Summer Catalog

This is an online course. The class will meet for ten weeks and will follow the deadlines for that term for add/drop/withdraw and grade changes.This course examines the psychological disorders that are usually first diagnosed prior to adulthood. Some of the specific disorders that will be discussed are Attention-Deficit and Disruptive Behavior Disorders, Neurodevelopmental Disorders, Learning Disorders, and Intellectual Disability.Students will become familiar with various diagnoses, etiologies, and methods of treatment. Note: This course does not count towards the Psychology major.

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 introductory course will create a foundational understanding of topics in Algebra. An emphasis will be on applications to prepare students for future courses like Precalculus or Statistics. After a review of elementary algebra concepts, topics covered include equations and inequalities, linear equations, exponents and polynomials, factoring, rational expressions and equations, relations and functions, radicals, linear and quadratic equations, higher-degree polynomials, exponential, logarithmic, and rational functions.

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.

Enjoy the opportunity to develop your creative writing skills. You will work in both fiction and poetry. Through a combination of robust discussion, writing exercises, and substantial feedback, you will learn about imagery, voice, narrative structure, and other aspects of the writer’s craft. The reading list will include a diverse range of contemporary authors. There will be a strong emphasis on collaborative workshopping, during which you will discuss one another’s works in progress.

This online program is primarily delivered asynchronously, but students are expected to meet both daily and weekly deadlines for class assignments. Your instructor will also provide optional opportunities for synchronous sessions, such as office hours, group discussions, and supplemental lectures. Attendance for synchronous sessions is voluntary and based on students’ availability.

Prerequisite: There are no prerequisites for this program.

Required Text: All required readings are available for free on JHU eReserves. Additional readings and video resources will be made available to you throughout the program.

Enjoy the opportunity to develop your creative writing skills. You will work in both fiction and poetry. Through a combination of robust discussion, writing exercises, and substantial feedback, you will learn about imagery, voice, narrative structure, and other aspects of the writer’s craft. The reading list will include a diverse range of contemporary authors. There will be a strong emphasis on collaborative workshopping, during which you will discuss one another’s works in progress.

This online program is primarily delivered asynchronously, but students are expected to meet both daily and weekly deadlines for class assignments. Your instructor will also provide optional opportunities for synchronous sessions, such as office hours, group discussions, and supplemental lectures. Attendance for synchronous sessions is voluntary and based on students’ availability.

Prerequisite: There are no prerequisites for this program.

Required Text: All required readings are available for free on JHU eReserves. Additional readings and video resources will be made available to you throughout the program.

Enjoy the opportunity to develop your creative writing skills. You will work in both fiction and poetry. Through a combination of robust discussion, writing exercises, and substantial feedback, you will learn about imagery, voice, narrative structure, and other aspects of the writer’s craft. The reading list will include a diverse range of contemporary authors. There will be a strong emphasis on collaborative workshopping, during which you will discuss one another’s works in progress.

This online program is primarily delivered asynchronously, but students are expected to meet both daily and weekly deadlines for class assignments. Your instructor will also provide optional opportunities for synchronous sessions, such as office hours, group discussions, and supplemental lectures. Attendance for synchronous sessions is voluntary and based on students’ availability.

Prerequisite: There are no prerequisites for this program.

Required Text: All required readings are available for free on JHU eReserves. Additional readings and video resources will be made available to you throughout the program.

This course focuses on building understanding of the culture of engineering while preparing students to communicate effectively with the various audiences with whom engineers interact. Working from a base of contemporary science writing (monographs, non-fiction, popular literature and fiction), students will engage in discussion, argument, case study and project work to investigate: the engineering culture and challenges to that culture, the impacts of engineering solutions on society, the ethical guidelines for the profession, and the ways engineering information is conveyed to the range of audiences for whom the information is critical. Additionally, students will master many of the techniques critical to successful communication within the engineering culture through a series of short papers and presentations associated with analysis of the writings and cases. No audits. WSE juniors and seniors or by instructor approval.

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.

In this two-week pre-college program, students work in groups to construct and present a data analysis project which collects, organizes, cleanses, and visualizes a dataset of their choosing. Topics include exploratory data analysis, data visualization, probability distributions, data scraping and cleansing, the basics of hypothesis testing, and regression modeling. Students will primarily use Microsoft Excel. Programs like Octave (Matlab), and Octoparse, will also be introduced to help students learn the basics of data analytics. 

This online program is primarily delivered asynchronously, but students are expected to meet both daily and weekly deadlines for class assignments. Your instructor will also provide optional opportunities for synchronous sessions, such as office hours, group discussions, and supplemental lectures. Attendance for synchronous sessions is voluntary and based on students’ availability.

Prerequisite: Precalculus. (There is no programming requisite required for this course.)

Required Text: There are no required textbooks for this program; all readings and resources will be made available to you throughout the program.

In this two-week pre-college program, students work in groups to construct and present a data analysis project which collects, organizes, cleanses, and visualizes a dataset of their choosing. Topics include exploratory data analysis, data visualization, probability distributions, data scraping and cleansing, the basics of hypothesis testing, and regression modeling. Students will primarily use Microsoft Excel. Programs like Octave (Matlab), and Octoparse, will also be introduced to help students learn the basics of data analytics. 

This online program is primarily delivered asynchronously, but students are expected to meet both daily and weekly deadlines for class assignments. Your instructor will also provide optional opportunities for synchronous sessions, such as office hours, group discussions, and supplemental lectures. Attendance for synchronous sessions is voluntary and based on students’ availability.

Prerequisite: Precalculus. (There is no programming requisite required for this course.)

Required Text: There are no required textbooks for this program; all readings and resources will be made available to you throughout the program.

In this two-week pre-college program, students work in groups to construct and present a data analysis project which collects, organizes, cleanses, and visualizes a dataset of their choosing. Topics include exploratory data analysis, data visualization, probability distributions, data scraping and cleansing, the basics of hypothesis testing, and regression modeling. Students will primarily use Microsoft Excel. Programs like Octave (Matlab), and Octoparse, will also be introduced to help students learn the basics of data analytics. 

This online program is primarily delivered asynchronously, but students are expected to meet both daily and weekly deadlines for class assignments. Your instructor will also provide optional opportunities for synchronous sessions, such as office hours, group discussions, and supplemental lectures. Attendance for synchronous sessions is voluntary and based on students’ availability.

Prerequisite: Precalculus. (There is no programming requisite required for this course.)

Required Text: There are no required textbooks for this program; all readings and resources will be made available to you throughout the program.

This is a course in ordinary differential equations (ODEs), equations involving an unknown function of one independent variable and some of its derivatives, and is primarily a course in the study of the structure of and techniques for solving ODEs as mathematical models. Specific topics include first and second ODEs of various types, systems of linear differential equations, autonomous systems, and the qualitative and quantitative analysis of nonlinear systems of first-order ODEs. Laplace transforms, series solutions and the basics of numerical solutions are included as extra topics.

Prerequisite: Grade of C- or better in 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 a 5 on the AP BC exam.

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 student is provided with many historical examples of topics, each of which serves as an illustration of and provides a background for many years of current research in number theory. Primes and prime factorization, congruences, Euler's function, quadratic reciprocity, primitive roots, solutions to polynomial congruences (Chevalley's theorem), Diophantine equations including the Pythagorean and Pell equations, Gaussian integers, Dirichlet's theorem on primes.

Prerequisite: Grade of C- or better in 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 course introduces the basic tools of macroeconomics and teaches how they are applied to real world economic policy. Throughout the course, the main goals will be to a) study economic aggregates such as the overall price level, the unemployment rate, and the GDP, and b) understand how they relate to each other. Attention will be given to fiscal and monetary policies. We will also analyze the recent COVID crisis and its impact on the economic activity.

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.

An introduction to the economic system and economic analysis with emphasis on demand and supply, relative prices, the allocation of resources, and the distribution of goods and services, theory of consumer behavior, theory of the firm, and competition and monopoly, including the application of microeconomic analysis to contemporary problems.

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.

In the midst of a global pandemic that has shifted the ways in which we move, work, and interact with others around the world, it is more important than ever to have a deeper understanding of how outbreaks, epidemics, and pandemics have evolved. You will review select communicable (COVID-19, Ebola, Zika, and HIV) and non-communicable (diabetes, cancer, cardiovascular disease, injury, and mental health) diseases in public health around the world. Examine the global burden of these diseases and the various forms of prevention efforts undertaken by global and national organizations. This program will use a combination of lecture, discussion, and student presentation format to encourage broad participation.

This online program is primarily delivered asynchronously, but students are expected to meet both daily and weekly deadlines for class assignments. Your instructor will also provide optional opportunities for synchronous sessions, such as office hours, group discussions, and supplemental lectures. Attendance for synchronous sessions is voluntary and based on students’ availability.

Prerequisite: There are no prerequisites for this program.

Required Text: There are no required textbooks for this program; all readings and video resources will be made available to you throughout the program.

Through a mix of lectures and hands-on activities, you will learn how astronomers study objects in space using different types of light, observatories, and instrumental techniques. You will also hear from active researchers about the big, open questions in astronomy and how we use space telescopes such as Hubble and Webb to answer those questions. Building on this knowledge, you will work with a small group to design your own space telescope and present that design to your peers. No prior knowledge of astronomy, physics, or mathematics is assumed.

Students in this course must bring a laptop or device capable of opening PDFs and running Google docs for project and group work.

Through a mix of lectures and hands-on activities, you will learn how astronomers study objects in space using different types of light, observatories, and instrumental techniques. You will also hear from active researchers about the big, open questions in astronomy and how we use space telescopes such as Hubble and Webb to answer those questions. Building on this knowledge, you will work with a small group to design your own space telescope and present that design to your peers. No prior knowledge of astronomy, physics, or mathematics is assumed.

Students in this course must bring a laptop or device capable of opening PDFs and running Google docs for project and group work.

Through a mix of lectures and hands-on activities, you will learn how astronomers study objects in space using different types of light, observatories, and instrumental techniques. You will also hear from active researchers about the big, open questions in astronomy and how we use space telescopes such as Hubble and Webb to answer those questions. Building on this knowledge, you will work with a small group to design your own space telescope and present that design to your peers. No prior knowledge of astronomy, physics, or mathematics is assumed.

Students in this course must bring a laptop or device capable of opening PDFs and running Google docs for project and group work.

As artificial intelligence models like ChatGPT become increasingly capable and part of our everyday life, the need to understand their inner workings intensifies. This course introduces the mathematical and statistical principles behind machine learning and AI technologies. Students will assimilate basic concepts including math models and performance measurement. They will apply software to build machine learning applications that serve as AI building blocks including linear regression, classification trees, neural networks, and reinforcement learning. Participants will be challenged to assess the quality of their analyses to better understand the opportunities for, and the limitations of AI.

Students in this course must bring a laptop or device capable of opening a spreadsheet, running cloud-based code, and running cloud-based programs like Microsoft Word and PPT.

As artificial intelligence models like ChatGPT become increasingly capable and part of our everyday life, the need to understand their inner workings intensifies. This course introduces the mathematical and statistical principles behind machine learning and AI technologies. Students will assimilate basic concepts including math models and performance measurement. They will apply software to build machine learning applications that serve as AI building blocks including linear regression, classification trees, neural networks, and reinforcement learning. Participants will be challenged to assess the quality of their analyses to better understand the opportunities for, and the limitations of AI.

Students in this course must bring a laptop or device capable of opening a spreadsheet, running cloud-based code, and running cloud-based programs like Microsoft Word and PPT.

As artificial intelligence models like ChatGPT become increasingly capable and part of our everyday life, the need to understand their inner workings intensifies. This course introduces the mathematical and statistical principles behind machine learning and AI technologies. Students will assimilate basic concepts including math models and performance measurement. They will apply software to build machine learning applications that serve as AI building blocks including linear regression, classification trees, neural networks, and reinforcement learning. Participants will be challenged to assess the quality of their analyses to better understand the opportunities for, and the limitations of AI.

Students in this course must bring a laptop or device capable of opening a spreadsheet, running cloud-based code, and running cloud-based programs like Microsoft Word and PPT.

A full-stack JavaScript developer is a person who can build modern software applications using primarily the JavaScript programming language. Creating a modern software application involves integrating many technologies - from creating the user interface to saving information in a database and everything else in between and beyond. A full-stack developer is not an expert in everything. Rather, they are someone who is familiar with various (software application) frameworks and the ability to take a concept and turn it into a finished product. This course will teach you programming in JavaScript and introduce you to several JavaScript frameworks that would enable you to build modern web, cross-platform desktop, and native/hybrid mobile applications. A student who successfully completes this course will be on the expedited path to becoming a full-stack JavaScript developer.

Students may not have taken or be concurrently enrolled in EN.601.421 (Object Oriented Software Engineering) or EN.601.621 (Ojbect Oriented Software Engineering--graduate degree version).

Prerequisites: EN.601.220 (Intermediate Programming) OR EN.601.226 (Data Structures).

This course introduces fundamental programming concepts and techniques, and is intended for all who plan to develop computational artifacts or intelligently deploy computational tools in their studies and careers. Topics covered include the design and implementation of algorithms using variables, control structures, arrays, functions, files, testing, debugging, and structured program design. Elements of object-oriented programming. algorithmic efficiency and data visualization are also introduced. Students deploy programming to develop working solutions that address problems in engineering, science and other areas of contemporary interest that vary from section to section. Course homework involves significant programming. Attendance and participation in class sessions are expected.

Prerequisite: Students may not have earned credit in the following courses: EN.500.113 (Gateway Computing: Python), EN.500.114 (Gateway Computing: Matlab), EN.500.202 (Computation and Programming for Materials Scientists and Engineers), EN.500.132 (Bootcamp: JAVA), EN.500.133 (Bootcamp: Python), or EN.500.134 (Bootcamp: Matlab).

This course introduces fundamental programming concepts and techniques, and is intended for all who plan to develop computational artifacts or intelligently deploy computational tools in their studies and careers. Topics covered include the design and implementation of algorithms using variables, control structures, arrays, functions, files, testing, debugging, and structured program design. Elements of object-oriented programming. algorithmic efficiency and data visualization are also introduced. Students deploy programming to develop working solutions that address problems in engineering, science and other areas of contemporary interest that vary from section to section. Course homework involves significant programming. Attendance and participation in class sessions are expected.

This course is scheduled to run Monday, Wednesday, and Friday between 12 p.m. and 3 p.m.

Prerequisite: Students may not have earned credit in the following courses: EN.500.112 (Gateway Computing: JAVA), EN.500.114 (Gateway Computing: Matlab), EN.500.202 (Computation and Programming for Materials Scientists and Engineers), EN.500.132 (Bootcamp: JAVA), EN.500.132 (Bootcamp: JAVA), or EN.500.134 (Bootcamp: Matlab).

This two-semester sequence in general physics is identical in subject matter to AS.171.101-AS.171.102, covering mechanics, heat, sound, electricity and magnetism, optics, and modern physics, but differs in instructional format. Rather than being presented via lectures and discussion sections, it is instead taught in an "active learning" style with most class time given to small group problem-solving guided by instructors.

Recommended Corequisites: AS.173.111 (General Physics Laboratory I) AND either AS.110.106 (Calculus I For Biology and Social Sciences) or AS.110.108 (Calculus I For Physical Sciences and Engineering) or AS.110.113 (Honors Single Variable Calculus).