| IF 100 Computational Approaches to Problem Solving |
3 Credits |
|
The course is an introduction to the key concepts in
computational thinking such as algorithmic thinking,
abstraction and decomposition. The students will also
gain basic programming skills in order to apply
computational thinking concepts in practice.
Through the lectures, homeworks, and interactive
recitations specific to different disciplines, the students
will learn how to design algorithms, how to divide a
problem into subproblems, and how to build a
solution by means of compositions. Evaluation of the
solutions in terms of correctness and
efficiency will also be covered.
In order to enable students apply computational thinking
skills in practice, basic programming concepts, such
as variables, statements, conditionals, iteration, and
functions will be introduced by using a simple
programming language such as Python.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2023-2024 |
Computational Approaches to Problem Solving |
3 |
| Fall 2023-2024 |
Computational Approaches to Problem Solving |
3 |
| Summer 2022-2023 |
Computational Approaches to Problem Solving |
3 |
| Spring 2022-2023 |
Computational Approaches to Problem Solving |
3 |
| Fall 2022-2023 |
Computational Approaches to Problem Solving |
3 |
| Summer 2021-2022 |
Computational Approaches to Problem Solving |
3 |
| Spring 2021-2022 |
Computational Approaches to Problem Solving |
3 |
| Fall 2021-2022 |
Computational Approaches to Problem Solving |
3 |
| Summer 2020-2021 |
Computational Approaches to Problem Solving |
3 |
| Spring 2020-2021 |
Computational Approaches to Problem Solving |
3 |
| Fall 2020-2021 |
Computational Approaches to Problem Solving |
3 |
| Summer 2019-2020 |
Computational Approaches to Problem Solving |
3 |
| Spring 2019-2020 |
Computational Approaches to Problem Solving |
3 |
| Fall 2019-2020 |
Computational Approaches to Problem Solving |
3 |
| Summer 2018-2019 |
Computational Approaches to Problem Solving |
3 |
| Spring 2018-2019 |
Computational Approaches to Problem Solving |
3 |
| Fall 2018-2019 |
Computational Approaches to Problem Solving |
3 |
| Summer 2017-2018 |
Computational Approaches to Problem Solving |
3 |
| Spring 2017-2018 |
Computational Approaches to Problem Solving |
3 |
| Fall 2017-2018 |
Computational Approaches to Problem Solving |
3 |
|
| Prerequisite: __ |
| Corequisite: IF 100R |
| ECTS Credit: 5 ECTS (5 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IF 100R Computational Approaches to Problem Solving – Recitation |
0 Credit |
|
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2023-2024 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Fall 2023-2024 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Summer 2022-2023 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Spring 2022-2023 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Fall 2022-2023 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Summer 2021-2022 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Spring 2021-2022 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Fall 2021-2022 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Summer 2020-2021 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Spring 2020-2021 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Fall 2020-2021 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Summer 2019-2020 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Spring 2019-2020 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Fall 2019-2020 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Summer 2018-2019 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Spring 2018-2019 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Fall 2018-2019 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Summer 2017-2018 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Spring 2017-2018 |
Computational Approaches to Problem Solving – Recitation |
0 |
| Fall 2017-2018 |
Computational Approaches to Problem Solving – Recitation |
0 |
|
| Prerequisite: __ |
| Corequisite: IF 100 |
| ECTS Credit: NONE ECTS (NONE ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IF 200 Fantasy, Reality, Science and Society |
3 Credits |
|
This course aims at making certain that our students
can maximally benefit from the rich and diverse
accumulation of knowledge at Sabancı University. It is an
interfaculty course, supported by our Faculty of
Engineering and Natural Sciences, Faculty of Arts and
Social Sciences, and Faculty of Management. The
contents are modular, such as: 1. Water: Its Physics,
Nanophysics, Chemistry, and Geopolitics; 2. Barriers
in Istanbul Facing Specially Challenged Persons; 3.
Quantum Computing and Time Travel; 4. Jules Verne,
Literature, Fantasy, Reality; 5. Economy, Finance, and
Your Future Well-Being; 6. Gender and
Cultural Rights, Richness in Diversity; 7. Phase Changes,
Scale Invariance, Universality, Brain and Memories.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2016-2017 |
Fantasy, Reality, Science and Society |
3 |
| Spring 2015-2016 |
Fantasy, Reality, Science and Society |
3 |
| Fall 2015-2016 |
Fantasy, Reality, Science and Society |
3 |
| Spring 2014-2015 |
Fantasy, Reality, Science and Society |
3 |
| Fall 2014-2015 |
Fantasy, Reality, Science and Society |
3 |
| Spring 2013-2014 |
Fantasy, Reality, Science and Society |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 6 ECTS (6 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IF 301 Gender in Science and Technology |
3 Credits |
|
Why are there relatively few women scientists in
some disciplines?
Does gender influence the production of scientific
knowledge and its content?
What kind of an impact did the entering of women
into science and engineering have? What is
“gendered science”? This course aims to
investigate these and related questions. It starts by
introducing the concept of gender and how science,
technology, engineering, mathematics (STEM) and
this concept are related to each other in general. It
then examines the historical exclusion of women
from these fields, their experiences and struggles
against it as well as the scientific, technological and
socio-economic costs of this exclusion. Finally, it
explores the policies and “best practices” that
eliminate gender biases in STEM fields, their
affects in the further development of STEM fields
and the new areas of research that arose as a result
of these efforts.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2019-2020 |
Gender in Science and Technology |
3 |
| Fall 2018-2019 |
Gender in Science and Technology |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 6 ECTS (6 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IF 333 Creativity, Innovation and Entrepreneurship |
3 Credits |
|
In this course, wide range approaches, techniques
and tools that have been developed for the
effective management of creativity, innovation
and entrepreneurship will be reviewed and
discussed in a common framework. Students will develop an
entrepreneurial project and have the opportunity to apply
these different approaches, techniques and tools
in a practical case. The students will learn how human
creative processes are organized and what their
underlying brain mechanisms are. Some of the topics that
will be included in this course are individual differences
in creativity, team creativity, visual imagery and
creativity, expertise and creativity, development of
creativity, creative problem solving
(cognitive mechanisms & creative strategies),
intelligence and emotional intelligence, brain basis of
creativity. This course will also focus on
qualitative and quantitative approaches, techniques and
tools (e.g.: data visualization, data analyses, focus groups
, structured/semi structured interviews, delphi method,
brainstorming, mind mapping, kano analysis, fishbone
analysis etc.) that provide students with abilities and
skills to further scrutinize, test and make decisions about
the problems and creative solutions that are developed
during the course and for their projects. During the
course, various steps of the process of realization of the
new ideas and products such as: value creation,
identification of target customers/ users, business models,
teaming, leadership, finding and acquiring resources, and
pitching ideas to resource holders, DMAIC (define,
measure, analyze, improve and control) the key
performance indicators will also be delivered.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2017-2018 |
Creativity, Innovation and Entrepreneurship |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 6 ECTS (6 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IF 467 Decision, Psychology and Brain |
3 Credits |
|
Many scientific fields such as neuroscience, psychology,
operations research, management science have modeled,
analyzed, and tried to understand how people make
decisions, with various tools, techniques and approaches
within their own conventional theoretical frameworks.
Recent advances in technology have accelerated brain
research, and have given the opportunity to experiment and
question the theoretical frameworks related to decision
making developed in various disciplines. In this
regard, decision making has become of particular interest
to scientific fields such as cognitive and behavioral
neuroscience, cognitive psychology, computational sociology
and neuroeconomics.
In this course, the students will learn how to model
realistically and consistently the basic elements of
decision making, i.e., the value system and objectives
, alternatives, uncertainties, and preferences, based on
the mathematical frameworks provided by various fields
such as economics, operations research, computer sciences,
as well as cognitive, physiological, and behavioral
neuroscience.
In the course, some mathematical tools, techniques
and approaches (e.g., decision trees, game theory,
mathematical programming, modeling uncertainty and Bayes
theorem, Bayesian learning, modeling of preferences and
vNM utility theory, entropy, decision tree learning and
artificial neural networks) which will provide an
analytical framework for decision making an learning
will be covered. Aside to these techniques findings from
the recently growing fields such as neuroeconomics,
behavioral economics and behavioral neuroscience (e.g.,
prospect theory, conditioning, reinforcement, reward
and punishment, expectation of judgment and decision-
making, experience and deferral) will also be discussed
within the same framework. In the course neural
processes and mechanisms of social and individual decision
making, behavior and choice (e.g., reward perception,
learning types, attention, memory, belief systems,
interaction with motor processes, trust, cooperation,
alturism, social behavior) will be addressed and supported
by neuroethological comparisons.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2017-2018 |
Decision, Psychology and Brain |
3 |
|
| Prerequisite: (NS 201 - Undergraduate - Min Grade D) |
| and (MATH 203 - Undergraduate - Min Grade D) |
| Corequisite: __ |
| ECTS Credit: 6 ECTS (6 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
