syl1

Neuroscience and Experience, as taught as an advanced seminar at Stanford;

Biosemiotics/Linguistics, as taught on the Symbolic systems program at Stanford;

Science and Society, as taught in the Molecular and Cell Biology program at UC Berkeley;

Irish Music and Culture, as taught for the Celtic Studies program at UC Berkeley.

comp3

As a result of this course, the graduate will have acquired the skills to be able to:

 

  1. Work as a language-engineer, in particular for the localization of software to other languages and cultures;
  2. Design a computer interface (CI) for specialized use, including for mentally and physically challenged individuals, as US law requires they have unrestricted access to information;
  3. Assist – and of course direct – R+D in the multitude of applications that will emerge over the next several generations of computing, including (but not restricted to) in particular speech processing and machine translation.
  4. Participate in an informed way on debate about how science impacts on society, particularly focusing on their own cutting-edge area.
  5. Work as an applications programmer in a range of commercial and industrial environments.

 

As in all these proposed courses, the student can take subjects from edX and/or Coursera*, and signatures of completion will be accepted as tentative proof that the student has mastered the material. However, in project assessments, those students that have no proof of mastery other than these signatures may be asked questions in oral examinations relating to the content they claim to have mastered. Alternatively, and particularly in the case of Coursera courses that do not give signatures of completion, the students may ask to be examined on the material , and an exam will be prepared for them.

 

It is envisaged that 30 units will be taken in the two “years” which may of course reflect more or less chronological time The only assumption is that the student has an undergraduate degree involving a major in one human language other than the student’s native language. Obviously, the subjects below can be the core for a range of undergraduate degrees, and indeed may be taught in conjunction with a foreign language.A central focus is machine translation The challenges are these;

 

  • To begin the process of mathematical formation, initially through relatively introductory courses in calculus and algebra

  • Likewise, to familiarize the students with computers, beginning with introductory courses

  • To continue the computational formation with algorithms and applications development courses

  • To culminate with a set of subjects focused on Computational linguistics

  • Finally, a set of projects and advanced seminars

 

 

Preparatory courses prior to year 1 for those unsure of their ability to cover the material;

 

Mathematics


A preparatory course is at

https://www.coursera.org/learn/pre-calculus
https://www.coursera.org/learn/trigonometry

Calculus may be handled by this or an equivalent:

https://www.coursera.org/course/calc1

 

Computer Science

There is good introductory material at

https://x.cs50.net/2013/syllabus

 

FIRST SEMESTER

 

Logic

 

This course will satisfy the requirements

 

https://class.coursera.org/intrologic/class/index

 

Linear algebra

This course will satisfy the requirements here

 

https://www.coursera.org/course/matrix

 

Algorithms 1

 

https://class.coursera.org/algo/class/index

 

is a very good start

 

compare https://www.coursera.org/course/algs4partI

 

which does not issue Certs

 

Applications development

 

SAAS gives a good intro

 

https://www.edx.org/courses/BerkeleyX/CS169.1x/2012_Fall/about

 

 

SECOND SEMESTER

algorithms 2

https://www.coursera.org/course/algs4partII

This will not involve a certificate

 

App Dev 2

SAAS2 https://www.edx.org/courses/BerkeleyX/CS169.2x/2012_Fall/about

 

 

NLP/Computational linguistics

either this

 

https://class.coursera.org/nlp/wiki/view?page=syllabus

 

or a computational linguistics module can be taken

 

 

HCI

 

https://class.coursera.org/hci/wiki/view?page=Syllabusandcalendar

 

 

An introduction to text linguistics, rounds out the year and we are preparing this

 

 

YEAR 2

 

 

Semester 1

 

 

AI

 

 

https://www.edx.org/courses/BerkeleyX/CS188.1x/2012_Fall/about

Stats in the age of Big data

Non-certificate courses include

Introduction

https://www.coursera.org/course/compdata

More advanced

https://www.coursera.org/course/dataanalysis

https://www.coursera.org/course/datasci

COMPILERS

https://www.coursera.org/course/compilers

 

 

Advanced seminars/projects will be the focus; the seminars will include topics from other areas such as tensor calculus, neuroscience and science and society as well as project presentations by the students with mandatory attendance. There will be a minor thesis, with subject proposed by either faculty or student (7 credits) and a major thesis to be entirely conceived by the student (10 credits)

 

 

Internship – 6 months, supervised at a participating company

*We do not claim to own content linked at Coursera and edX. We simply suggest courses you can take online that satisfy our requirements. There are zero fees for full-time students. Others who wish to take one our own modules, like consciousness studies, may pay a suggested donation. Nobody turned away for lack of funds!
 

bach1

As a result of this course, the graduate will have acquired the skills to be able to;

 

1. Design a computer game using specialized knowledge of how the brain processes the information presented on the screen;

2. Help to diagnose a patient based on a print out of the relevant genetic information, an interview, and overt behaviour analysis;

3. Design a computer interface (CI) for specialized use, including for mentally and physically challenged individuals, as US law requires they have unrestricted access to information;

4. Assist – and of course direct – R+D in the multitude of applications relating to cognition that will emerge over the next several generations, including (but not restricted to) intelligent search, machine translation, human CI in general (including neural implants), speech processing, bioinformatics approaches to brain, and so on

5. Participate in an informed way on debate about how science impacts on society, particularly focusing on their own cutting-edge area.

6. Work as an applications programmer in a range of commercial and industrial environments

 

As in all these proposed courses, the student can take subjects from EDX and/or coursera, and signatures of completion will be accepted as tentative proof that the student has mastered the material. However, in project assessments, those students that have no proof of mastery other than these signatures may be asked questions in oral examinations relating to the content they claim to have mastered. Alternatively, and particularly in the case of coursera courses that do not give certs the students may ask to be examined on the material at UOI, and an exam will be prepared for them

 

It is envisaged that 30 academic units will be taken in the two introductory “years” which may of course reflect more or less chronological time The challenges are these;

 

  • To begin the process of mathematical formation, initially through relatively introductory courses in calculus and algebra

  • Likewise, to familiarize the students with computers, beginning with introductory courses

  • To continue the computational formation with algorithms and applications development courses

  • To culminate with a set of subjects focused on cognitive science

  • Finally, a set of projects and advanced seminars

 

 

Preparatory/year 1

 

FIRST SEMESTER

 

Mathematics

 


A preparatory course is at

https://www.coursera.org/learn/pre-calculus
https://www.coursera.org/learn/trigonometry

Calculus may be handled by

https://www.coursera.org/course/calcsing

 

or

 

https://www.coursera.org/course/calc1

Computer Science

There is good introductory material at

https://x.cs50.net/2013/syllabus

 

SECOND SEMESTER

 

Logic

 

This course will satisfy the requirements

 

https://class.coursera.org/intrologic/class/index

 

Linear algebra

This course will satisfy the requirements here

 

https://www.coursera.org/course/matrix

 

Algorithms 1

 

https://class.coursera.org/algo/class/index

 

is a very good start

 

compare https://www.coursera.org/course/algs4partI

 

which does not issue Certs

 

Applications development

 

SAAS gives a good intro

 

https://www.edx.org/courses/BerkeleyX/CS169.1x/2012_Fall/about

 

 

The biosemiotics course, which incorporates an introduction to linguistics, rounds out the year.

 

YEAR 2

 

Semester 1

algorithms 2

https://www.coursera.org/course/algs4partII

This will not involve a certificate

 

App Dev 2

SAAS2 https://www.edx.org/courses/BerkeleyX/CS169.2x/2012_Fall/about

 

 

NLP/CL

either this

 

https://class.coursera.org/nlp/wiki/view?page=syllabus

 

or a computational linguistics module can be taken

 

 

SEMESTER 2

 

HCI

 

https://class.coursera.org/hci/wiki/view?page=Syllabusandcalendar

 

AI

 

 

https://www.edx.org/courses/BerkeleyX/CS188.1x/2012_Fall/about

Stats in the age of Big data

Non-certificate courses include

Introduction

https://www.coursera.org/course/compdata

More advanced

https://www.coursera.org/course/dataanalysis

https://www.coursera.org/course/datasci

COMPILERS

https://www.coursera.org/course/compilers

Year 3

There will be an intensive semester focussing on the subjects that comprise cognitive science; philosophy, psychology, linguistics, neuroscience, AI, anthropology, paramedical studies, engineering and biocomputing. There will be a minor thesis, with subject proposed by either faculty or student (7 credits) and a major thesis to be entirely conceived by the student (10 credits)