## Course Description

Computational methods for solving numerical problems in science, engineering and business. Linear and non-linear equations, approximation, optimization, interpolation,integration and differentiation. The aim is to give students a basic understanding of floating-point arithmetic and the implementation of algorithms used to solve numericalproblems, as well as a familiarity with current numerical computing environments.Course concepts are crucial to a wide range of practical applications such as computational finance and portfolio management, graphics and special effects, data mining and machine learning, as well as robotics, bioinformatics, medical imaging and others.

See the Syllabus for more information.

## Course Staff and Contact

**Instructor:** Lisa Zhang**Office Hours:** MF11:00-12:00, W13:00-14:00**Office:** DH3068**Email:** lczhang [at] cs [dot] toronto [dot] edu**Teachin Assistants:** Vlad, Hossein

Please include "CSC338" in your subject.

All announcements will be made on Piazza and Quercus

## Textbook

Michael Heath, Scientific Computing: An Introductory Survey, Second Edition, McGraw Hill, 2002.

Roughly the first half of the book will be covered. The relevant chapters have been made available by McGraw Hill in the textbook store at a special price.

## Tentative Schedule

The course schedule is tentative and subject to change.

Date | Course Material | Deadline | |
---|---|---|---|

Week 1 | Jan 7 | Lecture- Introduction
- Errors in Scientific Computing
- Lecture Notes [pdf]
Tutorial- Python and Jupyter Notebook
- Homework 1
Reading- Chapter 1 Slides 1-23 [pdf]
- Textbook Chapters 1.1, 1.2,
| |

Week 2 | Jan 14 | Lecture- Floating Point Numbers
- Lecture Notes [pdf]
- Notebook Output [pdf]
Tutorials- Floating Point Numbers [pdf]
Reading- Chapter 1 Slides 24-44 [pdf]
- Textbook Chapters 1.3-1.3.10
| Homework 1 (Jan 21 9pm) |

Week 3 | Jan 21 | Lecture- Systems of Linear Equations
- Gauss Elimination
- LU Factorization
Reading- Chapter 2 Slides 1-7, 23-39 [pdf]
- Textbook Chapters 2.1, 2.2, 2.4-2.4.4
Review- Essense of Linear Algebra by 3Blue1Brown [YouTube playlist]
| |

Week 4 | Jan 28 | Lecture- Vector and Matrix Norms
- Conditioning of Ax=b
- Gauss Elimination With Partial Pivoting
Reading- Chapter 2 Slides 8-22, 40-42 [pdf]
- Textbook Chapters 2.3, 2.4.5
| Homework 2 (Feb 4 9pm) |

Week 5 | Feb 4 | Lecture- Solving Modified Systems of Linear Equations
- Implementation Concerns
Reading- Chapter 2 Slides [pdf]
- Textbook Chapters 2.3
| |

Week 6 | Feb 11 | Lecture- Midterm
Tutorial- Midterm Take-up
| |

Reading Week | |||

Week 7 | Feb 25 | Lecture- Linear Least Squares
Reading- Chapter 3 Slides [pdf]
- Textbook Chapters 3
| Homework 3 (Mar 4 9pm) |

Week 8 | Mar 4 | Lecture- Nonlinear Equations
Reading- Book Slides [pdf]
- Textbook Chapters 5 (TBD)
| |

Week 9 | Mar 11 | Lecture- Nonlinear Equations
Reading- Book Slides [pdf]
- Textbook Chapters 5 (TBD)
| Homework 4 (Mar 18 9pm) |

Week 10 | Mar 18 | Lecture- Optimization
Reading- Book Slides [pdf]
- Textbook Chapters 6 (TBD)
| |

Week 11 | Mar 25 | Lecture- Optimization
Reading- Book Slides [pdf]
- Textbook Chapters 6 (TBD)
| Homework 5 (Apr 1 9pm) |

Week 12 | Apr 1 | Lecture- TBD
| |

Final Exam |