Curriculum and Schedules

For Students of Academic Year 2018/19

1st yr students: 30 credits to be collected during the academic year (22 for courses, 8 for PhD thesis proposal.)

2nd and 3rd yr students: 30 credits to be collected during the academic year (4 for courses, 6 for JC+Colloquia, 2 for conference presentation, 18 for PhD Progress Report)

Curriculum

The main goal of the coureses in our PhD program is to ensure that the students master the basic notions and theories in cognitive science and can do cutting-edge doctoral research in one area of expertise of program, such as social cognitive sciences and the study of social cognition. The PhD program will provide basic training (taught courses) on at least the following topics:

  • Cognitive psychology
  • Research methods in cognitive science
  • Social cognition

The credit requirements to be fulfilled during the three-year Cognitive Science PhD program are such that the course work is concentrated during the first year, while most of the requirements are research focused.

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Courses and Syllabi

Fall Term (2018/19) - credit requirements: 10 for 1st yr, 4 for 2nd and 3rd yr students.

Core Course:

Research Courses: [4 credits to be elected for 1st yr students]

Elective Courses: [2 credits to be elected -by both 1st, 2nd and 3rd yr students. This can also be selected as a further research course]

  • Computational Cognitive Science – Gergo Orban (2 credits, for Grade) crosslisted with CNS and MATHS
  • Critical perspectives on human nature - Maria Kronfelder (4 credits for Grade) PHIL offers for crosslist
  • Scientific Python – Janos Torok (2 credits for Grade) MATHS offers for crosslist
  • Introductory Python (2 credits for Grade) MATHS offers for crosslist
  • Graph Theory and Applications - Ervin Győri (2 credits for Grade) MATHS offers for crosslist
  • Probability in Economics – Balint Peter (2 credits for Grade) MATHS offers for crosslist, University Wide Course
  • How to think about science (2 credits for Grade) University Wide Course

Mandatory to attend for Pass/Fail  (for all 1st, 2nd 3rd yr students):

  • CDC Seminar/Department Colloquium - (1 credit for Pass/Fail)
  • Journal Club/Research Club - (1 credit for Pass/Fail)

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Winter Term (2018/19) - credit requirements: 10 for 1st yr, 4 for 2nd and 3rd yr students

Core Courses:

  • Statistics for Experimental Research - Jozsef Fiser (2 credits for Grade)

Elective Course [2 credits to be elected for 1st yr students, 2 credits for 2nd and 3rd yr students]:

  • Metarepresentations– Agnes Kovacs, Gergely Csibra (2 credits, for Grade), offered for Crosslist with Phil
  • Bayesian Data Analysis - Jozsef Fiser (2 credits, for Grade)
  • Social Cognition - Natalie Sebanz and Gunther Knoblich (2 credits for Grade) crosslisted with CNS and MATHS
  • Cognitive Science and Policy Making - Christophe Heintz, Anand Murugesan, (2 credits for Grade) crosslisted with PHIL, POLS, SPP and MATHS
  • Algorithms and Data Structures (2 credits for Grade) MATHS offers for crosslist
  • Fundamentals Stochastic Analysis - Miklós Rásonyi (2 credits for Grade) MATHS offers for crosslist
  • Mathematics and Fear - Miklós Abért  (2 credits for Grade) MATHS offers for crosslist
  • Statistical Methods in Network Science and Data Analysis (4 credits for Grade) –  Michael Szell - CNS offers for crosslist
  • Agent Based Models (2 credits for Grade) – Kertész János– CNS offers for crosslist
  • Data Mining & Big Data Analytics (2 credits for Grade) - CNS offers for crosslist
  • Data Management with Python (2 credits for Grade) - Ancsa Hannak - CNS offers for crosslist

One Individual Study Course with the Supervisor, 4 credits, graded (mandatory for all 1st yr students)

Mandatory to attend for Pass/Fail  (for all 1st 2nd 3rd yr students):

  • CDC Seminar/Department Colloquium- (1 credit for Pass/Fail)
  • Journal Club/Research Club - (1 credit for Pass/Fail)

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Spring Term (2018/19)

  • Research Proposal Development (8 credits for Pass/Fail - for 1st year students)
  • Comprehensive exam (0 credits for Pass/Fail - for 1st year students)
  • PhD Progress Report and Chapter (18 credits for Pass/Fail- for 2nd and 3rd yr students)
  • Conference presentation (2 credits for Pass/Fail - for 2nd and 3rd yr students)
  • CDC Seminar/Department Colloquium - (1 credit for Pass/Fail - for all 1st, 2nd 3rd yr students)
  • Journal Club/Research Club - (1 credit for Pass/Fail - for all 1st, 2nd 3rd yr students)

Detailed course descriptions are available at Courses.

Departmental Essay Marking Scheme is available here.

More information on credits and CEU Grading System available at Student Records Office.

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Exam Schedules

StatISTICS exam; 2 April, 2019. 10:00 am in Room 101.

Comprehensive Exam for 1st yr students: 28 May, Tuesday, 2019, 9:00 am, room 103.

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Student Handbook 2018-19

Student Records Manual 2018-19