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Lecture Plan

First year

Semester 1

COURSES ECTS Hours Lectures* Practice** Type
Innovative project 1 5 150 2 8 Obligatory
Negotiation and conflict resolution 4 45 2 1 Obligatory
Data Preparation 6 60 2 2 Obligatory
Data Warehouses and Business Intelligence 6 60 2 2 Obligatory
Introduction to Data Science 3 45 1 2 Obligatory
Data Analysis: Statistical Modeling and Computation in Applications 5 60 2 2 MITx*
Disruptive technologies 6 60 2 2 Elective
Machine Learning with Python: from Linear Models to Deep Learning 6 75 2 3 MITx*
Probability - The Science of Uncertainty and Data 5 60 2 2 MITx*
Managing Quality in IT Projects 6 60 2 2 Elective

Semester 2

COURSES ECTS Hours Lectures* Practice** Type
Innovative project 2 6 15 0.4 0.6 Obligatory
Creativity and Critical Thinking 3 45 2 1 Obligatory
Quantitative methods of data processing 6 45 1 2 Obligatory
Machine Learning Methods 4 45 1 2 Obligatory
Security, privacy and ethics of digital data 5 45 1 2 Obligatory
Capstone Exam in Statistics and Data Science 8 40 0 2.6 MITx*
Data Analysis in Social Science 5 60 2 2 MITx*
Fundamentals of Statistics 6 75 2 3 MITx*
Internet of things 6 60 2 2 Elective
Management of Innovation 6 45 1 2 Elective

Second year

Semester 3

COURSES ECTS Hours Lectures* Practice** Type
Analytical techniques based on large data sets 6 60 2 2 Obligatory
Innovative project 3 6 15 0.4 0.6 Obligatory
Advanced Machine Learning Methods 6 45 1 2 Obligatory
Management of Information Services 3 45 2 1 Obligatory
Visualisation and analytical software tools 3 45 1 2 Obligatory
Cloud Analysis 6 60 2 2 Elective
Structured Analytical Techniques 6 60 2 2 Elective

Semester 4

COURSES ECTS Hours Lectures* Practice** Type
Affective Computing 6 60 2 2 Obligatory
Social Network Analysis 6 60 2 2 Obligatory
Graduation Thesis 18 0 0 0 Obligatory
*The MIT Lecture Plan is executed independently of the lecture plan of the Algebra University College.

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