AI News, Python Computing for Data Science

Python Computing for Data Science

Python has become the de facto superglue language for modern scientific computing.

In this course we will learn Pythonic interactions with databases, imaging processing, advanced statistical and numerical packages, web frameworks, machine-learning, and parallelism.

In the final project, students will build a working codebase useful for their own research domain.

Throughout these lectures we will be peppering in sidebar knowledge concepts: Each Monday we will be introducing a resonably self-contained topic with two back-to-back lectures.

Electrical Engineering and Computer Science

Introduces practices for building a successful company, such as idea creation and validation, defining a value proposition, building a team, marketing, customer traction, and possible funding models.

In teams, students create a plan for a project of their choice in one of several areas, including aircraft modification, factory automation, enterprise software, flood prevention engineering, solar farm engineering, among others.

************************************************************************* [New for IAP 2018] Masa Bando January 8, 9, 10, 11, 12, 16, 17, 18, 19, 22, 23, 24, 25, 26, 29, 30, 31, 1, 2, 11-1 pm, 34-302 Preregister

U (6 units)   Graded P/D/F We'll analyze software, design and construct analysis tools, and study powerful analysis techniques such as shadow memory.  Learn to create tools for code coverage, memory monitoring, etc.  Class concludes with a final project designing and creating your own analysis tool.   Contact Masa Bando, ************************************************************************* [Updated for IAP 2018] Stefanie Shattuck-Hufnagel, Alejna Brugos, Nanette Veilleux January

The course is appropriate for undergrad or grad students with background in linguistics (phonology or phonetics), cognitive psychology (psycholinguistics), speech acoustics or music, who wish to learn about the prosody of speech, i.e.

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