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| - | **STAT E-50 Introduction to Statistics** (20993) | ||
| - | http://isites.harvard.edu/icb/icb.do?keyword=k48021 | ||
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| - | Spring term: Tuesdays, 7:30-9:30 pm. | ||
| - | Location: Harvard Hall 104 | ||
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| - | Joan Weinstein, CAS, MA, Professor of Mathematics and Computers, Pine Manor College. | ||
| - | Course tuition: undergraduate credit $950, graduate credit $1,725. Optional sections to be arranged. | ||
| - | Online and on-campus options. See Distance Education. | ||
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| - | This course is an introduction to descriptive and inferential statistics, including correlation and regression, hypothesis testing, estimation, and elementary probability. Students learn to analyze data using PC-based statistical software. No previous knowledge of statistics is assumed. Prerequisites: high school algebra, or the equivalent. (4 credits) | ||
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| **CSCI E-119 Data Structures** (22568) | **CSCI E-119 Data Structures** (22568) | ||
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| A survey of fundamental data structures for information processing, including lists, stacks, queues, trees, and graphs. The course explores the implementation of these data structures (both array-based and linked representations) and examines classic algorithms that use these structures for tasks such as sorting, searching, and text compression. The Java programming language is used to demonstrate the topics discussed; and key notions of object-oriented programming, including encapsulation and abstract data types, are emphasized. Prerequisites: a good working knowledge of Java (CSCI E-50b, or the equivalent). (4 credits) | A survey of fundamental data structures for information processing, including lists, stacks, queues, trees, and graphs. The course explores the implementation of these data structures (both array-based and linked representations) and examines classic algorithms that use these structures for tasks such as sorting, searching, and text compression. The Java programming language is used to demonstrate the topics discussed; and key notions of object-oriented programming, including encapsulation and abstract data types, are emphasized. Prerequisites: a good working knowledge of Java (CSCI E-50b, or the equivalent). (4 credits) | ||
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| - | **CSCI E-162 Distributed and Enterprise Computing** (21510) | ||
| - | (Website) (Check Availability and Location) | ||
| - | James Farley, MS, Director of Innovation Services, Cambridge Technology Enterprises. | ||
| - | Course tuition: noncredit and graduate credit $1,725. | ||
| - | Spring term: Thursdays, 5:30-7:30 pm. Optional sections to be arranged. | ||
| - | Online and on-campus options. See Distance Education. | ||
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| - | This course offers an in-depth, immersive study of the practice of building enterprise systems within the Java programming environment and Java Enterprise Edition (Java EE) framework. The course progresses through a series of units (basic tools of the trade, messaging, data and directory services), covering along the way many of the key application programming interfaces (APIs) and tools used to develop enterprise applications. The tools and APIs covered include XML, JavaServer Faces, Java Persistence API, and Enterprise JavaBeans. Programming assignments give students hands-on experience with these tools of the trade, and the final project provides a chance to engage in a more involved system design using these tools. Prerequisites: introduction to programming in Java; CSCI E-160, or the equivalent. Students are expected to be knowledgeable about the Java programming environment prior to taking this course. (4 credits) | ||
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| - | **MATH E-21b Linear Algebra** (21474) | ||
| - | http://math.rwinters.com/E21b/ | ||
| - | Robert Winters, PhD, Lecturer in Mathematics, Brandeis University. | ||
| - | Course tuition: noncredit and undergraduate credit $800, graduate credit $1,725. | ||
| - | Spring term: Thursdays, 7:30-9:30 pm. Optional sections to be arranged. | ||
| - | Harvard Hall 201 | ||
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| - | This course covers the following topics: solving systems of linear equations; matrices and linear transformations; image and kernel of a linear transformation; matrices and coordinates relative to different bases; determinants; eigenvalues and eigenvectors; discrete and continuous dynamical systems; least-squares approximation; applications in function spaces. Graduate-credit students complete additional computer-related or other projects consistent with the course material and their backgrounds. Prerequisites: MATH E-16, or the equivalent, and general familiarity with matrix-capable calculators or mathematical software. (4 credits) | ||
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| - | MATH E-15 **Introduction to the Calculus A** Eric C. Towne | ||
| - | Thur 6 – 9 pm Emerson Hall 21 | ||
| - | http://www.extension.harvard.edu/2008-09/courses/20399.jsp?caller=dce | ||
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| - | This is a complete course in first-semester calculus. Topics include the meaning, use, and interpretation of the derivative; techniques of differentiation; applications to curve sketching and optimization in a variety of disciplines; the definite integral and some applications; and the fundamental theorem of calculus. Students enrolling for graduate credit participate in weekly pedagogical seminars designed for current and future K-12 teacher | ||
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