|
|
| Language |
English |
| Exam ECTS |
7.5 ECTS |
| Type |
Elective |
| Level |
Full Degree Master |
| Duration |
One Semester |
| Course period |
Autumn
Changes in course schedule may occur
Tuesday 08.00-09.40, week 36-41, 43-51 |
| Time Table |
Please see course schedule at e-Campus |
| Study board |
Study Board for BSc/MSc in Business Administration and
Information Systems, MSc
|
| Course
coordinator |
- Daniel Hardt - Department of IT Mangement
(ITM)
|
| Administrative
contact person is Jeanette Hansen, ITM (jha.itm@cbs.dk). |
| Main academic
disciplines |
- Information Systems
- Innovation and entrepreneurship
|
|
Last updated on
15-03-2013
|
| Learning objectives |
- Independently identify, select and combine key theoretical
concepts taught in the course, and apply them on real business
cases
- Explain in depth, assess and analyze the key ideas and
techniques underlying Artificial Intelligence technologies
- Critically evaluate and compare the development and impact of
Artificial Intelligence technologies in different business
areas
- Identify and analyze the strategies and plans of leading
businesses with respect to Artificial Intelligence technology
- Describe and deploy tools for analysis and description of
web-based data
- Identify and analyze a specific problem which can be addressed
by new Artificial Intelligence techniques
|
| Examination |
|
Oral exam on
the basis of a mini project (group):
|
| Examination form |
Oral exam based on written product
In order to participate in the oral exam, the written product
must be handed in before the oral exam; by the set deadline. The
grade is based on an overall assessment of the written product and
the individual oral performance. |
| Individual or group exam |
Individual |
| Size of written product |
Max. 15 pages |
| Assignment type |
Project |
| Duration |
Written product to be submitted on specified date and
time.
20 min. per student, including examiners' discussion of grade,
and informing plus explaining the grade |
| Preparation time |
No preparation |
| Grading scale |
7-step scale |
| Examiner(s) |
Internal examiner and second internal
examiner |
| Exam period |
December/January |
| Make-up exam/re-exam |
Same examination form as the ordinary exam
|
Description of the exam
procedure
Oral exam on the basis of a project (individual or group),
max. 10 pages per student and max. 15 pages per 2-5 students.
The project is written in parallel with the course. The
student is not entitled to supervision. The date for handing
in the project will be decided by the secretary.
20 minutes per student incl. performance discussion. No
preparation for the oral exam. The teacher will act as examiner at
the oral exam. 2nd examiner is internal (CBS).
Even if it is a group exam, each student must be assessed
individually. The students do not need to give an account of which
parts of the project they are responsible for. The project and
the oral exam are both included in the overall assessment.
The title question(s) and content of the project must be prepared
by the student(s) within the framework of the syllabus, possibly
together with the teacher. The oral examination will be based on a
discussion and a perspective of the project. The examiner may
ask questions that go beyond the project, but within the framework
of the syllabus.
The re-exam takes place on the same conditions as the ordinary
exam.
|
|
| Course content and
structure |
|
This course examines new Artificial Intelligence technologies that
are rapidly transforming the digital marketplace. One highly
publicized example is Watson, IBM’s intelligent question-answering
system that recently won the game show Jeopardy! Another
high-profile example is Google Translate, which now translates more
text than all the world’s human translators. A few short years
ago Artificial Intelligence technology was primarily relegated
to the realm of fantasy and science fiction – now it is driving new
businesses and technologies in a wide range of areas, such as
e-discovery, sentiment analysis, topic tracking, and summarization.
We will see that the sudden emergence of successful AI systems
involves two key factors: the application of massive computing
power, and leveraging the wisdom of crowds.
Facebook, Twitter and similar services are generating an
enormous amount of data, covering every imaginable topic in
thousands of different languages and styles. Artificial
Intelligence is the key that can unlock the information in
these massive unstructured collections of data. Students will get
hands-on experience with newly developed tools for doing this.
We will look at how AI technology is central to the strategies of
IT Giants like Google, Microsoft, Facebook, Apple and IBM –
and we will look at speculation about how these developments
may well accelerate in the near future. A key point is that AI
technologies are becoming widely available, with
public descriptions and open-source implementations. This
means that they are no longer the province of large powerful
companies, and we will see how AI technologies are playing an
increasingly important role now for many small companies. Students
will have an opportunity with hands-on exercises to learn how
to access and deploy many of the leading technologies.
|
| Teaching methods |
| The class combines lectures,
discussions and group work. Students will apply the course material
in group presentations, and will get hands-on experience in the
development, deployment and assessment of computational
tools. |
| Expected literature |
Anderson (2004). The Long tail,
Wired, No. 10 (6 pages)
Asur and Huberman, 2010. Predicting the Future with Social Media.
CoRR (10 pages)
Bollen et al. 2011. Twitter mood predicts the stock market,
Journal of Computational Science, 2(1), March 2011, Pages
1-8
Grossman, L (2011)2045: The Year Man Becomes Immortal. Time
Magazine. Feb. 10, 2011.
Halavy et al. (2009) The Unreasonable Effectiveness of Data.
Intelligent Systems 24(2)
Huberman et al. (2009) Crowdsourcing, Attention and Productivity,
Journal of Information Science.
Joy, Bill (April 2000), Why the future doesn’t need
us. Wired Magazine (Viking Adult)
(8.04), ISBN 0670032492, retrieved 2007-08-07
O’Reilly and Battelle (2009) Web Squared: Web 2.0 Five Years On.
www.web2summit.com
Pang and Lee (2008) Opinion Mining and Sentiment Analysis.
Foundations and Trends in Information Retrieval 2.
Roush (2011) Inside Google’s Age of Augmented Humanity. Xconomy.com
Saunter.T. (2009) Assessing an Augmented Future. Digital
Cortex |
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