Course Overview:
Linear Algebra
J. H. Wang
Feb. 17, 2016
Instructor & TA
• Instructor
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J. H. Wang (王正豪)
Associate Professor, CSIE, NTUT
Office: R1534, Technology Building
E-mail: jhwang@csie.ntut.edu.tw
Tel: ext. 4238
Office Hour: 9:00-12:00 am, every Tuesday and
Thursday
• TA
– (TBA)
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Course Description
• Course Web Page:
– http://www.ntut.edu.tw/~jhwang/LA/
• Time: 4:10-6:00pm, Tue.; 9:10-10:00am, Fri.
• Classroom: R226, Sixth Teaching Building
• Textbook:
– David Lay, Stephen Lay, and Judi McDonald, Linear
Algebra and its Applications, 5th edition, Pearson,
2016.
• Global Edition, imported by 偉明圖書
• Prerequisites:
– Basic knowledge of college mathematics (calculus)
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Target Audience
• For those who
– Are EECS freshmen (or non-CSIE major
students),
– Familiar with basic college mathematics,
– Preparing to learn more details in linear
algebra, and
– Want to master the basic concepts and skills
in future careers
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Additional Resources
• References:
– Linear Algebra with Applications, 8th ed., by Steven
Leon, Pearson, 2014.
– Introduction to Linear Algebra with Applications, by
Jim DeFranza, Daniel Gagliardi, McGraw-Hill, 2009.
– Elementary Linear Algebra, 7th ed., by Ron Larson,
Cengage Learning, 2013.
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Teaching
• Lectures
• About 5-6 homework assignments
– Homeworks should be turned in within two
weeks
• 2 quizzes
– One before mid-term exam
– One before final exam
• Mid-term and final exams
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Grading Policy
• Homework assignments: ~30%
– Including programming exercises
• Quiz: ~20%
• Mid-term exam: ~25%
• Final exam: ~25%
• Note: All homework assignments and
exercises must be submitted before the
end of the semester (Jun. 24, 2016)
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Online Submission
• Submission instructions
– Systems, programs, project proposals, and
project reports in electronic files must be
submitted to the TA online at:
• Submissions website & instructions : (To be
announced)
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What Will You Learn
• The most interesting and worthwhile
undergraduate mathematics course
• Linear algebra concepts and computations
– Linear equations, matrices, eigenvalues and
eigenvectors, orthogonality and least-square
problems
• Gateway to more advanced courses and
future career
– Numerical linear algebra
Why You Need Linear Algebra
• Power of linear algebra
– Oil exploration, electrical networks, linear
programming, aircraft design, space flight and
control systems, GPS navigation, multichannel image
processing, computer graphics, …
• Wide applications in many fields
– Engineering, computer science, mathematics, physics,
biology, economics, statistics, …
• Linear algebra is a language
– You have to practice everyday
– Read and reread the text carefully
– Do the exercises
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Outline & Schedule
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Linear Equations
Matrix Algebra
Determinants
Vector Spaces
Eigenvalues and Eigenvectors
Orthogonality and Least Squares
Symmetric Matrices and Quadratic Forms
Geometry of Vector Spaces
Optimization (online)
Finite-State Markov Chains (online)
Outline & Schedule (Cont’)
• (Tentative) Schedule
– Ch.1-3: 6-7 wks
– Ch.4-5: 6-7 wks
– Ch.6: 2-3 wks
Some Tools for Linear Algebra
• Commercial packages
– Matlab, Mathematica, Maple, …
• Free numerical computational packages
– Scilab, Octave, Freemat, …
• R: open source statistical package and
language
• Open source numerical and scientific
packages in Python: scipy, numpy
•…
• And many more!
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Thanks for Your Attention!
• Any question or comment?
Please feel free to send e-mails to
jhwang@csie.ntut.edu.tw
or discuss with me at my office
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