On-Campus Pre-College Summer Programs

An understanding of physiology is an invaluable part of any budding physician’s or scientist’s repertoire. This course introduces classical physiology in the human body, and how it functions in both health and disease. This, the first of a two-part course (Anatomy, Physiology & Disease: Guts, Hormones and Reproduction is optional but should be a consideration), will cover core topics including the nervous, muscular, and cardiopulmonary systems, and physiology and disease. Additionally, students will be working outside the classroom to consolidate and reinforce their new understanding of the subject. Ultimately, knowledge of basic physiology should impact future research and serve as a foundation for all future scientific and biomedical endeavors.

Prerequisite: Background in Biology is strongly recommended.

Required Text: There is a required textbook. Details about the materials you need are available within your course syllabus and the Summer at Hopkins organization Canvas site.

An understanding of physiology is an invaluable part of any budding physician’s or scientist’s repertoire. This course introduces classical physiology in the human body, and how it functions in both health and disease. This, the first of a two-part course (Anatomy, Physiology & Disease: Guts, Hormones and Reproduction is optional but should be a consideration), will cover core topics including the nervous, muscular, and cardiopulmonary systems, and physiology and disease. Additionally, students will be working outside the classroom to consolidate and reinforce their new understanding of the subject. Ultimately, knowledge of basic physiology should impact future research and serve as a foundation for all future scientific and biomedical endeavors.

Prerequisite: Background in Biology is strongly recommended
.
Required Text: There is a required textbook. Details about the materials you need are available within your course syllabus and the Summer at Hopkins organization Canvas site.

An understanding of physiology is an invaluable part of any budding physician’s or scientist’s repertoire. In this, the second of a two-part course introducing classical physiology in the human body, and how it functions in both health and disease, we will cover guts (renal, digestive, and immune systems), as well as hormones (basic endocrinology) and sex/reproductive physiology. In addition to classroom study, students will be challenged to synthesize their newfound knowledge by taking part in immersive afternoon activities. While this represents a wholly separate course that may be taken independently, students should also consider taking the first part of this series (Anatomy, Physiology, & Disease: Core Systems) to bolster their understanding (offered in Summer Sessions 1 and 3). Ultimately, knowledge of basic physiological processes should impact the student's future research and serve as a foundation for all future scientific and biomedical endeavors.

Prerequisite: Background in Biology is strongly recommended.

Required Text: There is a required textbook. Details about the materials you need are available within your course syllabus and the Summer at Hopkins organization Canvas site.

Differential and integral calculus. Includes analytic geometry, functions, limits, integrals and derivatives, polar coordinates, parametric equations, Taylor's theorem and applications, infinite sequences and series. Some applications to the physical sciences and engineering will be discussed, and the courses are designed to meet the needs of students in these disciplines.

This course is scheduled to run Monday, Tuesday, Wednesday, and Thursday, between 9 a.m. and 11:30 a.m.

Calculus of Several Variables. Calculus of functions of more than one variable: partial derivatives, and applications; multiple integrals, line and surface integrals; Green's Theorem, Stokes' Theorem, and Gauss' Divergence Theorem.

This course is scheduled to run Monday, Tuesday, Wednesday, and Thursday, between 1 p.m. and 3:30 p.m.

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 AS.110.201 (Linear Algebra) or AS.110.212 (Honors Linear Algebra) or AS.110.302 (Differential Equations and Applications), or a 5 on the AP BC exam.

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.

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.

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 9 a.m. and 12 p.m.

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).

What does it mean to “design” an experiment? How do scientists go about planning experimental approaches that test specific hypotheses and provide informative results? These are the types of questions that lie at the heart of independent research. For example, scientists might ask: What analytical methods are best suited to answering a specific question? Which samples should be included in the analysis? What types of variables could influence the outcome of the experiments? This course will address such questions by having students design and carry out experiments to test specific hypotheses. Emphasis is placed on planning the experimental approaches and setting up experiments that include appropriate controls. The specific techniques used in the lab will vary but include standard techniques in molecular biology such as gel electrophoresis, PCR, and gene expression.

What does it mean to “design” an experiment? How do scientists go about planning experimental approaches that test specific hypotheses and provide informative results? These are the types of questions that lie at the heart of independent research. For example, scientists might ask: What analytical methods are best suited to answering a specific question? Which samples should be included in the analysis? What types of variables could influence the outcome of the experiments? This course will address such questions by having students design and carry out experiments to test specific hypotheses. Emphasis is placed on planning the experimental approaches and setting up experiments that include appropriate controls. The specific techniques used in the lab will vary but include standard techniques in molecular biology such as gel electrophoresis, PCR, and gene expression.

What does it mean to “design” an experiment? How do scientists go about planning experimental approaches that test specific hypotheses and provide informative results? These are the types of questions that lie at the heart of independent research. For example, scientists might ask: What analytical methods are best suited to answering a specific question? Which samples should be included in the analysis? What types of variables could influence the outcome of the experiments? This course will address such questions by having students design and carry out experiments to test specific hypotheses. Emphasis is placed on planning the experimental approaches and setting up experiments that include appropriate controls. The specific techniques used in the lab will vary but include standard techniques in molecular biology such as gel electrophoresis, PCR, and gene expression.

In this program you will be introduced to a variety of biochemical and molecular biological laboratory techniques. These will include DNA analysis by restriction enzyme mapping, amplification of DNA segments by PCR, and lipid analysis by chromatography. Additionally, you will visit a variety of biological laboratories to observe actual research projects.

Prerequisite: Background in Chemistry and Biology is strongly recommended.

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 program you will be introduced to a variety of biochemical and molecular biological laboratory techniques. These will include DNA analysis by restriction enzyme mapping, amplification of DNA segments by PCR, and lipid analysis by chromatography. Additionally, you will visit a variety of biological laboratories to observe actual research projects.

Prerequisite: Background in Chemistry and Biology is strongly recommended.

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 program you will be introduced to a variety of biochemical and molecular biological laboratory techniques. These will include DNA analysis by restriction enzyme mapping, amplification of DNA segments by PCR, and lipid analysis by chromatography. Additionally, you will visit a variety of biological laboratories to observe actual research projects.

Prerequisite: Background in Chemistry and Biology is strongly recommended.

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

Novel developments in the field of artificial intelligence have recently delivered staggering improvements nearly in any field imaginable. Machine learning models which detect and classify latent features of text, image and sound helped us read ancient scrolls we have not been able to read, improve cancer detection techniques and design better self-driving cars. Machine learning models also became better at producing new text, image and sound. ChatGPT is reaching level of competence which urges us to watermark its output and Dall-E is recreating any image to text in any style requested. The complexity of these models rivals and even surpasses their human counterparts at times. At other times, however, these models also behave shockingly incompetently. Self-driving cars struggle with unfamiliar situations, which give rise from absurd to dangerous situations. The detection models perform significantly worse on groups of individuals lying outside their training data. ChatGPT4 does not sound less confident when it makes up an answer than when it provides accurate information. These failures range from being merely amusing to threatening the very existence of humanity. With its promises of new heights and threats of new lows, machine-learning-based AI raises new and hard ethical issues. This course aims to introduce you both to the basic concepts in machine-learning-based AI as well as the hard ethical questions they raise from a philosophical perspective.

This course is scheduled to run Monday, Tuesday, Wednesday, and Thursday, between 12 p.m. and 2 p.m.

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.

Vector spaces, matrices, and linear transformations. Solutions of systems of linear equations. Eigenvalues, eigenvectors, and diagonalization of matrices. Applications to differential equations.

This course is scheduled to run Monday, Tuesday, Wednesday, and Thursday, between 9 a.m. and 11:30 a.m.

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 AS.110.202 (Calculus II) or AS.110.302 (Differential Equations and Applications), or a 5 on the AP BC exam.

Mathematics for Sustainability covers topics in measurement, probability, statistics, dynamics, and data analysis. In this course, students will analyze, visually represent, and interpret large, real data sets from a variety of government, corporate, and non-profit sources. Through local and global case studies, students will engage in the mathematics behind environmental sustainability issues and the debates centered on them. Topics include climate change, natural resource use, waste production, air and water pollution, water scarcity, and decreasing biodiversity. The software package R is used throughout the course.

This course is scheduled to run Monday, Tuesday, Wednesday, and Thursday, between 9 a.m. and 11:30 a.m.

Prerequisites: Comfort with algebraic expressions and functions. No prior experience in coding is required.

Is the mind identical to the brain? Is the mind (or brain) a computer? Could a computer reason, have emotions, or be morally responsible? This course examines such questions philosophically and historically. Topics include the history of AI research from 1940s to present; debates in cognitive science related to AI (computationalism, connectionism, and 4E cognition); and AI ethics.

This course is scheduled to run Tuesday and Thursday between 1 p.m. and 4:45 p.m.

This course provides students with the background necessary for the study of calculus. It begins with a review of the coordinate plane, linear equations, and inequalities, and moves purposefully into the study of functions. Students will explore the nature of graphs and deepen their understanding of polynomial, rational, trigonometric, exponential, and logarithmic functions, and will be introduced to complex numbers, parametric equations, and the difference quotient.

This course is scheduled to run Monday, Tuesday, Wednesday, and Thursday, between 1 p.m. and 3:30 p.m.

In epidemiology, public health scientists use quantitative and analytic tools examine to the distribution of disease across the population and to identify the various factors that shape these patterns. This course will explore how epidemiologic tools can be used to interrogate the social and structural factors that create health disparities in society. Students will learn about key social determinants of health (including class, race, and gender), the various pathways by which social experiences “get under the skin” to impact physiologic disease states, and how epidemiologists investigate these processes through population-based research. Students will leave the course with an understanding of the ways public health professionals and community members alike can use this public health research to develop policies and programs that protect the health of vulnerable groups and reduce inequality.

In epidemiology, public health scientists use quantitative and analytic tools examine to the distribution of disease across the population and to identify the various factors that shape these patterns. This course will explore how epidemiologic tools can be used to interrogate the social and structural factors that create health disparities in society. Students will learn about key social determinants of health (including class, race, and gender), the various pathways by which social experiences “get under the skin” to impact physiologic disease states, and how epidemiologists investigate these processes through population-based research. Students will leave the course with an understanding of the ways public health professionals and community members alike can use this public health research to develop policies and programs that protect the health of vulnerable groups and reduce inequality.