## CS 231N: Deep Learning for Computer Vision

Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification and object detection. Recent developments in neural network approaches have greatly advanced the performance of these state-of-the-art visual recognition systems. This course is a deep dive into details of neural-network based deep learning methods for computer vision. During this course, students will learn to implement, train and debug their own neural networks and gain a detailed understanding of cutting-edge research in computer vision. We will cover learning algorithms, neural network architectures, and practical engineering tricks for training and fine-tuning networks for visual recognition tasks.Prerequisites: Proficiency in Python - All class assignments will be in Python (and use numpy) (we provide a tutorial here for those who
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Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification and object detection. Recent developments in neural network approaches have greatly advanced the performance of these state-of-the-art visual recognition systems. This course is a deep dive into details of neural-network based deep learning methods for computer vision. During this course, students will learn to implement, train and debug their own neural networks and gain a detailed understanding of cutting-edge research in computer vision. We will cover learning algorithms, neural network architectures, and practical engineering tricks for training and fine-tuning networks for visual recognition tasks.Prerequisites: Proficiency in Python - All class assignments will be in Python (and use numpy) (we provide a tutorial here for those who aren't as familiar with Python). If you have a lot of programming experience but in a different language (e.g. C/C++/Matlab/Javascript) you will probably be fine.College Calculus, Linear Algebra (e.g.
MATH 19,
MATH 51) -You should be comfortable taking derivatives and understanding matrix vector operations and notation. Basic Probability and Statistics (e.g.
CS 109 or other stats course) -You should know basics of probabilities, gaussian distributions, mean, standard deviation, etc.

Terms: Spr
| Units: 3-4

Instructors:
Adeli, E. (PI)
;
Li, F. (PI)

## ENGR 15: Dynamics

The application of Newton's Laws to solve 2-D and 3-D static and dynamic problems, particle and rigid body dynamics, freebody diagrams, and equations of motion, with application to mechanical, biomechanical, and aerospace systems. Computer numerical solution and dynamic response. Prerequisites: Calculus (differentiation and integration) such as
Math 19, 20; and
ENGR 14 (statics and strength).

Terms: Aut
| Units: 3
| UG Reqs: WAY-SMA, GER:DB-EngrAppSci

Instructors:
Kennedy, M. (PI)
;
Jitosho, R. (TA)
;
Kitzmann, M. (TA)
...
more instructors for ENGR 15 »

Instructors:
Kennedy, M. (PI)
;
Jitosho, R. (TA)
;
Kitzmann, M. (TA)
;
Morstein, S. (TA)
;
Pham, G. (TA)

## ENGR 199A: Additional Calculus for Engineers

Additional problem solving practice for the calculus courses. Sections are designed to allow students to acquire a deeper understanding of calculus and its applications, work collaboratively, and develop a mastery of the material. Limited enrollment, permission of instructor required. Concurrent enrollment in
MATH 19, 20, 52, or 53 required

Terms: Win, Spr
| Units: 1
| Repeatable
for credit

Instructors:
Andrade, L. (PI)

## MATH 19: Calculus

Introduction to differential calculus of functions of one variable. Review of elementary functions (including exponentials and logarithms), limits, rates of change, the derivative and its properties, applications of the derivative. Prerequisites: periodic trigonometric functions, advanced algebra, and analysis of elementary functions (including exponentials and logarithms). You must have taken the math placement diagnostic (offered through the Math Department website:
https://mathematics.stanford.edu/academics/math-placement) in order to register for this course.

Terms: Aut, Win
| Units: 3
| UG Reqs: GER:DB-Math, WAY-FR

Instructors:
Stadlmann, J. (PI)
;
Wickham, Z. (PI)

## MATH 19ACE: Calculus, ACE

Additional problem solving session for
Math 19 guided by a course assistant. Concurrent enrollment in
Math 19 required. Application required:
https://engineering.stanford.edu/students-academics/equity-and-inclusion-initiatives/undergraduate-programs/additional-calculus

Terms: Aut
| Units: 1

## MATH 20: Calculus

The definite integral, Riemann sums, antiderivatives, the Fundamental Theorem of Calculus. Integration by substitution and by parts. Area between curves, and volume by slices, washers, and shells. Initial-value problems, exponential and logistic models, direction fields, and parametric curves. Prerequisite:
Math 19 or equivalent. If you have not previously taken a calculus course at Stanford then you must have taken the math placement diagnostic (offered through the Math Department website:
https://mathematics.stanford.edu/academics/math-placement) in order to register for this course.

Terms: Aut, Win, Spr
| Units: 3
| UG Reqs: GER:DB-Math, WAY-FR

## PHYSICS 41E: Mechanics, Concepts, Calculations, and Context

Physics 41E (
Physics 41 Extended) is a 5-unit version of
Physics 41 (4 units) for students with little or no high school physics. Course topics and mathematical complexity are similar, but not identical to
Physics 41. There is an additional class meeting every week, and attendance at all class sessions is mandatory. The extra classroom time and corresponding extra study time outside of class allows students to engage with concepts and become fluent in mathematical tools that include vector representations and operations, and relevant calculus. There is a strong emphasis on developing problem-solving skills, particularly as applied to real world examples, to leave students prepared for subsequent engineering, physics, or related courses they may take. The course will explore important physical principles in mechanics including: using Newton's Laws and torque to analyze static structures and forces; understanding the equations of kinematics; and utilizing energy in its many forms and
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Physics 41E (
Physics 41 Extended) is a 5-unit version of
Physics 41 (4 units) for students with little or no high school physics. Course topics and mathematical complexity are similar, but not identical to
Physics 41. There is an additional class meeting every week, and attendance at all class sessions is mandatory. The extra classroom time and corresponding extra study time outside of class allows students to engage with concepts and become fluent in mathematical tools that include vector representations and operations, and relevant calculus. There is a strong emphasis on developing problem-solving skills, particularly as applied to real world examples, to leave students prepared for subsequent engineering, physics, or related courses they may take. The course will explore important physical principles in mechanics including: using Newton's Laws and torque to analyze static structures and forces; understanding the equations of kinematics; and utilizing energy in its many forms and applications. Prerequisites: Physics placement diagnostic AND
Math 19 or higher Corequisites: Completion of OR co-enrollment of
Math 20 or higher. Since high school math classes vary widely, it is recommended that you take at least one math class at Stanford before or concurrently with
Physics 41E. In addition, it is required that you take
Math 21 before taking the next course in the
Physics 40 series,
Physics 43.Priority will be given to students who have had little physics background.

Terms: Aut, Win
| Units: 5
| UG Reqs: WAY-SMA

Instructors:
Bergeron, P. (PI)
;
Blakemore, C. (PI)
;
Church, S. (PI)
...
more instructors for PHYSICS 41E »

Instructors:
Bergeron, P. (PI)
;
Blakemore, C. (PI)
;
Church, S. (PI)
;
Nee, M. (TA)
;
Xiang, C. (TA)
;
Zenagui, A. (TA)

## SOAR 10MA: Preparation for Success in Mathematics at Stanford

This course will build on and enrich students' fundamental prerequisite skills in foundational mathematics to prepare students for success in Calculus and further mathematics courses at Stanford University. This course is intended for students that will enroll in the
Math 19-20-21 sequence, but will broadly be relevant and engaging for success in university-level mathematics courses at Stanford, as well as in other courses at Stanford in other disciplines that rely on these courses as prerequisites. Students will enhance their proficiency with precalculus mathematics, with an emphasis on higher level conceptual understanding and problem-solving. The primary of this course is to help students develop and hone the mathematical skills necessary to successfully transition to university level mathematics at Stanford University. The course will focus on fundamental concepts from algebra, functions and graphs, trigonometry, exponentials and logarithms, and limits.

Terms: Aut
| Units: 1

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