Summer Catalog

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).

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.

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.

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 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.

How do big data and social media shape our ideas about ourselves and our participation in governance? This interdisciplinary course examines the influence of algorithms and large-scale data systems in our lives and society at large. Students explore how data-driven technologies affect brain function, human behavior, and public discourse as they engage with the work of Dr. Lilliana Mason and other JHU faculty experts. Students investigate pressing ethical issues related to privacy, misinformation, data security, and digital manipulation. Through hands-on programming in Python, students will work with real-world datasets to analyze trends and patterns, culminating in a final project that explores data’s impact on social behavior and participatory governance. This course is ideal for students interested in computer science, data science, neuroscience, psychology, cybersecurity, and/or governance. No prior programming experience is required.

Students in this course are required to complete 3 hours of prework prior to the first day of class.

Students in this course must bring a laptop capable of running Python (with Anaconda installed), opening spreadsheets, browsing the internet, and using programs such as Microsoft Word, PowerPoint, and Canva for project and group work. Students will be required to download datasets from online sources, so their laptops should have appropriate privacy and security protections, such as antivirus software. Students must engage in secure browsing practices.

This course is an introduction to the economic system and economic analysis with emphasis on total national income and output, employment, the price level and inflation, money, the government budget, the national debt, and interest rates. The role of public policy and applications of economic analysis to government and personal decisions are also covered.

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.

Prerequisite: Basic facility with graphs and algebra.

This course is an introduction to the economic system and economic analysis, with an emphasis on demand and supply, relative prices, the allocation of resources, and the distribution of goods and services. It covers the theory of consumer behavior, the 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 and Claude become increasingly sophisticated, understanding how they work is more important than ever. This course introduces students to the mathematical and statistical principles behind machine learning and AI technologies. Students will learn the mathematical concepts behind classification and prediction models and implement these models in Python. Working with real-world data, students will design machine learning applications that power modern AI systems. Models studied include linear regression, classification trees, neural networks, and K-nearest neighbors (KNN). By testing and improving their models, students will gain insight into both the possibilities and limitations of AI.

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

Prerequsite: Algebra I.

As artificial intelligence models like ChatGPT and Claude become increasingly sophisticated, understanding how they work is more important than ever. This course introduces students to the mathematical and statistical principles behind machine learning and AI technologies. Students will learn the mathematical concepts behind classification and prediction models and implement these models in Python. Working with real-world data, students will design machine learning applications that power modern AI systems. Models studied include linear regression, classification trees, neural networks, and K-nearest neighbors (KNN). By testing and improving their models, students will gain insight into both the possibilities and limitations of AI.

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

Prerequsite: Algebra I.

As artificial intelligence models like ChatGPT and Claude become increasingly sophisticated, understanding how they work is more important than ever. This course introduces students to the mathematical and statistical principles behind machine learning and AI technologies. Students will learn the mathematical concepts behind classification and prediction models and implement these models in Python. Working with real-world data, students will design machine learning applications that power modern AI systems. Models studied include linear regression, classification trees, neural networks, and K-nearest neighbors (KNN). By testing and improving their models, students will gain insight into both the possibilities and limitations of AI.

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

Prerequsite: Algebra I.

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.500.112 (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 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.