Accelerate your entry into college life in a fast-paced environment while earning academic credit from a top university.

Filter your search by area of study, location, and date range. Qualified pre-college students may also consider the undergraduate courses listed below.

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Creative Writing - AS.220.138

Pre-College students July 20 - July 31 Online
1 Credit Status: Open Save this Course View Saved Courses

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.

Duration
2 weeks
Area of Study
Humanities
Department
Writing Seminars
Class Schedule
Monday
Self-paced
Tuesday
Self-paced
Wednesday
Self-paced
Thursday
Self-paced
Friday
Self-paced

Data Analytics Workshop - AS.110.100

Pre-College students June 22 - July 3 Online
1 Credit Status: Open Save this Course View Saved Courses

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.



Duration
2 weeks
Area of Study
STEM
Department
Mathematics
Class Schedule
Monday
Self-paced
Tuesday
Self-paced
Wednesday
Self-paced
Thursday
Self-paced
Friday
Self-paced

Data Analytics Workshop - AS.110.100

Pre-College students July 6 - July 17 Online
1 Credit Status: Open Save this Course View Saved Courses

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.



Duration
2 weeks
Area of Study
STEM
Department
Mathematics
Class Schedule
Monday
Self-paced
Tuesday
Self-paced
Wednesday
Self-paced
Thursday
Self-paced
Friday
Self-paced

Data Analytics Workshop - AS.110.100

Pre-College students July 20 - July 31 Online
1 Credit Status: Open Save this Course View Saved Courses

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.



Duration
2 weeks
Area of Study
STEM
Department
Mathematics
Class Schedule
Monday
Self-paced
Tuesday
Self-paced
Wednesday
Self-paced
Thursday
Self-paced
Friday
Self-paced

Data Structures - EN.601.226

Pre-College students & Undergraduate students June 1 - July 24 Online
4 Credits Status: Open Save this Course View Saved Courses

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.

Duration
8 weeks
Area of Study
STEM
Department
EN Computer Science
Instructor
Madooei, Ali
Class Schedule
Monday
9:30 AM-11:45 AM
Wednesday
9:30 AM-11:45 AM
Friday
9:30 AM-11:45 AM

Differential Equations with Applications - AS.110.302

Pre-College students & Undergraduate students June 1 - July 24 Online
4 Credits Status: Open Save this Course View Saved Courses

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.

Duration
8 weeks
Area of Study
STEM
Department
Mathematics
Instructor
Marshburn, Nicholas

Digital Society: Big Data, Social Media, and Ethical Engagement - AS.196.110

Pre-College students June 22 - July 1 Homewood Campus
1 Credit Status: Open Save this Course View Saved Courses

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.

Duration
2 weeks
Areas of Study
STEM, Social Sciences, Humanities
Department
Agora Institute
Class Schedule
Monday
9:30 AM-4:00 PM
Tuesday
9:30 AM-4:00 PM
Wednesday
9:30 AM-4:00 PM
Thursday
9:30 AM-4:00 PM
Friday
9:30 AM-4:00 PM

Elements of Macroeconomics - AS.180.101

Pre-College students & Undergraduate students May 26 - June 26 Online
3 Credits Status: Open Save this Course View Saved Courses

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.

Duration
5 weeks
Area of Study
Social Sciences
Department
Economics
Instructor
Seshie-Nasser, Hellen

Elements of Microeconomics - AS.180.102

Pre-College students & Undergraduate students May 18 - June 26 Online
3 Credits Status: Open Save this Course View Saved Courses

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.

Duration
6 weeks
Area of Study
Social Sciences
Department
Economics
Instructor
Husain, Muhammed

Epidemics, Pandemics, and Outbreaks - AS.360.146

Pre-College students July 6 - July 17 Online
1 Credit Status: Open Save this Course View Saved Courses

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.

Duration
2 weeks
Area of Study
Foundations of Medicine and Health
Department
Interdepartmental
Class Schedule
Monday
Self-paced
Tuesday
Self-paced
Wednesday
Self-paced
Thursday
Self-paced
Friday
Self-paced

Exploring the Universe with Space Telescopes - AS.171.135

Pre-College students June 22 - July 1 Homewood Campus
1 Credit Status: Open Save this Course View Saved Courses

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.

Duration
2 weeks
Area of Study
STEM
Department
Physics & Astronomy
Class Schedule
Monday
9:30 AM-4:00 PM
Tuesday
9:30 AM-4:00 PM
Wednesday
9:30 AM-4:00 PM
Thursday
9:30 AM-4:00 PM
Friday
9:30 AM-4:00 PM

Exploring the Universe with Space Telescopes - AS.171.135

Pre-College students July 6 - July 16 Homewood Campus
1 Credit Status: Open Save this Course View Saved Courses

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.

Duration
2 weeks
Area of Study
STEM
Department
Physics & Astronomy
Class Schedule
Monday
9:30 AM-4:00 PM
Tuesday
9:30 AM-4:00 PM
Wednesday
9:30 AM-4:00 PM
Thursday
9:30 AM-4:00 PM
Friday
9:30 AM-4:00 PM

Exploring the Universe with Space Telescopes - AS.171.135

Pre-College students July 20 - July 30 Homewood Campus
1 Credit Status: Open Save this Course View Saved Courses

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.

Duration
2 weeks
Area of Study
STEM
Department
Physics & Astronomy
Class Schedule
Monday
9:30 AM-4:00 PM
Tuesday
9:30 AM-4:00 PM
Wednesday
9:30 AM-4:00 PM
Thursday
9:30 AM-4:00 PM
Friday
9:30 AM-4:00 PM

Foundational Mathematics of Artificial Intelligence - AS.110.110

Pre-College students June 22 - July 1 Homewood Campus
1 Credit Status: Open Save this Course View Saved Courses

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.

Duration
2 weeks
Area of Study
STEM
Department
Mathematics
Class Schedule
Monday
9:30 AM-4:00 PM
Tuesday
9:30 AM-4:00 PM
Wednesday
9:30 AM-4:00 PM
Thursday
9:30 AM-4:00 PM
Friday
9:30 AM-4:00 PM

Foundational Mathematics of Artificial Intelligence - AS.110.110

Pre-College students July 6 - July 16 Homewood Campus
1 Credit Status: Open Save this Course View Saved Courses

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.

Duration
2 weeks
Area of Study
STEM
Department
Mathematics
Class Schedule
Monday
9:30 AM-4:00 PM
Tuesday
9:30 AM-4:00 PM
Wednesday
9:30 AM-4:00 PM
Thursday
9:30 AM-4:00 PM
Friday
9:30 AM-4:00 PM

Foundational Mathematics of Artificial Intelligence - AS.110.110

Pre-College students July 20 - July 30 Homewood Campus
1 Credit Status: Open Save this Course View Saved Courses

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.

Duration
2 weeks
Area of Study
STEM
Department
Mathematics
Class Schedule
Monday
9:30 AM-4:00 PM
Tuesday
9:30 AM-4:00 PM
Wednesday
9:30 AM-4:00 PM
Thursday
9:30 AM-4:00 PM
Friday
9:30 AM-4:00 PM

Gateway Computing: Python - EN.500.113

Pre-College students & Undergraduate students June 29 - July 31 Homewood Campus
3 Credits Status: Open Save this Course View Saved Courses

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).

Duration
5 weeks
Area of Study
STEM
Department
EN General Engineering
Instructor
Presler-Marshall, Kai
Class Schedule
Monday
12:00 PM-3:00 PM
Wednesday
12:00 PM-3:00 PM
Friday
12:00 PM-3:00 PM

General Biology I - AS.020.151

Pre-College students & Undergraduate students May 26 - June 26 Online
3 Credits Status: Open Save this Course View Saved Courses

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.

Duration
5 weeks
Area of Study
STEM
Department
Biology
Instructor
Shingles, Richard

General Biology II - AS.020.152

Pre-College students & Undergraduate students June 29 - July 31 Online
3 Credits Status: Open Save this Course View Saved Courses

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.

Duration
5 weeks
Area of Study
STEM
Department
Biology
Instructor
Shingles, Richard

Global Leadership for a Sustainable Future - AS.360.115

Pre-College students June 22 - July 3 Online
1 Credit Status: Open Save this Course View Saved Courses

Lead change for a sustainable future. Students sharpen their leadership skills by exploring global challenges through an intercultural lens. Through engaging lectures, interactive projects, and two optional live sessions with peers worldwide, participants learn to design actionable solutions, evaluate their environmental impact, and communicate ideas that inspire change. Throughout the course, students engage in guided, project-based learning and reflect on their growth as ethical, inclusive leaders. By the end, students will have built cross-cultural communication and leadership skills that prepare them to lead thoughtfully and effectively in an interconnected world, and to approach their academic and professional journeys with purpose and confidence.

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.

Duration
2 weeks
Areas of Study
Social Sciences, Humanities
Department
Interdepartmental
Class Schedule
Monday
Self-paced
Tuesday
Self-paced
Wednesday
Self-paced
Thursday
Self-paced
Friday
Self-paced

Global Leadership for a Sustainable Future - AS.360.115

Pre-College students July 6 - July 17 Online
1 Credit Status: Open Save this Course View Saved Courses

Lead change for a sustainable future. Students sharpen their leadership skills by exploring global challenges through an intercultural lens. Through engaging lectures, interactive projects, and two optional live sessions with peers worldwide, participants learn to design actionable solutions, evaluate their environmental impact, and communicate ideas that inspire change. Throughout the course, students engage in guided, project-based learning and reflect on their growth as ethical, inclusive leaders. By the end, students will have built cross-cultural communication and leadership skills that prepare them to lead thoughtfully and effectively in an interconnected world, and to approach their academic and professional journeys with purpose and confidence.

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.

Duration
2 weeks
Areas of Study
Social Sciences, Humanities
Department
Interdepartmental
Class Schedule
Monday
Self-paced
Tuesday
Self-paced
Wednesday
Self-paced
Thursday
Self-paced
Friday
Self-paced

Global Leadership for a Sustainable Future - AS.360.115

Pre-College students July 20 - July 31 Online
1 Credit Status: Open Save this Course View Saved Courses

Lead change for a sustainable future. Students sharpen their leadership skills by exploring global challenges through an intercultural lens. Through engaging lectures, interactive projects, and two optional live sessions with peers worldwide, participants learn to design actionable solutions, evaluate their environmental impact, and communicate ideas that inspire change. Throughout the course, students engage in guided, project-based learning and reflect on their growth as ethical, inclusive leaders. By the end, students will have built cross-cultural communication and leadership skills that prepare them to lead thoughtfully and effectively in an interconnected world, and to approach their academic and professional journeys with purpose and confidence.

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.

Duration
2 weeks
Areas of Study
Social Sciences, Humanities
Department
Interdepartmental
Class Schedule
Monday
Self-paced
Tuesday
Self-paced
Wednesday
Self-paced
Thursday
Self-paced
Friday
Self-paced

Green Chemistry: The Science of Sustainability - AS.030.110

Pre-College students June 22 - July 3 Online
1 Credit Status: Open Save this Course View Saved Courses

From packaging to electronics, petrochemicals underpin a vast array of everyday goods, from packaging to electronics. Guided by the 12 Principles of Green Chemistry, this course takes a sustainability-focused look at modern synthetic chemistry. Students will evaluate risks and long-term impacts, compare synthetic routes using atom economy and green metrics, consider safer solvent options, and gain a grounding in chemical toxicology. The goal is to cultivate critical, reflective practitioners who design safer, more sustainable syntheses.

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.

Duration
2 weeks
Area of Study
STEM
Department
Chemistry
Class Schedule
Monday
Self-paced
Tuesday
Self-paced
Wednesday
Self-paced
Thursday
Self-paced
Friday
Self-paced

Green Chemistry: The Science of Sustainability - AS.030.110

Pre-College students July 20 - July 31 Online
1 Credit Status: Open Save this Course View Saved Courses

From packaging to electronics, petrochemicals underpin a vast array of everyday goods, from packaging to electronics. Guided by the 12 Principles of Green Chemistry, this course takes a sustainability-focused look at modern synthetic chemistry. Students will evaluate risks and long-term impacts, compare synthetic routes using atom economy and green metrics, consider safer solvent options, and gain a grounding in chemical toxicology. The goal is to cultivate critical, reflective practitioners who design safer, more sustainable syntheses.

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.

Duration
2 weeks
Area of Study
STEM
Department
Chemistry
Class Schedule
Monday
Self-paced
Tuesday
Self-paced
Wednesday
Self-paced
Thursday
Self-paced
Friday
Self-paced

Intermediate Programming - EN.601.220

Pre-College students & Undergraduate students June 1 - July 24 Online
4 Credits Status: Open Save this Course View Saved Courses

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.

Duration
8 weeks
Area of Study
STEM
Department
EN Computer Science
Instructor
Darvish, Ali
Class Schedule
Monday
1:00 PM-3:15 PM
Wednesday
1:00 PM-3:15 PM
Friday
1:00 PM-3:15 PM

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