Math AI HL Spring Group Course
7 Max. Students
NY: 08:00-12:30, UK: 13:00-17:30, Dubai: 16:00-20:30 (4.5 Hours a day incl. 1/2 an hour break) 
Join our expert tutor, Mudassir as he provides you with Math AI HL Spring Revision Tuition. See our detailed Curriculum breakdown below.
Welcome AI HL students. This is a 3-day Revision Course which will be run at a good pace and shall cover all the topics with solving questions from the past papers. The course is split as follows:
Day 1
Topic 1 - Number and Algebra
- Arithmetic Sequences and Series
- Geometric Sequences and Series
- Sigma Notation
- Compound Interest and Depreciation
- Loans and Amortization
- Annuities
- GDC Tips (TVM Solver)
- Complex Numbers
- Operations of Complex Number
- Complex Numbers using GDC
- Matrices
- Solving Simultaneous Linear Equation using Matrices
- Eigenvalues, Eigenvectors and Matrix Powers
- Solving Matrix Operation using GDC
Topic 5 - Calculus
- Differentiation, Tangents, and Normals
- Rates of Change and Applications
- Max/Min and Optimization
- Related Rates
- Integration, Area under and b/w the Curves.
- Trapezoidal Rule
- Volumes of Revolution
- Kinematics
- Differential Equation
Day 2
Topic 2 - Functions
- Forms of Linear Equation
- Gradients and Intercepts of Linear Lines
- Parallel and Perpendicular Gradients
- Perpendicular Bisectors
- The intersection of two lines using GDC
- Function and its Types
- Plotting Functions and Analyzing graphs using GDC
- Using n-Solve to Solve Equations
- Domain and Range Composite and Inverse of a Function
- Transformations of functions
Topic 3 - Geometry and Trigonometry
- The geometry of 3D Shapes
- Sine and Cosine Rule/ Area of Triangle
- Length of Arc/ Area of Sector
- Degree vs Radian
- Voronoi Diagrams
Day 3
- Unit Circle and Trig Graphs
- Geometric Transformations
- Vector Equation of Straight Line
- Scalar and Vector Product
- Graph Theory
Topic 4 - Statistics and Probability
- Descriptive Statistics
- Bivariate Statistics
- Non-Linear Regression
- Tree Diagrams
- Venn Diagrams
- Transition Matrices and Markov Chains
- Probability Distribution
- Binomial Distribution
- Normal Distribution
- Poisson Distribution
- Combinations of Random Variables
- T-Test
- Chi-squared testing
- Further Hypothesis Testing
- Estimation and Confidence Interval