Online Summer Undergraduate Courses

This online course provides students who have already achieved a basic understanding of programming and computational thinking in one programming language with an opportunity to apply these skills in another programming language. Students will be expected to complete projects to demonstrate proficiency in the new language. Satisfactory/Unsatisfactory only

Prerequisites: Not open to students who have completed EN.500.113 (Gateway Computing: Python). Students must have completed: EN.500.112 (Gateway Computing: JAVA) or EN.500.114 (Gateway Computing: Matlab) or EN.510.202 (Computation and Programming for Materials Scientists and Engineers) or EN.520.123 (Computational Modeling for Electrical and Computer Engineering) or EN.601.220 (Intermediate Programming.)

This online course is primarily delivered asynchronously; however, your instructor may schedule live interactions as well. Please refer to your syllabus for these opportunities and for important course deadlines.

This is a two-course sequence in the differential and integral calculus of functions of one independent variable. Topics include the basic analytic geometry of graphs of functions, and their limits, integrals and derivatives, including the Fundamental Theorem of Calculus. Also, some applications of the integral, like arc length and volumes of solids with rotational symmetry, are discussed. Applications to the physical sciences and engineering will be a focus of this course, as this sequence of courses is designed to meet the needs of students in these disciplines.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

This is a second course in the calculus of functions of one independent variable. However, instead of continuing with standard calculus topics, this semester includes an introduction to differential equations, the basic structure of functions of several variables, an introduction to linear systems and linear algebra, and applications for systems of linear differential equations and probability distributions. Applications to the biological and social sciences will be discussed, and the course is designed to meet the needs of students in these disciplines.

Prerequisites: AS.110.106 (Calculus I for Biological or Social Sciences) or AS.110.108 (Calculus I for Physical Sciences and Engineering) or an Advanced Placement AB score of 3 or better.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

This is the second of a two-course sequence in the differential and integral calculus of functions of one independent variable. Topics include the basic and advanced techniques of integration, analytic geometry of graphs of functions, and their limits, integrals and derivatives, including the Fundamental Theorem of Calculus. Also, some applications of the integral, like arc length and volumes of solids with rotational symmetry, are discussed. Applications to the physical sciences and engineering will be a focus of this course, as this sequence of courses is designed to meet the needs of students in these disciplines.

Prerequisites: AS.110.106 (Calculus I for Biology and Social Sciences) or AS110.108 (Calculus I For Physical Sciences and Engineering), or a Advanced Placement AB score of 5.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

This is a course in the differential and integral calculus of several variables. Topics include vectors in two and three dimensions, analytic geometry of three dimensions, parametric curves, partial derivatives, the gradient, optimization in several variables, multiple integration with change of variables across different coordinate systems, line integrals, surface integrals, and Green’s Theorem, Stokes’ Theorem, and Gauss’ Divergence Theorem.

Prerequisite: AS.110.107 (Calculus II for Biological and Social Sciences) or AS.110.109 (Calculus II for Physical Sciences and Engineering) or AS.110.113 (Honors Single Variable Calculus) or an Advanced Placement BC score of 5.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

Students will examine a variety of topics regarding policy, legal, and moral issues related to the computer science profession itself and to the proliferation of computers in all aspects of society, especially in the era of the Internet. The course will cover various general issues related to ethical frameworks and apply those frameworks more specifically to the use of computers and the Internet. The topics will include privacy issues, computer crime, intellectual property law -- specifically copyright and patent issues, globalization, and ethical responsibilities for computer science professionals. Work in the course will consist of weekly assignments on one or more of the readings and a final paper on a topic chosen by the student and approved by the instructor.

We study the design and performance of a variety of computer systems from simple 8-bit micro-controllers through 32/64-bit RISC architectures all the way to ubiquitous x86 CISC architecture. We'll start from logic gates and digital circuits before delving into arithmetic and logic units, registers, caches, memory, stacks and procedure calls, pipelined execution, super-scalar architectures, memory management units, etc. Along the way we'll study several typical instruction set architectures and review concepts such as interrupts, hardware and software exceptions, serial and other peripheral communications protocols, etc. A number of programming projects, frequently done in assembly language and using various processor simulators, round out the course.

Prerequisite: EN.601.220 (Intermediate Programming).

In this course, you will explore the culture of engineering while preparing to think and communicate effectively with the various audiences with whom engineers interact. You will read, discuss, present, and write about major themes and questions in engineering today. We explore the origins and evolution of the engineering profession, the dreams and nightmares of our engineered world, and today’s major debates in engineering ethics. Over the course of the semester, you will boost your ability to think and communicate as an informed engineer. Assignments may include ethical analyses, case studies, multimodal technical documents, argumentative essays about the history and trajectory of the field, professional presentations, and proposals supporting improved, human-friendly outcomes in engineering.

A writing-intensive course (W) engages students in multiple writing projects, ranging from traditional papers to a wide variety of other forms, distributed throughout the term. Assignments include a mix of high and low stakes writing, meaning that students have the chance to write in informal, low-pressure--even ungraded--contexts, as well as producing larger, more formal writing assignments. Students engage in writing in the classroom through variety of means, including class discussions, workshop, faculty/TA lectures, and class materials (for instance, strong and weak examples of the assigned genre). Expectations are clearly conveyed through assignment descriptions, including the genre and audience of the assigned writing, and evaluative criteria. Students receive feedback on their writing, in written and/or verbal form, from faculty, TAs, and/or peers. Students have at least one opportunity to revise.

This course covers the design, implementation and efficiencies of data structures and associated algorithms, including arrays, stacks, queues, linked lists, binary trees, heaps, balanced trees and graphs. Other topics include sorting, hashing, Java generics, and unit testing. Course work involves both written homework and Java programming assignments.

Prerequisite: A grade of C+ or better in EN.500.112 (Gateway Computing: Java) OR EN.601.220 (Intermediate Programming) OR EN.500.132 (Bootcamp: Java) OR a score of 5 on the AP Computer Science A Exam. Students can't register until grades for prerequisites are posted.

CRISPR (clustered regularly-interspaced short palindromic repeat) is one of the greatest advances in biology in the past decade, providing researchers with the tools to precisely and affordably edit genomes and physicians a new tool to cure disease. However, the ability to edit plant and animal genomes, including human genomes, comes with significant ethical considerations. This course will utilize a hybrid classroom-laboratory approach to provide students with both a comprehensive knowledge of the CRISPR system and a deeper understanding of how gene function is studied. At the end of the course, you will not only understand how CRISPR works, but also have a better understanding of the power of genetics to illuminate molecular mechanisms of protein function.

Prerequisites: AS.020.303 (Genetics) must be taken prior to or during enrollment in the Developmental Genetics Lab. Students must have completed Lab Safety training prior to registering for this class. To access the tutorial, login to myLearning and enter 458083 in the Search box to locate the appropriate module.

This is an applied course in ordinary differential equations, which is primarily for students in the biological, physical and social sciences, and engineering. Techniques for solving ordinary differential equations are studied. Topics covered include first order differential equations, second order linear differential equations, applications to electric circuits, oscillation of solutions, systems of linear differential equations, autonomous systems, Laplace transforms and linear differential equations, mathematical models (e.g., in the sciences or economics).

Prerequisite: AS.110.107 (Calculus II for Biological and Social Science) or AS.110.109 (Calculus II for Physical Sciences and Engineering) OR AS.110.113 (Honors Single Variable Calculus) or the equivalent of a single full year of single variable calculus.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

This course is an introduction to biology from an evolutionary, molecular, and cellular perspective. Specific topics and themes include evolutionary theory, the structure and function of biological molecules, mechanisms of harvesting energy, cell division, classical genetics, and gene expression.

Prerequisite: AP Biology.

This online course is primarily delivered asynchronously; however, your instructor may schedule live interactions as well. Please refer to your syllabus for these opportunities and for important course deadlines.

This course builds on the concepts presented and discussed in General Biology I. The primary foci of this course will be on the diversity of life and on the anatomy, physiology, and evolution of plants and animals. There will be a special emphasis on human biology.

Prerequisite: AP Biology or AS.020.151 (General Biology I).

This online course is primarily delivered asynchronously; however, your instructor may schedule live interactions as well. Please refer to your syllabus for these opportunities and for important course deadlines.

This course teaches intermediate to advanced programming, using C and C++. (Prior knowledge of these languages is not expected.) We will cover low-level programming techniques, as well as object-oriented class design, and the use of class libraries. Specific topics include pointers, dynamic memory allocation, polymorphism, overloading, inheritance, templates, collections, exceptions, and others as time permits. Students are expected to learn syntax and some language specific features independently. Course work involves significant programming projects in both languages.

Prerequisite: EN.500.132 (Bootcamp: Java) OR EN.500.133 (Bootcamp: Python) OR EN.500.134 (Bootcamp: MATLAB); OR C+ or better in EN.500.112 (Gateway Computing: Java) or EN.500.113 (Gateway Computing: Python) or EN.500.114 (Gateway Computing MATLAB); OR a score of 5 on the AP Computer Science A Exam.

A first introduction to abstract algebra through group theory, with an emphasis on concrete examples, and especially on geometric symmetry groups. The course will introduce basic notions (groups, subgroups, homomorphisms, quotients) and prove foundational results (Lagrange’s theorem, Cauchy’s theorem, orbit-counting techniques, the classification of finite abelian groups). Examples to be discussed include permutation groups, dihedral groups, matrix groups, and finite rotation groups, culminating in the classification of the wallpaper groups.

Prerequisite: AS.110.201 (Linear Algebra) or AS.110.212 (Honors Linear Algebra).

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

This online course introduces students to important concepts in data analytics across a wide range of case studies. Students will learn how to gather, analyze, and interpret data to drive strategic and operational success. They will explore how to clean and organize data for analysis, and how to perform calculations using Microsoft Excel. Topics include the data science lifecycle, probability, statistics, hypothesis testing, set theory, graphing, regression, and data ethics.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

This course will provide a practical introduction to mathematical proof, both as they have been done for centuries, and using a modern technological theorem prover. The course begins with the basic building blocks of mathematics: propositional logic, set theory, functions, and relations. These foundational tools lead to answers to questions that are surprisingly difficult, like “what are numbers?” Students will be exposed to mathematical notation and how to create it in digital documents, as well as an “artificially intelligent” proof assistant. The course will conclude with a consideration of the role of A.I. in pure mathematics, particularly as it applies to proofs.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

The basic concepts of point-set topology: topological spaces, connectedness, compactness, quotient spaces, metric spaces, function spaces. An introduction to algebraic topology: covering spaces, the fundamental group, and other topics as time permits.

Prerequisite: AS.110.202 (Calculus III: Calculus of Several Variables) or AS.110.211 (Honors Multivariable Calculus).

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

This is a course in the study of linear, or vector, spaces and the structure of linear mappings between such spaces. Topics in this course include vector spaces, matrices, and linear transformations, solutions of systems of linear equations, eigenvalues, eigenvectors, and the diagonalization of matrices, along with applications to differential equations.

Prerequisite: AS.110.107 (Calculus II for Biological and Social Science) or AS.110.109 (Calculus II for Physical Sciences and Engineering) or AS.110.113 (Honors Single Variable Calculus) or an Advanced Placement BC score of 5.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

This course is designed for students of all backgrounds to provide a solid foundation in the underlying mathematical, programming, and statistical theory of data analysis. In today's data driven world, data literacy is an increasingly important skill to master. To this end, the course will motivate the fundamental concepts used in this growing field. While discussing the general theory behind common methods of data science there will be numerous applications to real world data sets. In particular, the course will use Python libraries to create, import, and analyze data sets. 

Prerequisites: There are no mathematical prerequisites for this course although prior knowledge of calculus, statistics and/or programming can be helpful.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

This course is a precalculus course and provides students with the background necessary for a study of calculus. The course Includes a review of algebra, trigonometry, exponential and logarithmic functions, coordinates and graphs. Each of these tools is introduced in its cultural and historical context. The concept of the rate of change of a function will be introduced. Not open to students who have studied Calculus in high school.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

This course is designed to give a firm grounding in the basic tools of analysis. It is recommended as preparation (but may not be a prerequisite) for other advanced analysis courses and may be taken as an Introduction to Proofs (IP) course. Topics include the formal properties of real and complex number systems, topology of metric spaces, limits, continuity, infinite sequences and series, differentiation, Riemann-Stieltjes integration. 

Prerequisite: AS.110.201 (Linear Algebra) or AS.110.212 (Honors Linear Algebra) AND AS.110.202 (Calculus III: Calculus of Several Variables) or AS.110.211 (Honors Multivariable Calculus).

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

This course continues AS.110.405 (Real Analysis I) with an emphasis on the fundamental notions of modern analysis. Sequences and series of functions, Fourier series, equicontinuity and the Arzela-Ascoli theorem, the Stone-Weierstrass theorem, functions of several variables, the inverse and implicit function theorems, introduction to the Lebesgue integral.

Prerequisite: AS.110.405 (Real Anaylsis I) or AS.110.415 (Honors Analysis I).

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

This course introduces students from all disciplines to the principles and practices of calculus-based statistics as a tool for understanding civic life. The course integrates foundational concepts from probability theory with statistical inference, emphasizing how probabilistic models underpin the construction of confidence intervals and hypothesis tests. Students develop fluency in describing, interpreting, and critically evaluating quantitative information found in public discourse, including polls, media reports, policy analyses, and scientific studies. Through a combination of theoretical development and hands-on data analysis, students learn to compute and interpret confidence intervals, conduct hypothesis tests, and assess uncertainty using probabilistic reasoning. Real-world case studies are used to connect formal statistical methods to questions arising in democratic society. Students will use R and other relevant software (e.g., Python) to analyze datasets, simulate probabilistic models, and communicate evidence-based conclusions.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.

Mathematical Cryptography introduces students to the exciting practice of making and breaking secret codes as well as the mathematical theory behind them. Cryptography has applications to communication security, electronic funds transfer, and military and law enforcement. Students will study mathematical topics in both classical and modern cryptography, such as RSA, digital signatures, and elliptic curve cryptography through topics from probability, statistics, abstract algebra, computational complexity, and number theory.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded for viewing at any time. Students should expect to work a minimum of 5-10 hours per week.