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191 - 196 of 196 results for: all courses

PSYCH 120: Cellular Neuroscience: Cell Signaling and Behavior (BIO 153)

Neural interactions underlying behavior. Prerequisites: PSYCH 1 or basic biology.
Terms: Aut | Units: 4 | UG Reqs: GER: DB-NatSci, WAY-SMA

PUBLPOL 122: Biosecurity and Bioterrorism Response (BIOE 122, EMED 122)

Overview of the most pressing biosecurity issues facing the world today. Guest lecturers have included former Secretary of State Condoleezza Rice, former Special Assistant on BioSecurity to Presidents Clinton and Bush Jr. Dr. Ken Bernard, Chief Medical Officer of the Homeland Security Department Dr. Alex Garza, eminent scientists, innovators and physicians in the field, and leaders of relevant technology companies. How well the US and global healthcare systems are prepared to withstand a pandemic or a bioterrorism attack, how the medical/healthcare field, government, and the technology sectors are involved in biosecurity and pandemic or bioterrorism response and how they interface, the rise of synthetic biology with its promises and threats, global bio-surveillance, making the medical diagnosis, isolation, containment, hospital surge capacity, stockpiling and distribution of countermeasures, food and agriculture biosecurity, new promising technologies for detection of bio-threats and countermeasures. Open to medical, graduate, and undergraduate students. No prior background in biology necessary. 4 units for twice weekly attendance (Mon. and Wed.); additional 1 unit for writing a research paper for 5 units total maximum.
Terms: Win | Units: 4-5 | UG Reqs: GER: DB-NatSci, GER:EC-GlobalCom, WAY-SI
Instructors: Trounce, M. (PI)

STATS 101: Data Science 101

This course will provide a hands-on introduction to statistics and data science. Students will engage with the fundamental ideas in inferential and computational thinking. Each week, we will explore a core topic comprising three lectures and two labs (a module), in which students will manipulate real-world data and learn about statistical and computational tools. Students will engage in statistical computing and visualization with current data analytic software (Jupyter, R). The objectives of this course are to have students (1) be able to connect data to underlying phenomena and to think critically about conclusions drawn from data analysis, and (2) be knowledgeable about programming abstractions so that they can later design their own computational inferential procedures. No programming or statistical background is assumed. Freshmen and sophomores interested in data science, computing and statistics are encouraged to attend. Open to graduates as well. http://web.stanford.edu/class/stats101/
Terms: Aut, Spr | Units: 5 | UG Reqs: GER: DB-NatSci, WAY-AQR

UGXFER NATSCI: GER DB-NATSCI SUBSTITUTION

| UG Reqs: GER: DB-NatSci | Repeatable for credit

UGXFER GER2A1: GER 2A SUBSTITUTION (1ST)

| UG Reqs: GER: DB-NatSci | Repeatable for credit

UGXFER GER2A2: GER 2A SUBSTITUTION (2ND)

| UG Reqs: GER: DB-NatSci | Repeatable for credit
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