
Semester 1
Compulsory courses |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-0120 | English Language 1 | 3 | 0 | 1 |
321-1500 | Discrete Mathematics I | 3 | 2 | 5 |
321-1200 | Structured Programming | 3 | 4 | 5 |
321-1400 | Introduction to Computer Science and Communications | 3 | 0 | 5 |
321-2000 | Logic Design | 3 | 2 | 5 |
321-1100 | Mathematics for Engineers I | 3 | 2 | 5 |
321-2400 | Probability and Statistics | 3 | 2 | 5 |
Semester 2
Compulsory courses |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-0130 | English Language 2 | 3 | 0 | 2 |
321-2100 | Object-Oriented Programming I | 3 | 2 | 5 |
321-2450 | Discrete Mathematics II | 3 | 2 | 5 |
321-3300 | Computer Communications | 3 | 2 | 5 |
321-2550 | Circuit Theory | 3 | 2 | 5 |
321-3150 | Mathematics for Engineers II | 3 | 2 | 5 |
321-2050 | Physics | 3 | 2 | 5 |
Semester 3
Compulsory courses |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-0140 | English Language 3 | 3 | 0 | 3 |
321-3650 | Object-Oriented Programming II | 3 | 2 | 5 |
321-3350 | Computer Architecture | 3 | 2 | 5 |
321-3000 | Data Structures | 3 | 2 | 5 |
321-5500 | Signals and Systems | 3 | 2 | 5 |
321-3750 | Stochastic Procedures | 3 | 2 | 5 |
321-8950 | Digital Innovation & Entrepreneurship | 3 | 0 | 5 |
Semester 4
Compulsory courses |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-4200 | Algorithms and Complexity | 3 | 2 | 5 |
321-3100 | Information Systems Analysis and Design | 3 | 2 | 5 |
321-3200 | Databases I | 3 | 2 | 5 |
321-7900 | Electronics | 3 | 2 | 5 |
321-4100 | Operating Systems | 3 | 2 | 5 |
321-4120 | Advanced Topics of Programming Languages | 3 | 2 | 5 |
Semester 5
Compulsory courses |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-3700 | Databases II | 3 | 2 | 5 |
321-6450 | Computer Networks | 3 | 2 | 5 |
321-6700 | Theory of Computation | 3 | 0 | 5 |
321-2300 | Operation of Business & Information Systems | 3 | 2 | 5 |
321-4000 | Software Engineering | 3 | 2 | 5 |
321-3450 | Telecommunications | 3 | 2 | 5 |
Semester 6
Compulsory courses |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-3400 | Information and Communication Systems Security | 3 | 2 | 5 |
321-7950 | Distributed Systems | 3 | 2 | 5 |
321-5200 | Information Law | 3 | 0 | 5 |
321-6500 | Information Systems Management | 3 | 0 | 5 |
321-88100 | Internet Programming | 3 | 2 | 5 |
321-3600 | Artificial Intelligence | 3 | 2 | 5 |
Semester 7
Cycle 1: Information and Communication Systems Security and Privacy |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-9700 | Computer Network Security and Privacy Enhancing Technologies | 3 | 0 | 5 |
321-5750 | Privacy and Data Protection Law | 3 | 0 | 5 |
Cycle 2: Information Systems and Entrepreneurship |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-8100 | Project Management | 3 | 2 | 5 |
321-7650 | Systems Theory | 3 | 0 | 5 |
321-5150 | Information Systems Analysis and Design Methodologies | 3 | 0 | 5 |
Cycle 3: Computer and Telecommunication Technologies |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-7050 | Digital Systems Design | 3 | 2 | 5 |
321-10300 | Digital Communications | 3 | 2 | 5 |
Cycle 4: Communication Systems and Networks |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-8350 | Network Management | 3 | 0 | 5 |
321-7000 | Performance Evaluation and Simulation of Computer Systems and Networks | 3 | 2 | 5 |
Cycle 5: Information Management and Intelligent Systems |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-7750 | Introduction to Robotics | 3 | 2 | 5 |
321-6100 | Natural Language Processing | 3 | 2 | 5 |
Cycle 6: Computer Science Foundations |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-8600 | Information Theory | 3 | 0 | 5 |
Semester 8
Cycle 1: Information and Communication Systems Security and Privacy |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-10750 | Mobile and Wireless Networks Security | 3 | 0 | 5 |
321-6000 | Security on Physical Layer | 3 | 0 | 5 |
321-8050 | Cryptography | 3 | 0 | 5 |
Cycle 2: Information Systems and Entrepreneurship |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-5600 | Human - Computer Interaction and Web Applications | 3 | 2 | 5 |
321-8500 | Decision Support Systems | 3 | 2 | 5 |
321-11100 | Electronic Government Technologies and Applications | 3 | 0 | 5 |
Cycle 3: Computer and Telecommunication Technologies |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-7800 | Wireless Communications | 3 | 2 | 5 |
321-8750 | Introduction to VLSI | 3 | 2 | 5 |
321-7850 | Microprocessors | 3 | 2 | 5 |
321-9350 | Digital Image Processing | 3 | 2 | 5 |
Cycle 4: Communication Systems and Networks |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-7250 | Mobile Communication Networks | 3 | 2 | 5 |
321-6250 | Internet Protocols and Architectures | 3 | 0 | 5 |
321-11000 | Cloud Technologies | 3 | 2 | 5 |
Cycle 5: Information Management and Intelligent Systems |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-10200 | Information Retrieval | 3 | 0 | 5 |
321-9250 | Data Mining | 3 | 2 | 5 |
321-6050 | Intelligent Recommender Systems | 3 | 0 | 5 |
321-6600 | Advanced Robotics | 3 | 2 | 5 |
Cycle 6: Computer Science Foundations |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-99000 | Numerical Analysis | 3 | 0 | 5 |
321-8000 | Game Theory | 3 | 0 | 5 |
321-9850 | Mathematical Modeling | 3 | 0 | 5 |
321-9000 | Forecasting Techniques | 3 | 0 | 5 |
Optional courses |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-2630 | 3 | 2 | 5 | |
321-7600 | 3 | 0 | 5 |
Semester 9
Cycle 1: Information and Communication Systems Security and Privacy |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-99100 | Regulatory and Social Issues in Information Society | 3 | 0 | 5 |
Cycle 2: Information Systems and Entrepreneurship |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-5400 | Information Systems Strategy and Investment | 3 | 0 | 5 |
321-8200 | E-Commerce Technologies and Applications | 3 | 0 | 5 |
Cycle 3: Computer and Telecommunication Technologies |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-3250 | Internet of Things | 3 | 2 | 5 |
321-10650 | Satellite Communications | 3 | 2 | 5 |
321-8650 | Optoelectronics | 3 | 2 | 5 |
321-6550 | Multimedia | 3 | 2 | 5 |
Cycle 4: Communication Systems and Networks |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-9400 | Sensor Networks | 3 | 2 | 5 |
321-9120 | Design and Development of Mobile Computing applications | 3 | 2 | 5 |
Cycle 5: Information Management and Intelligent Systems |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-9450 | Applied Topics in Data Structures and Databases | 3 | 0 | 5 |
321-7400 | Knowledge Engineering and Knowledge Systems | 3 | 0 | 5 |
Cycle 6: Computer Science Foundations |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-10000 | Algorithms and Combinatorial Optimization | 3 | 0 | 5 |
Optional courses |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-2600 | 3 | 0 | 5 |
Semester 10
Compulsory courses |
||||
---|---|---|---|---|
Lesson Code | Title | H(T) | H(L) | ECTS |
321-7100 | Diploma Thesis | 30 |
Title | Forecasting Techniques |
---|---|
Lesson Code | 321-9000 |
Semester | 8 |
ECTS | 5 |
Hours (Theory) | 3 |
Hours (Lab) | 0 |
Faculty | ICS Eng. Department |
Syllabus
Time Series Data, Correlation, Time Series Analysis, Forecasting Strategies, Demanding forecasting, Basic Stochastic Models, Characteristics of Time Series, Definition of Prediction, Prediction Fields and Applications, Categories of Predictive Paths, Predictive Performance Measures, Basic statistical concepts, Statistical Methods in the Frequency Domain, Basic Statistical Analysis and prediction models, Statistical measures of accuracy in Predictions, Graphical Data Representation, Parameter Estimation, Growth Rate, Normalization Terms, classical Decomposition methods, Stationary Models, Non-stationary Models, Introduction to Spectral Analysis and Filtering, State Space Models, Multivariate Models, Confidence Space, Business Forecast Process, Mobile Intermediate Terms for Exposure, Methods of Exposure Smoothing , Seasonal Smoothing), Selection of smoothing model, Introduction to ARIMA Timeline Forecasting Models (Prediction Limits). Time Series Regression and Exploratory Data Analysis (simple linear and multiple regression), Binary Categorization (such as Support Vector Machines and Multiple Layer Perceptron) and Machine Learning applications as well as Clustering techniques (such as Neural Networks, k-Nearest Neighbours, Expectation Maximization).
Learning Outcomes
The aim of the course is to enable students to understand the basic principles of time series analysis, strategies prediction, basic Statistical Analysis and Performance measures in forecasting, Time Series Regression and Exploratory Data Analysis (simple linear and multiple regression), Binary Categorization (such as Support Vector Machines and Multiple Layer Perceptron) and Machine Learning applications as well as Clustering techniques (such as Neural Networks, k-Nearest Neighbours, Expectation Maximization). By concluding the course, students are able to:
- analyze and adapt data in original form
- estimate the parameters and compute the mobile average of data based on basic Statistic methodology
- distinguish the quality of characteristics in time series data
- apply forecasting methods analyzing and designing data required for prediction
- develop deep knowledge in Time Series Regression and Exploratory Data Analysis
- understand the content / role of forecasting based on basic prediction models
- identify, describe and distinguish the main methods and prediction techniques in Binary Classification as well as clustering.
- have comprehensive knowledge in methodology and application of forecasting techniques
Prerequisite Courses
Not required.
Basic Textbooks
- Μέθοδοι Προβλέψεων και Ανάλυσης Αποφάσεων, Αγιακλογλου Ν. Χρήστος, Οικονόμου Γιώργος, Εκδόσεις Μπένου, 2014.
- Φ. Πετρόπουλος & Β. Ασημακόπουλος, Επιχειρησιακές Προβλέψεις, Εκδόσεις Συμμετρία, 2011.
- Σύγχρονες Μέθοδοι Ανάλυσης Χρονολογικών Σειρών". Συγγραφέας: Δημέλη Σοφία. Εκδόσεις: Οικονομικό Πανεπιστήμιο Αθηνών. Εταιρεία Ο.Π.Α. Α.Ε.
Teaching and Learning Methods
Lectures, resolving exercises, Laboratory Exercises.
Activity | Semester workload |
---|---|
Lectures | 39 hours |
Exercises | 45 hours |
Personal study | 38 hours |
Final exams | 3 hours |
Course total | 125 hours (5 ECTS) |
Student Performance Evaluation
Personal assignments and pair or group assignments, lab practice, regular short assessments in the form of a quiz test, final examination.
Language of Instruction and Examinations
Delivery Mode
Face-to-face