Τμήμα Εφαρμοσμένης Πληροφορικής
Σχολή Επιστημών Πληροφορίας

Program of studies




acad.year 2015-2016

Applied Informatics - Technology Management: 1st year
[Semester 1] [Semester 2] 
AI - Applied Informatics
[Semester 3] [Semester 4] 
[Semester 5] [Semester 6] [Semester 7] [Semester 8] 
TM - Technology Management
[Semester 3] [Semester 4] 
[Semester 5] [Semester 6] [Semester 7] [Semester 8] 

Semester 2
Study Direction: Applied Informatics - Technology Management: 1st year   


APPLIED MATHEMATICS II (ΠΛ0112) up.gif
Hristu - Varsakelis Dimitrios    Mamatas Eleftherios     

General Competences
Introduction to Mathematical Analysis, Optimization, Difference Equations, Basic usage of Python.
Course Content
1. Function differentiation - differentials
2. Differentiation of multivariable functions
3. Sequences, Series and Convergence
4. Taylor series and applications
5. Extrema of multivariable functions
6. Optimization with equality constraints
7. Difference Equations – equilibrium points, stability
8. Introduction to Python as a computational tool.
Assessment
Written Final examination 100%
Course Bibliography
(One of the following) :
• Ν. Μυλωνάς και Γ. Σαραφόπουλος, Οικονομικά Μαθηματικά, εκδ. Τζιόλα, 2015.
• Λουκάκης, Μανόλης. Πρόσκληση στα Μαθηματικά Οικονομικών και Διοικητικών Επιστημών. 1η. Τόμ. Β΄. Θεσσαλονίκη: Σοφία, 2014.
• Hoy, Michael, και συν. Μαθηματικά Οικονομικών Επιστημών. Επιμ. Ιωάννης Κυρίτσης. Αθήνα: Gutenberg, 2012..
Additional Material
Instructor's Notes



DATA STRUCTURES (ΠΛ0201) up.gif
Koloniari Georgia    Satratzemi Maria     

General Competences
The of this course is the study of data structures and it is focused in two axes: a) the recognition and the development of useful mathematic models (Abstract Data Types (ADT) and their functions as well as the determination of categories of problems that they can solve. b) the development of methods of representation for the objects of abstract data models and the implementation of their functions in procedural programming language C.
Course Content
1. Introduction to Data Structures.
2. Stacks, Basic operations, implementing stacks with arrays and records, application of stacks.
3. Queues, Basic operations, implementing Queues with arrays and records, application of Queues.
4. Lists, Basic operations, sequential storage implementation of Lists.
5. Introduction to Linked Lists, array-based implementation of Linked Lists. A pointer-based implementation of Linked lists. A pointer-based implementation of Stacks and Queues.
6. Linked implementation of sparse polynomials.
7. Binary Trees, basic operations. A pointer-based implementation of Binary Trees. A recursive implementation of Binary trees. Application of Binary Trees: Huffman Codes.
8. Hashing, open probing, Chaining.
9. B-Trees. AVL Trees, basic operations.
Assessment
Written Examination 80%
Compulsory Assignments 20%
Course Bibliography
(One of the following):
• Μισυρλής, Νικόλαος. Δομές Δεδομένων με C. Αθήνα, 2008.
• Sahni, Sartaj. Δομές Δεδομένων, αλγόριθμοι και εφαρμογές στη C++. Θεσσαλονίκη: Εκδόσεις Τζιόλα, 2004.
• Μποζάνης, Μποζάνης. Δομές Δεδομένων. 2η έκδ. Θεσσαλονίκη: Εκδόσεις Τζιόλα, 2016.
Additional Material
Course website



DISCRETE MATHEMATICS (ΠΛ0108-3) up.gif
Petridou Sofia    Stephanides George     

General Competences
The study of discrete objects and relationships among them. The study and implementation of computational methods in finite algebraic structures.
Course Content
1. Logic and proof: Statements and Logic - Predicates and quantifiers - Proof techniques - Mathematical induction.
2. Combinatorics: sum and product rules - rules of combinatorics - binomial coefficients.
3. Discrete probability: events and probabilities - conditional probability - random variables and expected values - covariance and correlation.
4. Relations - Operations - Structures: binary relations - representation of binary relations - properties of relations - equivalence relations and partial orders - binary operations - internal operation and equivalence classes - structures - isomorphisms.
5. Modular arithmetic - Cyclic groups: Divisibility - Euclidean algorithm - residues - "exponents" - cyclic groups - computations with big integers.
6. Rings and finite fields: the problem of generators and discrete logarithm - polynomial arithmetic and applications - Algorithms for finite fields - applications.
7. Recursion: sequences - recurrence relations - computation of sums and products.
Assessment
Written Final examination 100%
Course Bibliography
(One of the following):
• Στεφανίδης, Γεώργιος Χρ. Διακριτά μαθηματικά. Θεσσαλονίκη: Ζυγός, 2015.
• Shoup, Victor. Μια υπολογιστική εισαγωγή στη θεωρία αριθμών και την άλγεβρα. Αθήνα: Κλειδάριθμος, 2007.
• Epp, Susanna S. Διακριτά μαθηματικά με εφαρμογές. 2η βελτ. έκδ. Αθήνα: Κλειδάριθμος, 2010.
Additional Material



FINANCIAL ACCOUNTING (ΠΛ0502-1) up.gif
Stavropoulos Antonios    Vazakidis Athanasios     

General Competences
This course is aiming to:Enable students familiar and aware of the essentials of accounting.Enable students capable of posting entries belonged to the general or financial accounting (Journal, general ledger, balance sheets).Enable students aware of posting entries in the accounting books of a company which is classified in the second class (B' class) of book keeping using the manuscript method, and at the time capable for the accounting estimation of the value added tax (VAT).Enable students capable of posting entries in accounting books of a company which is classified in the second class of book keeping (B' class) by the use of computer' software.
Course Content
Essentials of accounting, general accepted accounting principles (G.A.A.P), and accounting branches. Accounting recording methods: "Aplografiko" and Double entry system. Analysis of the Greek general chart of accounts. Valuation of inventories. Fixed assets and their depreciation. Development and analysis of the financial statements (Journal entries, general ledger, trial balance, balance sheet, profit and losses statement). Adjustments. Accounting process for the measuring, reporting and announcement of the financial annual results. Book keeping of the first and second classes of accounting classification, using manuscript method and by the use of software. Exercises related to the different classes of book keeping (mainly B' and C'). Questions and answers related to the subject of code for books and records as well as value added tax and intersection of tax records.
Assessment
Laboratory exams 35%
Final writing exams 65%
Course Bibliography
(One of the following) :
• Σταυρόπουλος, Αντώνιος, Αθανάσιος Βαζακίδης και Σταύρος Τσόπογλου. Χρηματοοικονομική Λογιστική, Λογιστικό Σχέδιο. 2η έκδ. συμπληρωμένη και βελτ. Θεσσαλονίκη, 2010.
• Καραγιάννης, Δημήτρης Ι, Ιωάννης Δ Καραγιάννης και Αικατερίνη Δ Καραγιάννη. Παραδείγματα εφαρμογής και ανάλυσης του γενικού λογιστικού σχεδίου: στην πράξη. 9η έκδ., ενημερωμένη με τους τελευταίους νόμους. Θεσσαλονίκη, 2016.
Additional Material



INTRODUCTION TO ALGORITHM ANALYSIS (ΠΛ0509-2) up.gif
Satratzemi Maria     

General Competences
By the completion of the course the student will be acquainted with the basic mathematical concepts for algorithm analysis, will be able to compare the theoretical complexities of the algorithms and apply the basic methodology in developing efficient algorithms.
Course Content
Theory:
1. The concepts of computational problem and algorithm
2. Asymptotic analysis (The asymptotic symbols Ο, Θ, Ω, ο and ω
3. Properties of the asymptotic symbols
4. The value of Algorithm analysis)
5. The concept of algorithm complexity (Worst, best and average case
6. Homogeneous and non homogeneous algorithms)
7. Computational models
8. Analysis of iterative algorithms
9. Analysis of recursive and divide and conquer algorithms
10. Analysis of greedy algorithms, Analysis of dynamic programming algorithms
11. Graph algorithms (Breath first search, Depth first search, Topological order, Bipartite graphs, connectivity)
Laboratory:
12. Algorithm programming and computational studies to evaluate the practical complexity of algorithms.
Assessment
Written Final examination 100%
Course Bibliography
(One of the following) :
• Cormen, Thomas H. Εισαγωγή στους αλγορίθμους. Επιμ. Γεώργιος Φρ Γεωργακόπουλος, και συν. Μεταφρ. Ιωάννης Παπαδόγγονας. 1η έκδ. σε ενιαίο τόμο. Ηράκλειο: Πανεπιστημιακές Εκδόσεις Κρήτης, 2012.
• Παπαρρίζος, Κωνσταντίνος. Ανάλυση και σχεδίαση αλγορίθμων. Θεσσαλονίκη: Εκδόσεις Τζιόλα, 2010.
• Kleinberg, Jon και Éva Tardos. Σχεδιασμός αλγορίθμων. Αθήνα: Εκδόσεις Κλειδάριθμος, 2008.
• Levitin, Anany. Ανάλυση και σχεδίαση αλγορίθμων. Επιμ. Μάνος Ρουμελιώτης. Μεταφρ. Ευθύμιος Κότσιαλος. Θεσσαλονίκη: Εκδόσεις Τζιόλα, 2008.
Additional Material
Course website



STATISTICS I (ΠΛ0104) up.gif
Papanastasiou Demetrios     

General Competences
The course is an introduction to the basics of the probability theory. The aim is to prepare the student to follow other subjects that require relative knowledge, such as statistics, operations research, etc. Calculations are implemented using the free source software R.
Course Content
1. Data (introduction to R, entry and presentation of data).
2. Modeling uncertainty.
3. Probability: Definitions, basic rules.
4. Random Variable: Discrete, continuous, expected value, conditional rv, independence.
5. Basic theoretical distributions.
6. Basic inequalities, LLN, CLT.
7. Stochastic Process: Definitions, Poisson process, Markov chain.
Assessment
Written examination, a four (4) question paper, very similar to those taught in the class.
Course Bibliography
(One of the following) :
• Sheldon Ross. Βασικές Αρχές Θεωρίας Πιθανοτήτων,. Εκδ.8η Αμερικανική. Εκδόσεις Κλειδάριθμος ΕΠΕ, 2011
• Μπερτσεκάς Δ., Τσιτσικλής Γ..Εισαγωγή στις Πιθανότητες. Εκδ.1η έκδ. ΤΖΙΟΛΑ, 2010
Additional Material
Instructor's notes and slides, see http://compus.uom.gr/INF267