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CHEM XL 14BL
General and Organic Chemistry Laboratory I

This chemistry laboratory course accompanies Chemistry 14B and provides the general chemistry lab component necessary for pre-medical and pre-health students. This is the first lab course for the chemistry series.

course
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In Person
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CHEM XL 14B
General Chemistry for Life Scientists II

This course is the conclusion of general chemistry and introduces organic chemistry. This course is geared towards pre-medical and pre-health students and is the second course in the general and organic chemistry series.

course
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Live Online
In Person
CHEM XL 14A
General Chemistry for Life Scientists I

This course provides an introduction to physical and general chemistry and is geared towards pre-medical and pre-health students. This course is the first course in the general and organic chemistry series.

course
Format:
Live Online
In Person
CHEM 827
Cosmetic Sciences: Skin Care Ingredients, Skin Conditions and Regulatory Issues for Cosmetic Professionals

Introduction to claims & claims substantiation, cell & skin biology, the skin’s aging exposome and the Hallmarks of Aging, free radical species & antioxidants, and sunscreens.

course
Format:
In Person
CHEM 825
Skin Care Ingredient Series for Cosmetic Professionals: Part I

Beauty professionals from all genres and areas of expertise will find this course essential for understanding ingredient technologies and U.S. regulations – regardless of scientific background. 

course
Format:
In Person
COM SCI XLC 263
Natural Language Processing

CS 263. Natural Language Processing (Professor: V. Peng) Lecture, four hours; outside study, eight hours. Natural language processing (NLP) enables computers to understand and process human languages. NLP techniques have been widely used in many applications, including machine translation, question answering, machine summarization, and information extraction. Study of fundamental elements and recent trends in NLP. Students gain ability to apply NLP techniques in text-orientated applications, understand machine learning and algorithms used in NLP, and propose new approaches to solve NLP problems. Letter grading.  

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