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Social Policy (S40)  (Dept. Info)Social Work and Public Health  (Policies)
S40 SWSP 5608MSP Short Course: A Practical Introduction to Artificial Intelligence Using Python2.0 Units
Description:Priority is given to MSP students. Space permitting, MSW and MPH students may enroll for elective credit. The course contributes to the overarching goal of training next-generation policy analysts in modern data analytics. It aims to equip students with the core knowledge and essential skills to apply deep learning models to address real-world problems. Through the course, students will familiarize themselves with computer programming in data science, learn state-of-the-art deep learning models, and apply them to social and behavioral questions. In addition, one essential field of deep learning applications is assisting decision- and policy-making through identifying patterns and trends, improving prediction precision, and automating evidence collection, synthetization, and dissemination. MSP students who master deep learning tools will be at the frontier to leverage the power of AI in policy analysis and practices. Data are now available to social scientists in a way and quantity that has never existed before, presenting unprecedented opportunities for advancing social research and practices through state-of-the-art data analytics. On the other hand, dealing with extensive, complex, unconventional "big data" (e.g., free text, image, video/audio recording) requires revolutionary analytic tools only made available during the past decade. Artificial intelligence (AI), characterized by machine and deep learning, has become increasingly recognized as an indispensable tool in modern social and behavioral sciences. For example, AI methodologies have been applied to enhance the effectiveness of diagnosis and prediction of disease conditions, advance understanding of human development and functioning, and improve the effectiveness of data management in various social and human services. As a subdomain of AI, deep learning is based on artificial neural networks in which multiple ("deep") layers of processing are used to extract higher-level features progressively fro
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Instruction Type:Online Course Grade Options:C Fees:
Course Type:HomeSame As:N/AFrequency:None / History
Label

Home/Ident

A course may be either a “Home” course or an “Ident” course.

A “Home” course is a course that is created, maintained and “owned” by one academic department (aka the “Home” department). The “Home” department is primarily responsible for the decision making and logistical support for the course and instructor.

An “Ident” course is the exact same course as the “Home” (i.e. same instructor, same class time, etc), but is simply being offered to students through another department for purposes of registering under a different department and course number.

Students should, whenever possible, register for their courses under the department number toward which they intend to count the course. For example, an AFAS major should register for the course "Africa: Peoples and Cultures" under its Ident number, L90 306B, whereas an Anthropology major should register for the same course under its Home number, L48 306B.

Grade Options
C=Credit (letter grade)
P=Pass/Fail
A=Audit
U=Satisfactory/Unsatisfactory
S=Special Audit
Q=ME Q (Medical School)

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No section found for SP2025.