Intelligent technologies
Course: Informatics
Structural unit: Faculty of Computer Science and Cybernetics
            Title
        
        
            Intelligent technologies
        
    
            Code
        
        
            ДВС.1.03
        
    
            Module type 
        
        
            Обов’язкова дисципліна для ОП
        
    
            Educational cycle
        
        
            Second
        
    
            Year of study when the component is delivered
        
        
            2021/2022
        
    
            Semester/trimester when the component is delivered
        
        
            4 Semester
        
    
            Number of ECTS credits allocated
        
        
            4
        
    
            Learning outcomes
        
        
            LO18.1. To know and apply modern hardware-software and computing tools, technologies and software solutions for the effective analysing of the industrial software development problems.
        
    
            Form of study
        
        
            Prerequisites and co-requisites
        
        
            Have knowledge of modern programming languages and tools for developing and designing programs for solving scientific and applied problems.
Have basic skills in compiling and analyzing algorithms and programming in one of the languages: Python, Java, C #, C ++.
        
    
            Course content
        
        
            The aim of the course is to acquaint students with modern technologies that used in development in the field of artificial intelligence. Introduction to bot creation technologies using Microsoft's Bot Framework technology. Introduction to the set of technologies Microsoft Cognitive Services.
        
    
            Recommended or required reading and other learning resources/tools
        
        
            1. Stephen Marsland. Machine Learning: An Algorithmic Perspective, 452 р., 2015.
2. Christopher M Bishop. Pattern recognition. Machine Learning, 128 p., 2006.
3. Ethem Alpaydin. Introduction To Machine Learning, 584 p., 2009.
4. Programming the Microsoft Bot Framework: A Multiplatform Approach to Building Chatbots, 396 p., 2017
5. Gaddam Kishore. Building Bots with Microsoft Bot Framework, 424p, 2017
6. Machiraju, Srikanth, Modi, Ritesh. Developing Bots with Microsoft Bots Framework, 283p, 2018
        
    
            Planned learning activities and teaching methods
        
        
            Lectures, practical classes, independent work.
        
    
            Assessment methods and criteria
        
        
            Semester assessment:
1. Test 1 - 15 points / 9 points
2. Test work 2 - 15 points / 9 points;
3. Laboratory work 1 (project) - 30 points / 18 points
Final assessment in the form of an exam:
Maximum number of points that can be obtained by a student: 40 points.
Form of conducting: written work.
Types of tasks: 3 written tasks.
        
    
            Language of instruction
        
        
            Ukrainian language
        
    Lecturers
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