Search Results
Your search for courses · during 24FA · meeting requirements for FSR, Formal or Statistical Reasoning · returned 32 results
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CS 111 Introduction to Computer Science 6 credits
This course will introduce you to computer programming and the design of algorithms. By writing programs to solve problems in areas such as image processing, text processing, and simple games, you will learn about recursive and iterative algorithms, complexity analysis, graphics, data representation, software engineering, and object-oriented design. No previous programming experience is necessary. Students who have received credit for Computer Science 201 or above are not eligible to enroll in Computer Science 111.
- Fall 2024
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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NOT open to students who have completed any of the following course(s): CS 201 or greater with a grade of C- or better.
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CS 201 Data Structures 6 credits
Think back to your favorite assignment from Introduction to Computer Science. Did you ever get the feeling that “there has to be a better/smarter way to do this problem”? The Data Structures course is all about how to store information intelligently and access it efficiently. How can Google take your query, compare it to billions of web pages, and return the answer in less than one second? How can one store information so as to balance the competing needs for fast data retrieval and fast data modification? To help us answer questions like these, we will analyze and implement stacks, queues, trees, linked lists, graphs, and hash tables. Students who have received credit for a course for which Computer Science 201 is a prerequisite are not eligible to enroll in Computer Science 201.
- Fall 2024
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): CS 111 – Introduction to Computer Science with a grade of C- or better or a score of 4 or better on the Computer Science A AP exam or equivalent. Not open to students that have taken CS 200 – Data Structures with Problem Solving.
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CS 202 Mathematics of Computer Science 6 credits
This course introduces some of the formal tools of computer science, using a variety of applications as a vehicle. You’ll learn how to encode data so that when you scratch the back of a DVD, it still plays just fine; how to distribute “shares” of your floor’s PIN so that any five of you can withdraw money from the floor bank account (but no four of you can); how to play chess; and more. Topics that we’ll explore along the way include: logic and proofs, number theory, elementary complexity theory and recurrence relations, basic probability, counting techniques, and graphs.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 111 – Introduction to Computer Science with a grade of C- or better or received a score of 4 or better on the AP Computer Science exam AND MATH 101 – Calculus with Problem Solving or MATH 111 – Introduction to Calculus or greater with a grade of C- or better or greater or received a score of 4 or better on the Calculus AB AP exam or received a score of 4 or better on the Calculus BC AP exam or received a score of 5 or better on the Mathematics IB exam or equivalent.
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CS 202.00 Fall 2024
- Faculty:Sneha Narayan 🏫 👤
- Size:28
- M, WLeighton 304 11:10am-12:20pm
- FLeighton 304 12:00pm-1:00pm
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CS 208 Introduction to Computer Systems 6 credits
Are you curious what’s really going on when a computer runs your code? In this course we will demystify the machine and the tools that we use to program it. Our broad survey of how computer systems execute programs, store information, and communicate will focus on the hardware/software interface, including data representation, instruction set architecture, the C programming language, memory management, and the operating system process model.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 200 – Data Structures with Problem Solving or CS 201 – Data Structures with a grade of C- or better or equivalent.
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CS 208.00 Fall 2024
- Faculty:Tanya Amert 🏫 👤
- Size:28
- M, WLeighton 305 1:50pm-3:00pm
- FLeighton 305 2:20pm-3:20pm
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CS 208.02 Fall 2024
- Faculty:Bridger Herman 🏫 👤
- Size:28
- M, WAnderson Hall 223 12:30pm-1:40pm
- FAnderson Hall 223 1:10pm-2:10pm
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CS 251 Programming Languages: Design and Implementation 6 credits
What makes a programming language like “Python” or like “Java”? This course will look past superficial properties (like indentation) and into the soul of programming languages. We will explore a variety of topics in programming language construction and design: syntax and semantics, mechanisms for parameter passing, typing, scoping, and control structures. Students will expand their programming experience to include other programming paradigms, including functional languages like Scheme and ML.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 200 – Data Structures with Problem Solving or CS 201 – Data Structures with a grade of C- or better or equivalent.
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CS 251.00 Fall 2024
- Faculty:Josh Davis 🏫 👤
- Size:28
- M, WAnderson Hall 329 1:50pm-3:00pm
- FAnderson Hall 329 2:20pm-3:20pm
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CS 252 Algorithms 6 credits
A course on techniques used in the design and analysis of efficient algorithms. We will cover several major algorithmic design paradigms (greedy algorithms, dynamic programming, divide and conquer, and network flow). Along the way, we will explore the application of these techniques to a variety of domains (natural language processing, economics, computational biology, and data mining, for example). As time permits, we will include supplementary topics like randomized algorithms, advanced data structures, and amortized analysis.
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CS 252.00 Fall 2024
- Faculty:Layla Oesper 🏫 👤
- Size:34
- M, WAnderson Hall 329 12:30pm-1:40pm
- FAnderson Hall 329 1:10pm-2:10pm
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CS 254 Computability and Complexity 6 credits
An introduction to the theory of computation. What problems can and cannot be solved efficiently by computers? What problems cannot be solved by computers, period? Topics include formal models of computation, including finite-state automata, pushdown automata, and Turing machines; formal languages, including regular expressions and context-free grammars; computability and uncomputability; and computational complexity, particularly NP-completeness.
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CS 254.00 Fall 2024
- Faculty:Chelsey Edge 🏫 👤
- Size:34
- M, WLanguage & Dining Center 104 11:10am-12:20pm
- FLanguage & Dining Center 104 12:00pm-1:00pm
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CS 257 Software Design 6 credits
It’s easy to write a mediocre computer program, and lots of people do it. Good programs are quite a bit harder to write, and are correspondingly less common. In this course, we will study techniques, tools, and habits that will improve your chances of writing good software. While working on several medium-sized programming projects, we will investigate code construction techniques, debugging and profiling tools, testing methodologies, UML, principles of object-oriented design, design patterns, and user interface design.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 200 – Data Structures with Problem Solving or CS 201 – Data Structures with a grade of C- or better or equivalent.
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CS 257.00 Fall 2024
- Faculty:Jean Salac 🏫 👤
- Size:28
- M, WWeitz Center 235 9:50am-11:00am
- FWeitz Center 235 9:40am-10:40am
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CS 322 Natural Language Processing 6 credits
Computers are poor conversationalists, despite decades of attempts to change that fact. This course will provide an overview of the computational techniques developed in the attempt to enable computers to interpret and respond appropriately to ideas expressed using natural languages (such as English or French) as opposed to formal languages (such as C++ or Lisp). Topics in this course will include parsing, semantic analysis, machine translation, dialogue systems, and statistical methods in speech recognition.
- Fall 2024
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): CS 200 or CS 201 – Data Structures AND CS 202 – or MATH 236 – Mathematical Structures with a grade of C- or better or equivalent. MATH 236 will be accepted in lieu of Computer Science 202.
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CS 322.00 Fall 2024
- Faculty:Eric Alexander 🏫 👤
- Size:34
- M, WLanguage & Dining Center 104 12:30pm-1:40pm
- FLanguage & Dining Center 104 1:10pm-2:10pm
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CS 338 Computer Security 6 credits
When hackers can disable gas pipelines, national hospital systems, and electrical grids, and data brokers can create a largely unregulated world-wide surveillance system, there’s a clear need for people who understand the mechanisms of computer security and insecurity. Towards that end, in this course we will study technical and social aspects of computer and network security. Topics will include threat modeling, cryptography, secure network protocols, web security, ethical hacking and penetration testing, authentication, authorization, historical hacking incidents, usability, privacy, and security-related law.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 200 – Data Structures with Problem Solving or CS 201 – Data Structures with a grade of C- or better or equivalent.
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CS 338.00 Fall 2024
- Faculty:Jeff Ondich 🏫 👤
- Size:34
- M, WAnderson Hall 329 8:30am-9:40am
- FAnderson Hall 329 8:30am-9:30am
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CS 364 Computational Modeling and Simulation of Natural Systems 6 credits
Computational models have become a fundamental part of how we make sense of the world, doing everything from economic forecasting to simulating the birth of the universe. But we need to understand how to use models effectively. In this class we’ll explore computational models used across many disciplines, including: agent-based models to prevent forest fires, compartmental models to protect endangered species, N-body models to track the spread of germs from a sneeze, and more. We’ll learn about what problems are (and are not) suited for computational modeling and engage with extensive datasets to evaluate and refine models for practical use.
- Fall 2024
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): CS 200 – Data Structures with Problem Solving or CS 201 – Data Structures with a grade of C- or better or equivalent.
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ENTS 232 Research Methods in Environmental Studies 3 credits
This course covers various methodologies that are used to prosecute interdisciplinary academic research relating to the environment. Among the topics covered are: identification of a research question, methods of analysis, hypothesis testing, and effective rhetorical methods, both oral and written.
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ENTS 232.00 Fall 2024
- Faculty:Mark Kanazawa 🏫 👤
- Size:25
- THWillis 204 8:15am-10:00am
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LING 115 Introduction to the Theory of Syntax 6 credits
This course is organized to enable the student to actively participate in the construction of a rather elaborate theory of the nature of human cognitive capacity to acquire and use natural languages. In particular, we concentrate on one aspect of that capacity: the unconscious acquisition of a grammar that enables a speaker of a language to produce and recognize sentences that have not been previously encountered. In the first part of the course, we concentrate on gathering notation and terminology intended to allow an explicit and manageable description. In the second part, we depend on written and oral student contributions in a cooperative enterprise of theory construction.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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LING 115.00 Fall 2024
- Faculty:Catherine Fortin 🏫 👤
- Size:20
- M, WLeighton 236 12:30pm-1:40pm
- FLeighton 236 1:10pm-2:10pm
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LING 217 Phonetics and Phonology 6 credits
Although no two utterances are ever exactly the same, we humans don’t function like tape recorders; we overlook distinctions to which mechanical recording devices are sensitive, and we “hear” contrasts which are objectively not there. What we (think we) hear is determined by the sound system of the language we speak. This course examines the sound systems of human languages, focusing on how speech sounds are produced and perceived, and how these units come to be organized into a systematic network in the minds of speakers of languages.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): One 100-level LING course with grade of C- or better.
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LING 217.00 Fall 2024
- Faculty:Andrew Bray 🏫 👤
- Size:25
- T, THLeighton 330 10:10am-11:55am
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LING 315 Topics in Syntax 6 credits
What moves where, how, and for what purpose? In this course, participants explore accounts of various types of syntactic movement within the Minimalist Program. After an introduction to Minimalism, we read, discuss, and evaluate primary literature. This course offers an overview of the progression of generative syntactic theory from the mid-1980s to the mid-1990s, with a focus on objectively comparing competing analyses. By the end of the course, participants will have familiarity with scholarly literature on theoretical syntax; with evaluating and critiquing existing theoretical analyses; and with proposing and defending a novel analysis.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): LING 216 with grade of C- or better.
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LING 315.00 Fall 2024
- Faculty:Catherine Fortin 🏫 👤
- Size:25
- M, WLibrary 305 9:50am-11:00am
- FLibrary 305 9:40am-10:40am
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MATH 101 Calculus with Problem Solving 6 credits
An introduction to the central ideas of calculus with review and practice of those skills needed for the continued study of calculus. Problem solving strategies will be emphasized. In addition to regular MWF class time, students will be expected to attend two problem-solving sessions each week, one on Monday or Tuesday, and one on Wednesday or Thursday. Details will be provided on the first day of class.
Extra time for TTH labs. Not open to students who have received credit for MATH 111
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has received a score of 101 on the Carleton Math Placement exam. Not open to students who have received credit for Mathematics 111. For more information, see the Mathematics' web page.
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MATH 111 Introduction to Calculus 6 credits
An introduction to the differential and integral calculus. Derivatives, antiderivatives, the definite integral, applications, and the fundamental theorem of calculus.
Not open to students who have received credit for MATH 101
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has received a score of 111 on the Carleton Math Placement exam. Not open to students who have received credit for Mathematics 101 or received a score of 4 or better on the Calculus AB AP exam or received a score of 4 or better on the Calculus BC AP exam or received a score of 5 or better on the Calculus IB exam. For more information, see the Mathematics' web page.
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MATH 120 Calculus 2 6 credits
Inverse functions, integration by parts, improper integrals, modeling with differential equations, vectors, calculus of functions of two independent variables including directional derivatives and double integrals, Lagrange multipliers.
Not open to students who have received credit for MATH 211 or have a score of 4 or 5 on the AP Calculus BC exam.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): MATH 101 – Calculus with Problem Solving or MATH 111 – Introduction to Calculus with a grade of C- or better or received a scored of 4 or better on AP Calculus AB test or received a scored of 5 or better on Calculus IB test or placement exam. Not open to students who received a scored of 4 or better on the AP Calculus BC test or completed MATH 211 with a grade of C- or better.
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MATH 134 Linear Algebra with Applications 6 credits
Linear algebra centers on the geometry, algebra, and applications of linear equations. It is pivotal to many areas of mathematics, natural sciences, computer science, and engineering. To study linear equations, we will develop concepts including matrix algebra, linear independence, determinants, eigenvectors, and orthogonality. Students will use these tools to model real world problems and solve these problems using computational software.
This course is not open to students who have received credit for MATH 232.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Not open to students who have taken MATH 232 – Linear Algebra or equivalents.
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MATH 211 Introduction to Multivariable Calculus 6 credits
Vectors, curves, partial derivatives, gradient, multiple and iterated integrals, line integrals, Green’s theorem.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has received a score of 4 or better on the AP Calculus BC exam or received a score of 211 on the Carleton Math Placement exam.
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MATH 232 Linear Algebra 6 credits
Linear algebra centers on the study of highly structured functions called linear transformations. Given the abundance of nonlinear functions in mathematics, it may come as a surprise that restricting to linear ones opens the door to a rich and powerful theory that finds applications throughout mathematics, statistics, computer science, and the natural and social sciences. Linear transformations are everywhere, once we know what to look for. They appear in calculus as the functions that are used to define lines and planes in Euclidean space. In fact, differentiation is also a linear transformation that takes one function to another. The course focuses on developing geometric intuition as well as computational matrix methods. Topics include kernel and image of a linear transformation, vector spaces, determinants, eigenvectors and eigenvalues.
This course is not open to students who have received credit for MATH 134.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): MATH 120 – Calculus 2 or MATH 211 – Introduction to Multivariable Calculus with a grade of C- or better or equivalent.
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MATH 236 Mathematical Structures 6 credits
Basic concepts and techniques used throughout mathematics. Topics include logic, mathematical induction and other methods of proof, problem solving, sets, cardinality, equivalence relations, functions and relations, and the axiom of choice. Other topics may include: algebraic structures, graph theory, and basic combinatorics.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): MATH 134 – Linear Algebra with Applications or MATH 232– Linear Algebra AND MATH 210 – Calculus 3 or MATH 211 – Multivariable Calculus with a grade of C- or better or equivalent.
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MATH 240 Probability 6 credits
Introduction to probability and its applications. Topics include discrete probability, random variables, independence, joint and conditional distributions, expectation, limit laws and properties of common probability distributions.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): MATH 120 or MATH 211 or greater with a grade of C- or better or received a score of 4 or better on the Calculus BC AP exam or equivalent.
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MATH 241 Ordinary Differential Equations 6 credits
Ordinary differential equations are a fundamental language used by mathematicians, scientists, and engineers to describe processes involving continuous change. In this course we develop ordinary differential equations as models of real world phenomena and explore the mathematical ideas that arise within these models. Topics include separation of variables; phase portraits; equilibria and their stability; non-dimensionalization; bifurcation analysis; and modeling of physical, biological, chemical, and social processes.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student must have completed any of the following course(s): MATH 134 – Linear Algebra with Applications or MATH 232 – Linear Algebra AND MATH 120 – Calculus 2 or MATH 211 – Multivariable Calculus with a grade of C- or better or equivalents.
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MATH 295 Numerical Differential Equations 6 credits
An introduction to numerical methods to compute approximate solutions of differential equations. Material will be selected from a range of topics such as error analysis, numerical differentiation, Euler and Runge-Kutta methods, predictor-corrector methods, boundary value problems, and curve fitting. Applications to other subjects such as physics, chemistry, ecology, epidemiology and neuroscience will be covered. Programming experience is not required.
- Fall 2024
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): MATH 134 – Linear Algebra with Applications or MATH 232 – Linear Algebra with a grade of C- or better or equivalent.
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MATH 342 Abstract Algebra I 6 credits
Introduction to algebraic structures, including groups, rings, and fields. Homomorphisms and quotient structures, polynomials, unique factorization. Other topics may include applications such as Burnside’s counting theorem, symmetry groups, polynomial equations, or geometric constructions.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): MATH 236 – Mathematical Structures with a grade of C- or better or equivalent.
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MATH 344 Differential Geometry 6 credits
Differential geometry is the study of shapes (like curves and surfaces) using tools from linear algebra and calculus. In this course we focus on the differential geometry of curves and surfaces and the concepts of curvature, geodesics, and first and second fundamental forms. These concepts will lead us to remarkable results like the Theorem Egregium and the Gauss-Bonnet Theorem, which relate the ways that curvature and shape interact.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): MATH 236 – Mathematical Structures with a grade of C- or better or equivalent.
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STAT 120 Introduction to Statistics 6 credits
Introduction to statistics and data analysis. Practical aspects of statistics will be emphasized, including extensive use of programming in the statistical software R, interpretation and communication of results. Topics include: exploratory data analysis, correlation and linear regression, design of experiments, the normal distribution, randomization approach to inference, sampling distributions, estimation, and hypothesis testing. Students who have taken Mathematics 211 are encouraged to consider the more advanced Mathematics 240/Statistics 250 Probability/Statistical Inference sequence.
Not open to students who have already received credit for Psychology 200/201, Sociology/Anthropology 239 or Statistics 250
- Fall 2024
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Not open to students that have taken PSYC 200 – Measurement and Data Analysis in Psychology, PSYC 201 – Measurement and Data Analysis Lab , SOAN 239 – Social Statistics or STAT 250 – Introduction to Statistical Inference.
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STAT 220 Introduction to Data Science 6 credits
This course will cover the computational side of data analysis, including data acquisition, management, and visualization tools. Topics may include: data scraping, data wrangling, data visualization using packages such as ggplots, interactive graphics using tools such as Shiny, an introduction to classification methods, and understanding and visualizing spatial data. We will use the statistics software R in this course.
- Fall 2024
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): STAT 120 – Introduction to Statistics or STAT 230 – Applied Regression Analysis, or STAT 250 – Introduction to Statistical Inference with a grade of C- or better.
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STAT 230 Applied Regression Analysis 6 credits
A second course in statistics covering simple linear regression, multiple regression and ANOVA, and logistic regression. Exploratory graphical methods, model building and model checking techniques will be emphasized with extensive use of statistical software R to analyze real-life data.
- Fall 2024
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): STAT 120 – Introduction to Statistics or STAT 250 – Introduction to Statistical Inference or PSYC 200 – Measurement & Data Analysis or SOAN 239 – Social Statistics with a grade of C- or better or received a score of 4 or better on the Statistics AP exam.
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STAT 270 Statistical Learning 6 credits
Statistical learning (sometimes called statistical machine learning) centers on the discovery of structural patterns and making predictions using complex data sets. This course explores supervised and unsupervised statistical learning methods, and the ethical considerations of their use. Topics may include nonparametric regression, classification, cross validation, linear model selection techniques and regularization, and clustering. Students will implement these concepts using open-source computational tools, such as the R language.
Not open to students who have received credit for CS 320
- Fall 2024
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): STAT 230 Applied Regression Analysis with a grade of C- or better and has NOT taken CS 320 – Machine Learning
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STAT 285 Statistical Consulting 2 credits
Students will apply their statistical knowledge by analyzing data problems solicited from the Northfield community. Students will also learn basic consulting skills, including communication and ethics.
All interested students are encouraged to add to the waitlist and the instructor will reach out after registration. This course is repeatable, but if the instructor cannot admit every student on the waitlist, priority will be given first to Statistics majors who have not previously taken the course and then to other students who have not taken the course.
- Fall 2024
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed the following course(s): STAT 230 with a grade of C- or better.