Capstone Course:

Capstone in AI

The capstone is a 1 semester long project course in which you are embedded in a company or university research group. You will work with stakeholders at these companies or groups to define an Al project which delivers lasting business or research value to these organizations. This process includes, in order, (a) project definition (b) project implementation, with deliverables including the process notebooks and (c) the delivery of results products, along with the communication and visualization of data and results. Mentors from Univ.AI and from the client organization will assist you along the way. Examples of projects include research on unsupervised distribution learning with combined autoencoders and GANS, Unets to learn oilfield saturation maps from permeability fields, the use of autoencoders to represent patient and disease data, and the use of transfer learning to create domain specific classifiers, bots and summarisers. The capstone course will let you gain experience that will be critical for future employment and research.

  • AI 1
  • DSE 1
  • DSE 2
  • AI 2
  • AI 3
  • AI 4


Prerequisites

Topics

Learning Objectives

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Schedule

Students

Summer Cohort

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Conducted alongside elective

Winter Cohort

Intake 1:

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Conducted along with elective

Intake 2:

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Conducted along with elective

Working Professionals

Summer Cohort

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Conducted along with elective

Fall Cohort

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Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.

Conducted along with elective

Winter Cohort

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.

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Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.

Conducted along with elective