CS 4540 (F19) Entry Survey

JavaScript isn't enabled in your browser, so this file can't be opened. Enable and reload.

Welcome to CS 4540 at Georgia Tech! Please fill out this short (~5-10min) survey to help us get to know the class better! Your response is completely anonymous.

What is your major? *

Computer Science

Computational Sci & Engr

Mathematics

Other:

If your major is Computer Science, which "threads" are you working towards?

Theory

Modeling & Simulation

Devices

Info Internetworks

Intelligence

Media

People

Systems & Architecture

Have you used any of the following before? *

Check all that apply.

Python

Numpy / Matplotlib / SciPy

Jupyter Notebooks / JupyerLab

PyTorch, TensorFlow, etc.

Matlab

C++/C

Java

Haskell

No, I haven't.

Required

PREREQUISITES & OTHER COURSES

Prerequisites: Calculus + Analysis *

Have you taken a calculus class before? Check all that apply.

Calc I + II (single-variable differentiation and integration)

Calculus III (multivariate differentiation and integration)

Advanced Calculus (proof-based; lots of epsilons and deltas)

I have never taken a calculus class.

Other:

Required

Prerequisites: Linear Algebra *

Have you taken a linear algebra class before? Check all that apply.

Intro Linear Algebra

Advanced Linear Algebra (e.g. minimal polynomials, invariant subspaces, Jordan canonical forms...)

Numerical Linear Algebra (e.g. QR factorization, Gauss-Seidel iteration, conjugate gradient...)

I have never taken a linear algebra class.

Other:

Required

Prerequisites: Probability *

Have you taken a probability class before? Check all that apply.

Intro Probability (no calculus)

Calculus-based Probability

Measure-theoretic Probability (Lebesgue integrals, sigma-algebras, MCT, etc.)

I have never taken a probability class.

Other:

Required

Other Courses

Have you taken or are you currently taking any of the following courses?

Machine Learning (e.g. CS 3600, CS 4641, CS 4646)

Artificial Intelligence (e.g. CS 3600, CS 4731, CS 4635)

Linear Programming (e.g. MATH 4580)

Numerical Analysis (e.g. MATH 4640)

Convex Optimization

Information Theory (e.g. MATH 4280)

CONCEPTS

Which of the following topics have you studied before? Check all that apply. Topics marked with (*) will not be needed for this course and are only included here to gauge your prior knowledge.

Concepts: Calculus & Analysis *

Gradient of a function f : R^n --> R

Differential of a function f : R^n --> R^m

Rigorous definition of a limit (for all epsilon > 0, exists delta > 0 such that...)

Maximizing a multivariable function; Lagrange multipliers for equality constraints

Convex function optimization; Lagrange duality; convex conjugates

Newton's Method

(*) Inverse Function Theorem / Implicit Function Theorem

(**) Measure theory (Lebesgue integrals, monotone convergence, Radon-Nikodym...)

I have never studied calculus.

Required

Concepts: Linear Algebra *

Matrices, vectors, and matrix multiplication

Basis vectors, change of basis; orthogonal vectors, Gram-Schmidt

Eigenvalues and eigenvectors

Abstract vector spaces, linear transformations

Positive-definite matrices and their eigenvalues

Solving linear systems via least-squares; Moore-Penrose pseudoinverse

Matrix Decompositions (SVD, QR, etc.)

(*) Invariant subspaces

(*) Minimal polynomials, Cayley-Hamilton

I have never studied linear algebra.

Required

Concepts: Probability & Statistics *

Discrete distributions, random variables, expectation, variance

Continuous distributions, random variables, expectation, variance

Independence; expectation and variance of independent random variables

Normal distribution, central limit theorem

Markov and Chebychev inequalities

Hoeffding and Chernoff bounds

Bayesian statistics, prior and posterior distributions, conjugate priors, exponential families

I have never studied probability.

Required

Concepts: Machine Learning *

Convolutional Neural Networks

Variational Autoencoders and/or Generative Adversarial Networks

Reinforcement Learning (MDPs, Q-learning, etc.)

Perceptron Classifiers

Kernel Regression

I have never studied machine learning.

Required

What do you hope to learn from this class?

Is there anything else you'd like to tell us? (hopes, dreams, concerns...)

Submit

Clear form

Never submit passwords through Google Forms.

This content is neither created nor endorsed by Google. Report Abuse - Terms of Service - Privacy Policy

Forms