Middlebury

 

Sections

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CSCI0101A-F13

CRN: 90099

The Computing Age

The Computing Age
In this course we will provide a broad introductory overview of the discipline of computer science, with no prerequisites or assumed prior knowledge of computers or programming. A significant component of the course is an introduction to algorithmic concepts and to programming using Python; programming assignments will explore algorithmic strategies such as selection, iteration, divide-and-conquer, and recursion, as well as introducing the Python programming language. Additional topics will include: the structure and organization of computers, the Internet and World Wide Web, abstraction as a means of managing complexity, social and ethical computing issues, and the question "What is computation?" 3 hr. lect./lab

CSCI0101B-F13

CRN: 90609

The Computing Age

The Computing Age
In this course we will provide a broad introductory overview of the discipline of computer science, with no prerequisites or assumed prior knowledge of computers or programming. A significant component of the course is an introduction to algorithmic concepts and to programming using Python; programming assignments will explore algorithmic strategies such as selection, iteration, divide-and-conquer, and recursion, as well as introducing the Python programming language. Additional topics will include: the structure and organization of computers, the Internet and World Wide Web, abstraction as a means of managing complexity, social and ethical computing issues, and the question "What is computation?" 3 hr. lect./lab

CSCI0150A-F13

CRN: 91539

Computing for the Sciences

Computing for the Sciences
In this course we will provide an introduction to the field of computer science geared towards students interested in mathematics and the natural sciences. We will study problem-solving approaches and computational techniques utilized in a variety of domains including biology, chemistry, physics, and engineering. Students will learn how to program in Python and other languages, how to extract information from large data sets, and how to utilize a common technique employed in scientific computation. The course has no prerequisites and assumes no prior experience with programming or computer science. 3 hrs. lect./lab

CSCI0190A-F13

CRN: 92468

Computer Models & Simulation

Computer Models and Multi-Agent Simulation
In this course we will explore agent-based computer models and simulations as a means of studying phenomena from both biological and social sciences. Agent-based simulation will then be used as a basis for introducing individual-based modeling and complex adaptive systems. A significant amount of time will be spent teaching the NetLogo programming language as a software tool for developing simulations. We will also introduce some of the important topics in the discipline of computer science, including algorithmic reasoning and data abstraction. No prior experience in programming is assumed. This course counts as an environmental studies lab science cognate. 3 hrs. lect./lab

CSCI0190B-F13

CRN: 92469

Computer Models & Simulation

Computer Models and Multi-Agent Simulation
In this course we will explore agent-based computer models and simulations as a means of studying phenomena from both biological and social sciences. Agent-based simulation will then be used as a basis for introducing individual-based modeling and complex adaptive systems. A significant amount of time will be spent teaching the NetLogo programming language as a software tool for developing simulations. We will also introduce some of the important topics in the discipline of computer science, including algorithmic reasoning and data abstraction. No prior experience in programming is assumed. This course counts as an environmental studies lab science cognate. 3 hrs. lect./lab

CSCI0201A-F13

CRN: 90151

Data Structures

Data Structures
In this course we will study the ideas and structures helpful in designing algorithms and writing programs for solving large, complex problems. The Java programming language and object-oriented paradigm are introduced in the context of important abstract data types (ADTs) such as stacks, queues, trees, and graphs. We will study efficient implementations of these ADTs, and learn classic algorithms to manipulate these structures for tasks such as sorting and searching. Prior programming experience is expected, but prior familiarity with the Java programming language is not assumed. (One CSCI course at the 0100-level) 3 hrs. lect./lab

CSCI0202A-F13

CRN: 90152

Computer Architecture

Computer Architecture
A detailed study of the hardware and software that make up a computer system. Topics include assembly language programming, digital logic design, microarchitecture, pipelines, caches, and RISC vs. CISC. The goal of the course is teach students how computers are built, how they work at the lowest level, and how this knowledge can be used to write better programs. (CSCI 0201 previously or concurrently) 3 hrs. lect./lab

CSCI0301A-F13

CRN: 90153

Theory of Computation

Theory of Computation
This course explores the nature of computation and what it means to compute. We study important models of computation (finite automata, push-down automata, and Turing machines) and investigate their fundamental computational power. We examine various problems and try to determine the computational power needed to solve them. Topics include deterministic versus non-deterministic computation, and a theoretical basis for the study of NP-completeness. (CSCI 0200 and CSCI 0201) 3 hrs. lect./disc.

CSCI0314A-F13

CRN: 92471

Operating Systems

Operating Systems
An operating system manages the complex resources of modern computers and provides an interface between the user and the hardware. This course covers the key concepts of operating systems, including process, memory, and storage management; synchronization and deadlock; protection and security; and distributed systems. (CSCI 0200 previously or concurrently, and CSCI 0202) 3 hrs. lect./lab

CSCI0451A-F13

CRN: 92472

Machine Learning

Machine Learning
Machine Learning is the study and design of computational systems that automatically improve their performance through experience. This course introduces the theory and practice of machine learning and its application to tasks such as database mining, pattern recognition, and strategic game-playing. Possible topics include decision-tree methods, neural networks, Bayesian and statistical methods, genetic algorithms, and reinforcement learning. (CSCI 0200 and CSCI 0201) 3 hrs. lect./lab

CSCI0500A-F13

CRN: 90549

Advanced Study

Advanced Study
Individual study for qualified students in more advanced topics in computer science theory, systems, or application areas. Particularly suited for students who enter with advanced standing. (Approval required) 3 hrs. lect.

CSCI0500D-F13

CRN: 90689

Advanced Study

Advanced Study
Individual study for qualified students in more advanced topics in computer science theory, systems, or application areas. Particularly suited for students who enter with advanced standing. (Approval required) 3 hrs. lect.

CSCI0500E-F13

CRN: 90690

Advanced Study

Advanced Study
Individual study for qualified students in more advanced topics in computer science theory, systems, or application areas. Particularly suited for students who enter with advanced standing. (Approval required) 3 hrs. lect.

CSCI0500F-F13

CRN: 90771

Advanced Study

Advanced Study
Individual study for qualified students in more advanced topics in computer science theory, systems, or application areas. Particularly suited for students who enter with advanced standing. (Approval required) 3 hrs. lect.