1. Relations and Functions

 Content: Discusses types of relations and functions, their compositions, and inverses. Also covers binary operations.

 Objective: Understand different kinds of relations and functions, and how to perform operations on them.

 2. Algebra of Matrices

 Content: Focuses on the basics of matrices, matrix operations (addition, multiplication), and the application of matrices in solving linear equations.

 Objective: Learn how to perform operations with matrices and apply them in solving systems of linear equations.

 3. Inverse Trigonometric Functions

 Content: Explores the concepts and properties of inverse trigonometric functions, their domain, range, and graphical representation.

 Objective: Understand the use of inverse trigonometric functions in solving equations and realworld problems.

 4. Linear Programming

 Content: Introduces the formulation of linear programming problems and discusses methods to solve them graphically.

 Objective: Learn to model reallife optimization problems using linear programming and solve them graphically.

 5. Continuity and Differentiability

 Content: Covers the concepts of continuity and differentiability of functions, including higherorder derivatives, and mean value theorems.

 Objective: Understand the fundamentals of calculus, especially the behavior of functions with respect to their continuity and differentiability.

 6. Applications of Derivatives

 Content: Explains how derivatives are used in reallife applications like rate of change, tangents and normals, maxima and minima, and approximation.

 Objective: Apply the concept of derivatives in practical situations involving optimization and curve sketching.

 7. Integrals

 Content: Focuses on indefinite and definite integrals, their properties, and techniques of integration, including substitution, partial fractions, and integration by parts.

 Objective: Master integration techniques and understand their application in finding areas under curves.

 8. Probability

 Content: Introduces conditional probability, Bayes' theorem, independent events, random variables, and probability distributions.

 Objective: Analyze and solve problems involving uncertainty using advanced probability techniques.

 9. Statistics

 Content: Discusses measures of central tendency, dispersion, correlation, and regression. Also covers analysis of data and distribution fitting.

 Objective: Learn to organize, analyze, and interpret statistical data, and apply concepts of correlation and regression to realworld data.