73
ÅboAkademiUniversity2014/2015
ÅBO CAMPUS
Analytics
(AnalyticsandSoftComputing)
457515.0
5credits
Advanced (Master's /graduate) level
Lecturedcourse
Offered:Autumn2014
Target audience:Master level students (4thyear and later)
Lecturer: JozsefMezei
Aimandcontent: Informationandcommunicationtechnology
[ICT]hasbecomebothanessential resource forbusinessand
anefficient,effectiveanddevelopable instrument forachiev-
ing the strategic targets thatmoderncorporations face. The
courseprovides the studentswithabasis forunderstanding
these relations; the students will be able to independently
study furtherandunderstand thedevelopmentof ICT instru-
ments and their strategic consequences, and to formulate
newstrategicsolutions forcorporations facingthechallenges
posedbyadvances in ICT.
Themaincontentsof thecourseare:
.
Analyticsandcorporatemanagement
.
Advancedanalyticsandcomputational intelligence
.
Complexdecisionsandadvancedmethods
.
Riskassessment and riskmanagement
.
The forgotten skillsof optimization: industrial cases
.
Knowledgemanagement andmobilization
.
Competingonanalytics
After completing thecoursea student shouldbeable to
.
Understand and explain the key possibilities and chal-
lenges of analytics inmodern corporations in the form
ofwrittenessays; the issues include riskassessmentand
management, complex decisions, advanced planning
in real time, knowledgemanagementandmobilisation,
competingonanalytics
.
Learnhow tosearch forandfind relevantdata, informa-
tion and knowledge in support of the issues dealtwith
in thecoursebyworking through internet sourceswith
intelligent ICT tools
.
Read, learn and critically evaluate thematerial of text-
books, articlesandcase studies
Prerequisites:Basicand intermediate levelcourses in Informa-
tionSystems; Computational IntelligenceandManagement
ElectronicCommerce
457502.0
5credits
Advanced (Master's /graduate) level
Lecturedcourse
Offered:Spring2015
Target audience:Master level students (4thyear and later)
Lecturer: PirkkoWalden
Aimandcontent:Thecoursefocusesonthedevelopmentand
use of businessmodels in electronic commerce. It provides
an insight into thealternativeapproaches, suchasCANVAS,
STOF,C-SOFTorVISOR, andhow theycanbeused toanalyze
e-commercebusinesscases.Attention to the technical foun-
dationofe-Commerce isalsopaidas theanalysisofbusiness
caseswillbeenhancedwithadescriptionofthebusiness logic.
Learninggoals: The learninggoalsof thecourseare:
.
Togainknowledgeaboutbusinessmodelsandbusiness
logicandhow theyareused inelectroniccommerce
.
To gain insights through the analysis of e-commerce
business cases
.
To understand how business models are related to
business logic
Prerequisites:Bachelordegree in InformationSystems/Busi-
nessor equivalent
DataMiningandTextMining
457513.0
5credits
Advanced (Master's /graduate) level
Lecturedcourse, researchexercises ingroups
Offered:Spring2015
Target audience:Master level students (4thyear and later)
Lecturer: BarbroBack
Aim and content: Today, many organizations strugglewith
vastamountsofdata.Worldwidethecomputershaveturned
intomassivedata tombs. It ismore thanevident thatwecan
capture and store data, but it is not at all evident that we
are able to process and utilize it effectively and efficiently.
This course concerns solutions to this problem: data and
text mining. The course focuses onwhat data/text mining
is, what data/text mining techniques and tools there are,
and how to use a sample of the tools and techniques. We
willusecasestudiesusing largedatasets taken from real-life
applications. Datamining softwarewill be used extensively
during thecourse.
After completing thecourse, students shouldbeable to
.
Describe the roleof datamining and textmining in an
organization
.
Differentiatebetweendatamining, databasesanddata
warehousing
.
Create, evaluate and apply decision treemodels, un-
supervised clustering, market basket models, Support
vectormachines, RoughSets
.
Developscenarios inwhichuseofdecision treemodels,
unsupervisedclustering,marketbasketmodels,Support
vectormachines, RoughSetswouldbeappropriate
.
Performanceevaluationofdataminingand textmining
methods
.
Use data mining software to develop and apply data
miningmodels tobusinessproblems
.
Discussethical issuessurroundingtheuseofdatamining
Prerequisites:Bachelordegree in InformationSystems/Busi-
nessorequivalent;DatabasesorDataWarehousing;Business
Intelligence
MobileValueServices
457516.0
5credits
Advanced (Master's /graduate) level
Lecturedcourse, researchexercises ingroups
Offered:Spring2015
Target audience:Master level students (4thyear and later)
Lecturer: PirkkoWalden
Aimandcontent:Thecourseaimstotraceemergingmethods,
technologies and business models for the production and
distributionofmobilevalueservicesandtoshowtheroleand
impactofmobile technologyon themanagementprocesses
inthecorporateworld.Mobilevalueservicesarenewentities
inbothB-to-BandB-to-Cmarketsandwill introduceprocesses
ofchange,withan impactonsustainablecompetitiveadvan-
tages foracompany.Central themes in thecoursewillbe the
substance and formof newproducts and services, business
models, emergingmarkets and information technology to
support themobile technologyand logisticsprocesses.
Themaincontentsof thecourseare:
.
Mobilevalue services: a state-of-the-art
.
Emergingproductsand services
.
Businessmodelsandemergingmarkets
.
Wireless technologies
.
Intelligent support systemsonmobileplatforms
Prerequisites:Bachelordegree in InformationSystems/Busi-
nessor equivalent.
