IB Math AI: Full Package (HL)

방원준 선생님의 IB Math AI 전체 단원 


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IB Math AI의 1~5 단원
Chapter 1: Number and Algebra
Chapter 2: Functions
Chapter 3: Geometry & Trigonometry
Chapter 4: Statistics & Probability
Chapter 5: Calculus
커리큘럼
  • 1.6에 통합된 내용
    0
  • 무료 수업 12:06
  • 1.2.2 Arithmetic Sequence
    15:30
  • 1.2.3 Series
    07:42
  • 1.2.4 Arithmetic Series
    11:08
  • 1.2.5 Simple Interest
    14:43
  • 1.2.6 Real-life example
    07:39
  • 1.3.1 Geometric Sequence
    09:36
  • 1.3.2 Geometric Series
    13:47
  • 1.3.3 Real-life example
    08:55
  • 1.4.1 Financial Sequence & Series
    09:34
  • 1.5.1 Laws of Exponents
    11:06
  • 1.5.2 Exponential Function
    21:32
  • 1.6.1 Approximation
    04:48
  • 1.6.2 Bound
    07:15
  • 1.6.3 Percentage Errors
    05:13
  • 1.6.4 Estimation
    03:12
  • 1.7.1 Amortization
    10:00
  • 1.8.1 Simultaneous Equations
    06:09
  • 1.8.2 Simultaneous equations with Calculator 1
    03:42
  • 1.8.3 Simultaneous equations with Calculator 2
    04:40
  • 1.9.1 Logarithmc Function and Equation
    30:08
  • 1.5로 통합된 내용
    0
  • 1.12.1 Complex Numbers with Cartesian Form
    17:21
  • 1.13.1 Polar form
    30:19
  • 1.13.2 Euler form
    07:16
  • 1.13.3 De Moivre's Theorem
    08:37
  • 1.13.4 Sinusoidal function with Complex Numbers
    10:14
  • 1.14.1 Algebra 1
    04:27
  • 1.14.2 Algebra 2
    13:12
  • 1.14.3 Identity and Zero Matrix
    04:51
  • 1.14.4 Inverse Matrix by Calculator
    09:26
  • 1.14.5 Inverse Matrix by Hand
    06:58
  • 1.14.6 Simultaneous Equations
    06:55
  • 1.15.1 Eigenvalue and Eigenvector
    10:38
  • 1.15.2 Diagonalization
    06:25
  • 1.15.3 Power of Matrices
    07:04
  • 무료 수업 02:03
  • 1.2 SL Q&A
    07:12
  • 1.3 SL Q&A
    04:30
  • 1.4 SL Q&A
    04:41
  • 1.5 SL Q&A
    02:03
  • 1.6 SL Q&A
    04:23
  • 1.7 SL Q&A
    04:09
  • 1.8 SL Q&A
    01:09
  • 무료 수업 01:06
  • 1.10 HL Q&A (HL)
    01:26
  • 1.11 HL Q&A (HL)
    01:24
  • 1.12 HL Q&A (HL)
    05:58
  • 1.13 HL Q&A (HL)
    05:22
  • 1.14 HL Q&A (HL)
    07:34
  • 1.15 HL Q&A (HL)
    08:16
  • 2.2.1 Function: Domain and Range
    11:54
  • 2.2.2 Parent Function
    05:52
  • 2.3~4 Function with Calculator
    08:11
  • 2.5.1 Linear Modeling
    14:47
  • 2.5.2 Quadratic Modeling
    13:21
  • 2.5.3 Exponential Modeling
    09:31
  • 2.5.4 Direct/Inverse Variation
    05:30
  • 2.5.5 Cubic Modeling
    06:30
  • 2.5.6 Sinusoidal Modeling
    11:38
  • 2.6.1 Modelling Skills
    15:18
  • 2.8.1 Transformation 1
    22:59
  • 2.9.1 Exponential Model with Half Life
    08:00
  • 2.9.2 Natural Logarithmic model
    04:35
  • 2.9.3 Sinusoidal model 2
    06:47
  • 2.9.4 Logistic Models
    08:31
  • 2.9.5 Piecewise models
    05:39
  • 2.10.1 Logarithmic Scale 1
    11:00
  • 2.10.2 Interpretation of log scale graph
    05:21
  • 무료 수업 02:51
  • 2.2 Q&A
    02:30
  • 2.3 Q&A
    02:24
  • 2.4 Q&A
    04:53
  • 2.5a Q&A
    01:32
  • 2.5b Q&A
    02:31
  • 2.5c Q&A
    01:36
  • 2.5d Q&A
    02:30
  • 2.5e Q&A
    01:31
  • 2.6 Q&A
    04:10
  • 무료 수업 01:20
  • 2.7b Q&A (HL)
    01:30
  • 2.8 Q&A (HL)
    04:16
  • 2.9 Q&A (HL)
    06:42
  • 2.10 Q&A (HL)
    03:30
  • 3.2.1 Area of Triangle
    05:47
  • 3.2.2 Sine Rule
    19:40
  • 3.2.3 Cosine Rule
    06:09
  • 3.3.1 Modeling with Trigonometry
    16:50
  • 3.4.1 Circle in Degree
    04:58
  • 3.6.1로 통합된 내용
    0
  • 3.6.1 Voronoi Diagram
    14:24
  • 3.6.2 Addition of a site
    08:20
  • 3.6.3 Nearest Neighbour Interpolation
    03:16
  • 3.6.4 Toxic Waste Dump Problem
    08:05
  • 3.8.1 Pythagorean Identities
    08:47
  • 3.8.2 Proving Identities
    10:55
  • 3.8.3 Reference Angle
    15:55
  • 3.8.4 Trigonometric Equations
    11:59
  • 3.8.5 Trigonometric Function
    10:27
  • 3.8.6 Trigonometric Function Transformation
    18:03
  • 3.9.1 Affine Transformation
    10:10
  • 3.9.2 Common Transformation 1
    18:21
  • 3.9.3 Common Transformation 2
    09:01
  • 3.9.4 Determinant of Transformation Matrix
    04:57
  • 3.9.5 Eigenvalues and Eigenvectors with Transformation
    10:23
  • 3.10.1 Vector Definition
    04:30
  • 3.10.2 Vector Addition
    08:45
  • 3.10.3 Vector Scalar Multiplication
    08:36
  • 3.10.4 Vector 3D Representation
    05:04
  • 3.10.5 Vector Magnitude
    05:43
  • 3.10.6 Vector Component
    09:29
  • 3.11.1 Vector Line Equations
    16:39
  • 3.11.2 Angle between lines
    03:41
  • 3.11.3 Distance with Line Equations
    13:21
  • 3.11.4 Vector Line Intersection
    11:49
  • 3.12.1 Motion with variables in 2D
    10:03
  • 3.12.2 Projectile Motion
    10:10
  • 3.12.3 Circular Motion
    06:44
  • 3.12.4 Modelling time-shift
    05:15
  • 3.13.1 Dot Product
    11:12
  • 3.13.2 Cross Product
    11:11
  • 3.13.3 Cross Product with Geometry
    10:23
  • 3.14.1 Introduction to Graph Theory
    22:19
  • 3.14.2 Adjacency Table
    10:43
  • 3.14.3 Moving Around a Graph
    17:12
  • 3.15.1 Weighted Graph
    06:48
  • 3.15.2 Transition Matrix
    20:19
  • 3.16.1 Eulerian Graph
    07:26
  • 3.16.2 Hamiltonian Graph
    04:07
  • 3.16.3 Kruskal's Algorithm
    11:52
  • 3.16.4 Prim's Algorithm
    10:07
  • 3.16.5 Chinese Postman Problem
    16:06
  • 3.16.6 Travelling Salesman problem
    15:45
  • 무료 수업 01:17
  • 3.1b Q&A
    03:04
  • 3.1c Q&A
    04:16
  • 3.2a Q&A
    00:42
  • 3.2b Q&A
    01:34
  • 3.3 Q&A
    02:08
  • .3.4 Q&A
    01:30
  • 3.5 Q&A
    01:50
  • 3.6 Q&A
    05:54
  • 무료 수업 01:21
  • 3.8 Q&A (HL)
    03:38
  • 3.9 Q&A (HL)
    06:34
  • 3.10 Q&A (HL)
    03:57
  • 3.11 Q&A (HL)
    03:11
  • 3.12a Q&A (HL)
    02:20
  • 3.12b Q&A (HL)
    04:17
  • 3.13 Q&A (HL)
    04:39
  • 3.14 Q&A (HL)
    02:53
  • 3.15a Q&A (HL)
    01:55
  • 3.15b Q&A (HL)
    01:20
  • 3.15c Q&A (HL)
    02:46
  • 3.16a Q&A (HL)
    04:06
  • 3.16b Q&A (HL)
    04:32
  • 3.16c Q&A (HL)
    04:23
  • 3.16d Q&A (HL)
    05:49
  • 4.2 Types of Data
    03:57
  • 4.3.1 Discrete Data
    07:37
  • 4.3.2 Grouped Data
    08:54
  • 4.3.3 Variance and Standard Deviation
    08:54
  • 4.4.1 Bivariate Statistics
    04:56
  • 4.5.1 Theoretical Probability
    12:02
  • 4.6.1 Venn Diagrams
    05:19
  • 4.6.2 Tree Diagrams
    08:17
  • 4.6.3 Additional Law
    02:54
  • 4.6.4 Conditional Probability
    16:19
  • 4.6.5 Independence
    10:05
  • 4.6.6 De Morgan's Law
    08:11
  • 4.7.1 Discrete Random Variables
    13:13
  • 4.7.2 Expected Value
    13:22
  • 4.7.3 Variance
    06:19
  • 4.8.1 Binomial Distribution
    20:58
  • 4.9.1 Normal Distribution
    12:18
  • 4.9.2 Inverse Normal Distribution
    20:58
  • 4.10.1 Spearman's Rank Correlation Coefficient
    10:23
  • 4.11.1 Null and Alternative Hypothesis
    19:37
  • 4.11.2 Chi-squared Test
    14:53
  • 4.11.3 chi-squarted for independence
    09:23
  • 4.11.4 t-distribution
    17:39
  • 4.11.5 Means of Two Populations
    11:23
  • 4.13.1 Non-linear Regression
    08:44
  • 4.14.1 Linear Transformation of Single random variable
    22:00
  • 4.14.2 Unbiased Esimate for mean and variance
    08:02
  • 4.15.1 Central Limit Theorem
    18:43
  • 4.16.1 Confidence interval
    18:20
  • 4.17.1 Poisson distribution, properties, Sum of two indepndent Poisson Distribution
    58:42
  • 4.18.1 Critical Value and Region
    14:07
  • 4.18.2 means of Unpaired Samples
    14:56
  • 4.18.3 Test for Binomial distribution
    22:08
  • 4.18.4 Test for Poisson distribuion
    12:53
  • 4.18.5 Test for bivariate modeling
    07:58
  • 4.18.6 Type I and II errors
    21:37
  • 4.19.1 Markov Chain
    11:42
  • 4.19.2 Steady State
    07:51
  • 무료 수업 04:59
  • 4.2 Q&A
    03:44
  • 4.3 Q&A
    04:22
  • 4.4 Q&A
    03:54
  • 4.5 Q&A
    02:59
  • 4.6 Q&A
    06:21
  • 4.7 Q&A
    04:48
  • 4.8 Q&A
    02:43
  • 4.9 Q&A
    03:39
  • 4.10 Q&A
    04:58
  • 4.11 Q&A
    14:52
  • 무료 수업 05:04
  • 4.13 Q&A (HL)
    08:51
  • 4.14 Q&A (HL)
    05:13
  • 4.15 Q&A (HL)
    02:50
  • 4.16 Q&A (HL)
    03:31
  • 4.17 Q&A (HL)
    02:12
  • 4.18 Q&A(HL)
    03:22
  • 4.19 Q&A (HL)
    14:10
  • 5.2.1 Monotonicity
    05:53
  • 5.3.1 Power Rule
    02:46
  • 5.3.2 Rules of Differentiation
    09:33
  • 5.4.1 Tangent and Normal
    08:35
  • 5.5.1 Fundamental Theorem of Calculus
    08:00
  • 5.5.2 Riemann Sum
    06:13
  • 5.5.3 Integration
    03:56
  • 5.5.4 Definite Integral
    05:23
  • 5.5.5 Integration with Area
    05:34
  • 5.6.1 Stationary Point
    08:23
  • 5.7.1 Second Derivative Test
    06:02
  • 5.7.2 Optimization: Modeling
    35:53
  • 5.8.1 Trapezoidal Rule
    07:29
  • 5.10.1 Concavity and Inflexion Point
    12:06
  • 5.11.1 Integration by Substitution
    07:44
  • 5.11.2 Integration by Radicals
    04:28
  • 5.11.3 Integration with Trigonometry
    05:05
  • 5.11.4 Integration with Quotient
    02:23
  • 5.12.1 Area between two curves
    08:05
  • 5.12.2 Volume of Revolution
    04:26
  • 5.12.3 Volume Washer
    10:41
  • 5.13.1 Kinematics 1
    04:51
  • 5.13.2 Signs of Variables
    02:49
  • 5.13.3 Speed vs Velocity
    08:24
  • 5.13.4 Distance vs Displacement
    07:56
  • 5.14.1 Differential Equations
    03:55
  • 5.14.2 Separation of Variables
    13:47
  • 5.15.1 Slope Fields
    12:44
  • 5.16.1 Euler's Method
    05:54
  • 5.16.2 Euler's Method with coupled system
    06:33
  • 5.17.1 Coupled System
    07:40
  • 5.17.2 Phase Portraits
    18:56
  • 5.17.3 Phaese Portraits with Euler
    08:54
  • 5.18.1 Second Order Differential Equation
    11:23
  • 무료 수업 05:37
  • 5.2 Q&A
    02:52
  • 5.3 Q&A
    01:44
  • 5.4 Q&A
    05:18
  • 5.5 Q&A
    02:22
  • 5.6 Q&A
    02:50
  • 5.7 Q&A
    01:55
  • 5.8 Q&A
    03:20
  • 무료 수업 03:33
  • 5.10 Q&A (HL)
    04:15
  • 5.11 Q&A (HL)
    02:44
  • 5.12 Q&A (HL)
    03:09
  • 5.13 Q&A (HL)
    05:22
  • 5.14 Q&A (HL)
    03:06
  • 5.15 Q&A (HL)
    02:07
  • 5.16 Q&A (HL)
    04:09
  • 5.17 Q&A (HL)
    08:08
  • 5.18 Q&A (HL)
    04:46
설명

방원준 선생님의 IB Math AI (HL) 강좌입니다. 

다루는 단원은 Chapter 1~5 HL (전체 과정) 입니다.

 

*방원준 선생님의 강좌는 각 단원별 문제풀이도 포함되어 있습니다!

*얼라이언스 에듀의 모든 IB과정 HL 강좌는 SL 내용을 포함하고 있습니다!

일시정지 기간: 14일 2회

 

교재 다운받는 방법:

인강 수강 시에 선생님의 핵심 노하우가 담긴 필기용 교재를 학생분께 PDF로 드립니다. 

1) 인강 결제 후에 왼쪽 상단에 있는 "내 강의실"에서 구매한 강의를 누르면 아래 사진과 같은 수강 페이지가 보이게 됩니다. 

2) 각 단원의 첫 번째 영상을 보면 "첨부파일" 버튼이 있는데, 이를 누르면 PDF가 열려서 다운이 가능합니다^^

 

 

질문하기 방법:

인강 수강 시에 강의에서 궁금한 내용을 올리시면 다음날 까지는 답변을 드려요~

선생님의 빠르고 정확한 답변을 위해 학생분들은 아래 형식을 꼭 지켜주세요! 

 

1. 궁금한 부분의 강의 영상 번호 (1.1.1) 

2. 강의 영상의 시간

3. 궁금한 내용을 구체적으로!

 

 

강사 평점

★★★★★ 5.0

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