Hello,

Here's entire syllabus of 2nd PUC after being reduced :

Relations and Functions :
Introduction
Types of Relations
Types of Functions
Binary Operations

Inverse Trigonometric Functions :
Introduction
Basic Concepts
Principal values

Matrices :
Introduction
Matrix
Types of Matrices
Operations on Matrices
Transpose of a Matrix
Symmetric and Skew Symmetric Matrices
Invertible matrices

Determinants :
Introduction
Determinant
Area of a Triangle
Minors and Cofactors
Adjoint and Inverse of a Matrix
Applications of Determinants and Matrices

Continuity and Differentiability :
Introduction
Continuity
Differentiability
Exponential and Logarithmic Functions
Logarithmic Differentiation
Derivatives of Functions in Parametric
Forms
Second Order Derivative

Application of Derivatives :
Introduction
Rate of Change of Quantities
Increasing and Decreasing Functions
Tangents and Normals
Maxima and Minima

Integrals :
Introduction
Integration as an Inverse Process of Differentiation
Methods of Integration
Integrals of some Particular Functions
Integration by Partial Fractions
Integration by Parts
Definite Integral
Fundamental Theorem of Calculus
Evaluation of Definite Integrals by Substitution
Some Properties of Definite Integrals

Applications of Integrals :
Introduction
Area under simple curves

Differential Equations :
Introduction
Basic Concepts
Particular Solutions of a differential
Equation
Methods of Solving First order, First
Degree Differential Equations

Vector Algebra :
Introduction
Some Basic Concepts
Types of Vectors
Addition of Vectors
Multiplication of a Vector by a Scalar
Product of Two Vectors

Three Dimensional Geometry :
Introduction
Direction Cosines and Direction Ratios of a Line
Equation of a Line in Space
Shortest Distance between Two Lines
Plane
Coplanarity of Two Lines
Distance of a Point from a Plane

Linear Programming :
Introduction
Linear Programming Problem and its Mathe
matical Formulation
Different
Types of Linear Programming Problems

Probability :
Introduction
Conditional Probability
Multiplication Theorem on Probability
Independent Events
Bayes' Theorem.

I hope this helps.