master differentiation rules and explore real-world applications.

Integration and Differential Equations
Study the reverse process of differentiation — integration — and its uses in calculating areas, solving differential equations, and modeling change in dynamic systems.

Motion in Two and Three Dimensions
Model motion and change using vectors and calculus. Topics include velocity, acceleration, and systems of coupled differential equations.

Random Variables and Probability Distributions
Examine how random variables model uncertainty. This chapter covers binomial, Poisson, and continuous distributions, along with mean and variance analysis.

Statistical Testing and Validity
Learn how to evaluate hypotheses and test data reliability using Spearman’s correlation, chi-squared tests, and hypothesis testing for various distributions.

Graph Theory and Network Optimization
Discover how graphs represent real-world networks. Students analyze routes, connections, and efficiencies using graph algorithms and optimization methods.

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About Course

Discounts Available

Subjects I Teach

About Me

Lesson Format

What Will You Learn?

Course Content

Measuring Space: Accuracy and Geometry Learn how to represent quantities precisely and understand the geometric principles that describe two- and three-dimensional space. This chapter introduces exact and approximate numbers, angle relationships, and geometric solids.

Representing Numbers Exactly and Approximately

Angles and Triangles

Three-Dimensional Geometry

Representing and Describing Data: Descriptive Statistics This chapter develops skills in collecting, organizing, and interpreting data. Students learn measures of central tendency, variability, and graphical methods for data presentation.

Collecting and Organizing Data

Statistical Measures

Presenting Data in Different Ways

Bivariate Data

Coordinate Geometry, Voronoi Diagrams, and Vectors Explore how space can be divided and represented mathematically using coordinates, vectors, and diagrams. The focus is on modeling spatial relationships and lines in 2D and 3D.

Coordinate Geometry in Two and Three Dimensions

Equations of Straight Lines

Voronoi Diagrams

Displacement Vectors

Scalar and Vector Products

Vector Equations of Lines

Linear Functions and Constant Rates of Change Learn to model relationships with constant rates of change through linear functions, inverse functions, and arithmetic sequences. Regression techniques are introduced for analyzing real data.

Functions

Linear Models

Inverse Functions

Arithmetic Sequences and Series

Linear Regression

Probability and Quantifying Uncertainty An introduction to the mathematics of chance. Students learn how to calculate, represent, and interpret probabilities using diagrams, formulas, and systematic reasoning.

The Concept of Probability

Representing Combined Probabilities with Diagrams

Representing Combined Probabilities with Formulas

Concise and Consistent Representations of Probability

Power and Polynomial Functions Explore how quadratic, cubic, and power functions model different real-world patterns. Emphasis is placed on interpreting graphs, solving equations, and understanding functional relationships.

Quadratic Models

Applications of Quadratic Equations

Cubic Functions and Models

Power, Direct, and Inverse Variation

Exponential and Logarithmic Models Discover how exponential growth, decay, and logarithmic relationships describe processes such as population growth, finance, and natural phenomena.

Geometric Sequences and Series

Financial Applications of Geometric Sequences

Exponential Functions and Models

Laws of Exponents and Logarithms

Logistic Models

Trigonometric and Complex Number Models This chapter unites trigonometric and complex number concepts to model periodic behavior and extend the number system beyond the real line.

Measuring Angles

Sinusoidal Models

Extending the Number System

Geometrical Interpretation of Complex Numbers

Using Complex Numbers in Periodic Models

Matrices and Data Analysis Learn how matrices can represent and solve systems of equations, model transformations, and analyze steady-state systems in data and applied contexts.

Introduction to Matrices and Operations

Matrix Multiplication and Properties

Solving Systems of Equations Using Matrices

Transformations of the Plane

Representing Systems and Steady States

Eigenvalues and Eigenvectors

Differential Calculus: Analyzing Change Understand how derivatives measure change and describe motion, growth, and optimization. Students master differentiation rules and explore real-world applications.

Limits and Derivatives

Advanced Differentiation Techniques

Applications and Higher Derivatives

Integration and Differential Equations Study the reverse process of differentiation — integration — and its uses in calculating areas, solving differential equations, and modeling change in dynamic systems.

Approximate Areas and Integration Concepts

Techniques of Integration

Applications of Integration

Introduction to Differential Equations

Slope Fields and Solution Methods

Motion in Two and Three Dimensions Model motion and change using vectors and calculus. Topics include velocity, acceleration, and systems of coupled differential equations.

Vector Quantities and Components

Motion with Variable Velocity

Exact and Approximate Solutions of Coupled Equations

Random Variables and Probability Distributions Examine how random variables model uncertainty. This chapter covers binomial, Poisson, and continuous distributions, along with mean and variance analysis.

Modeling Random Behaviour

Number of Successes in Fixed Trials or Intervals

Random Measurement Distributions

Transformations and Combinations of Random Variables

Statistical Testing and Validity Learn how to evaluate hypotheses and test data reliability using Spearman’s correlation, chi-squared tests, and hypothesis testing for various distributions.

Spearman’s Rank Correlation

Hypothesis Testing for Binomial, Poisson, and Correlation Coefficients