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.

Students in this course must bring a laptop or tablet, such as a Chromebook.

Prerequisite: Background in Biology is strongly recommended.

Required Text: The textbook for this course is Lauralee Sherwood’s HUMAN PHYSIOLOGY: FROM CELLS TO SYSTEMS 9th Edition (Cengage Learning, ISBN 978-1285866932). Students may purchase either a hard copy or eTextbook.

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.

Students in this course must bring a laptop or tablet, such as a Chromebook.

Prerequisite: Background in Biology is strongly recommended
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Required Text: The textbook for this course is Lauralee Sherwood’s HUMAN PHYSIOLOGY: FROM CELLS TO SYSTEMS 9th Edition (Cengage Learning, ISBN 978-1285866932). Students may purchase either a hard copy or eTextbook.

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.

Students in this course must bring a laptop or tablet, such as a Chromebook.

Prerequisite: Background in Biology is strongly recommended.

Required Text: The textbook for this course is Lauralee Sherwood’s HUMAN PHYSIOLOGY: FROM CELLS TO SYSTEMS 9th Edition (Cengage Learning, ISBN 978-1285866932). Students may purchase either a hard copy or eTextbook.

Ever wondered how the ads you see seem to know exactly what you want even before you do? Dive into the world of Big Data and Advertising where technology meets creativity to shape consumer behavior and business strategy. This course offers a deep exploration of how big data is revolutionizing advertising, from personalized ads to predictive analytics. By integrating perspectives from psychology, economics, computer science, and marketing, you’ll gain insights into how data drives decisions in the advertising world. Explore the psychological principles behind consumer behavior, learn how data is collected, and understand the ethical implications of using personal information in advertising. Through hands-on programming in Python, you’ll manipulate large datasets to discover patterns that drive ad campaigns. This interdisciplinary course challenges you to think critically about the intersection of technology, ethics, and business, preparing you to navigate the complexities of data-driven advertising. No prior coding experience is required, making this course accessible to all students interested in the powerful combination of big data and advertising.

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 and PowerPoint 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.

Curious about how big data and social media shape democracy and everyday life? This course offers an interdisciplinary exploration of big data, focusing on its applications and ethical concerns at the intersection of neuroscience, psychology, civic engagement, and data security. You'll examine how algorithms and big data influence brain function, behavior, and political polarization. The course addresses ethical implications such as privacy, misinformation, and security, alongside the role of social media in shaping democratic processes. Through hands-on programming in Python, you'll manipulate large datasets, with a final project exploring data's role in democracy, entertainment, safety, or social media. Discussions and quizzes will cover broader societal and ethical impacts, providing a well-rounded understanding of data origins, analysis, and use in civic life. This course is ideal for students interested in careers in computer science, data science, neuroscience, psychology, cybersecurity and civic engagement. No prior coding experience is required.

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 and PowerPoint 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.

Curious about how big data and social media shape democracy and everyday life? This course offers an interdisciplinary exploration of big data, focusing on its applications and ethical concerns at the intersection of neuroscience, psychology, civic engagement, and data security. You'll examine how algorithms and big data influence brain function, behavior, and political polarization. The course addresses ethical implications such as privacy, misinformation, and security, alongside the role of social media in shaping democratic processes. Through hands-on programming in Python, you'll manipulate large datasets, with a final project exploring data's role in democracy, entertainment, safety, or social media. Discussions and quizzes will cover broader societal and ethical impacts, providing a well-rounded understanding of data origins, analysis, and use in civic life. This course is ideal for students interested in careers in computer science, data science, neuroscience, psychology, cybersecurity and civic engagement. No prior coding experience is required.

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 and PowerPoint 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.

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.

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.

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.

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.

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.

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.