Data Science & MachineLearning

This course is aimed at developing practical machine learning and data science skills. It will cover various machine learning concepts and methods as well as hands on programming with Python. The students will be able to identify the type of problems and the appropriate machine learning models, strengths and weaknesses of each model, including the assumptions of the method, and apply machine learning for prediction and evaluate the results.

Quantum Field Theory II

Second half of a full year course in Quantum Field Theory. The focus will be on symmetries in quantum field theory, with a particular emphasis on the Poincare group and its representations. Quantization of spin-1/2 fields will be subsequently covered, followed by an in-depth treatment of Quantum Electrodynamics and its renormalization. An introduction to path integral quantization of non-Abelian gauge theories will also be included.

Quantum Computation

This course introduces the fundamental concepts and techniques relevant for physical implementations of quantum computing. The course focuses on continuous quantum dynamics of few-qubit systems, using concrete examples of superconducting qubits as a main thread. It is intended for physics, engineering, and computer science juniors and seniors who wish to learn the language of experimental quantum information research. (It is particularly suited as a sequel to COMPSCI 490Q: Quantum Information Science from a hardware perspective).

Elementary Italian I

This course emphasizes understanding, speaking, and writing in a contemporary context. It also promotes creativity with presentations and original group projects. It includes Web activities, films, short stories, and frequent conversation sessions with language assistants.

Jody Slade

Submitted by admin on
Primary Title:  
Institution Maintenance Foreman
Institution:  
UMASS Amherst
Department:  
Facilities & Campus Services
Email Address:  
jfslade@umass.edu
Telephone:  
413-545-0812
Office Building:  
Berkshire House

Malcolm Keating

Submitted by admin on
Primary Title:  
Associate Professor
Institution:  
Smith College
Department:  
Philosophy
Email Address:  
mkeating@smith.edu
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