MA 214 Introduction to Numerical Analysis (Spring 2016-17)

First response

Instructor Name: Prof. Sivaji Ganesh, Prof. S. Baskar

Course Type: Core

Pre-requisites: MA 105, MA 106, MA 108

Course Content: Error Analysis - Floating Point Representation, Propagation of Errors, Numerical Linear Algebra - algebraic and iterative methods to solve a system of linear eqns, eigenvalue problems, Nonlinear Equations - iterative methods like bisection, Newton-Raphson, Interpolation-finding an interpolating polynomial given a set of data points and errors, Numerical Integration and Differentiation, Numerical Ordinary Differential Equations. 

Books: The lecture notes are more than enough

Lectures: Lectures take place in LA, Slides based teaching. strict 80% attendance policy - several DXs were handed out. Teaching quality is decent.

Assignments: Tutorials are of moderate level and complement the course well.

Exams and Grading: 2 quizzes (15%), midsem(30%) and endsem(40%). 

Follow up courses: Any applied CMP course/project!

Pro-Tips: Lecture notes are your bible for this course. Every single word uttered by the prof will be from the lecture notes (for the most part). And the notes are very clear. Tutorials similarly are essential to this course. Make sure you go and note down all the solutions - invaluable before and during the exams - you'll be tested on similar ideas. Staying in touch with the class and the tuts is more than enough to do well in this course.

Respondent: Hrishikesh Iyer 

Second response

Instructor Name: Prof. Sivaji and Prof. Baskar

Course Type: Core 

Pre-requisites: Linear Algebra, Calculus 

Course Content: Error Analysis: Propagation of error, Stability of Computation
Numerical Linear Algebra: Solving Linear System, Matrix Factorization, Solving and locating eigenvalue of matrix
Nonlinear Equation: Closed and open domain iterative scheme to approximate solution of nonlinear equation
Interpolation: Newton and Lagrange form of interpolation, Newton's divided difference, Error in polynomial interpolation
Numerical Differentiation and Integration: Various methods to approximate integration and differentiation, Error in these methods
Numerical Ordinary Differential Equation: Euler method and Runge-Kutta method to approximate solution of ordinary differential equation
Books: Lecture notes are provided by the instructor in the beginning of the course. 

Lectures: Attendance policy is very strict.
Both instructors use slides to teach.
Lectures are a bit slow.
Assignments: Tutorial sheet as well as a separate exercises for each chapter is provided.

Exams and Grading: Exams: 2 quiz(15% each), 1 midsem(30%), 1 endsem(40%).

Pro-Tips: Exams were moreover careful calculation based (and calculators are allowed).
It is a good idea to go through the exercises (apart from the tutorial) once.
Do attend lecture and tutorial (around 150 students given DX grade).

Respondent: Rahul Dandwate