MA214: Introduction to Numerical Analysis
Course Instructor: Prof. Sivaji G. Sista
Course Name: MA214: Introduction to Numerical Analysis, Spring 2018-19
Credits: 8
Course Type: Core, Theory
Prerequisites:
Formal: None
Informal: None(although knowing some tidbits of Multivariable calculus such as Taylor's expansion for many variables and matrix decomposition might help but can be picked up during the course too)
Course Content:
Mathematical Prelims(Cauchy sequences, Differentiation, Taylor's theorem)
Error Analysis (floating-point approx., error propagation for different operations, rounding and significant digits)
Numerical Linear Algorithms ( methods for solving system of linear equations, errors involved thereof, iterative methods and eigenvalue probs)
Non-linear equations(solvability and methods)
Interpolation
Methods of Numerical Integration and Differentiation
Numerical Solution of Ode's
Lectures: Slides were used though Prof Didn't upload them. Quality - Sir's teaching was more or less the same as given in the lecture notes and could be covered easily by self-study (the reason for many people not turning up). However, he did discuss some non-trivial applications of discussed methods in class itself that turned up in midsem as one of the problems. Attendance policy - 80% was the norm and proxies were dealt harshly, resulting in grade penalty.
Assignments: Assignments, typically consisting of end of chapter problems of lecture notes, were pretty chill. Not graded though.
Exams: There were 3 quizzes of 15 marks each, midsems of 25 marks and endsems worth 40 marks. AP was awarded at >100 marks. Difficulty was medium to tough level, though partial marking did help.
Online Study Material: Not required
Advanced Follow-up Courses: N/A
Pro Tips: Do's- Practice as many problems as you can from end of chapter, previous years etc. A knowledge of assumptions made by each method and errors involved surely helps from an exam point of view. Avoid losing marks in quizzes and try to remember various formulas towards the end(they are too many).
Dont's- Proxy attendance can really screw up your grade and may result in penalty too.
Personal Comments: Though I did feel the course to be a bit mechanistic, several methods such as Simpson's rule to estimate integrals or Gerschgorin theorem to find the bound for eigenvalues of a matrix or to determine it's invertibility can serve as handy tools to keep in your arsenal.
Course Name: MA214: Introduction to Numerical Analysis, Spring 2018-19
Credits: 8
Course Type: Core, Theory
Prerequisites:
Formal: None
Informal: None(although knowing some tidbits of Multivariable calculus such as Taylor's expansion for many variables and matrix decomposition might help but can be picked up during the course too)
Course Content:
Mathematical Prelims(Cauchy sequences, Differentiation, Taylor's theorem)
Error Analysis (floating-point approx., error propagation for different operations, rounding and significant digits)
Numerical Linear Algorithms ( methods for solving system of linear equations, errors involved thereof, iterative methods and eigenvalue probs)
Non-linear equations(solvability and methods)
Interpolation
Methods of Numerical Integration and Differentiation
Numerical Solution of Ode's
Other Topics covered: N/A
Books:
Selected Chapters of Lecture Notes(authored by the same Prof) were put up weekly for reference and was quite sufficient. Other than that, Atkinson and Han and Cante de Boor was mentioned in the tut sheets but never used it myself.
Selected Chapters of Lecture Notes(authored by the same Prof) were put up weekly for reference and was quite sufficient. Other than that, Atkinson and Han and Cante de Boor was mentioned in the tut sheets but never used it myself.
Lectures: Slides were used though Prof Didn't upload them. Quality - Sir's teaching was more or less the same as given in the lecture notes and could be covered easily by self-study (the reason for many people not turning up). However, he did discuss some non-trivial applications of discussed methods in class itself that turned up in midsem as one of the problems. Attendance policy - 80% was the norm and proxies were dealt harshly, resulting in grade penalty.
Exams: There were 3 quizzes of 15 marks each, midsems of 25 marks and endsems worth 40 marks. AP was awarded at >100 marks. Difficulty was medium to tough level, though partial marking did help.
Online Study Material: Not required
Advanced Follow-up Courses: N/A
Pro Tips: Do's- Practice as many problems as you can from end of chapter, previous years etc. A knowledge of assumptions made by each method and errors involved surely helps from an exam point of view. Avoid losing marks in quizzes and try to remember various formulas towards the end(they are too many).
Dont's- Proxy attendance can really screw up your grade and may result in penalty too.
Personal Comments: Though I did feel the course to be a bit mechanistic, several methods such as Simpson's rule to estimate integrals or Gerschgorin theorem to find the bound for eigenvalues of a matrix or to determine it's invertibility can serve as handy tools to keep in your arsenal.
Respondent: Guru Kalyan Jayasingh
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