Master’s program in AI Engineering

Artificial intelligence is considered to be one of the key concepts of digitalization that will affect many areas of our daily lives. People are already addressed by intelligent bots on the World Wide Web, cars drive themselves, gamers play against smart computer opponents in automatically generated artificial worlds, proteins are folded on the computer, doctors are supported in image analysis by software that has learned from thousands of images ... far-reaching fields of application are in prospect for the future, because AI algorithms and their interaction with the environment are essential components of the development of future software and hardware systems. Therefore, an analysis of the FHTW has shown that a strongly growing demand for experts in Artifical Intelligence can also be expected on the job market.

AI Engineering

Students choose one of two specializations within the AI  Engineering program:

  • AI Technologies
  • Game Engineering
  • Specialization 1: Knowledge Representation & Symbolic AI
    Fundamentals of knowledge representation, propositional and predicate logic, methods of knowledge representation and extraction, rule-based systems and knowledge-based systems, declarative problem solving, search methods, heuristics and evolutionary algorithms.
     
  • Specialization 2: Reinforcement Learning
    Fundamentals of reinforcement learning (uninformed combinatorial search, value iteration, dynamic programming), intelligent software and hardware agents, Markov decision problems, reinforcement learning methods, AlphaZero, Swarm Intelligence
     
  • Specialization 3: Multimedia AI
    Fundamentals of multimedia data, data mining and knowledge discovery in databases, semantic web and open data, multimedia analytics, text classification, entity recognition and sentiment analysis, Big Data infrastructures for multimedia and time series data, sensor data analytics
     
  • Specialization 4: Deep Learning Engineering
    Fundamentals of Artificial Neural Networks, computing infrastructure and efficient programming of deep learning algorithms, deep learning software tools and libraries, recurrent neural networks and architectures for time-dependent data, convolutional neural networks and architectures for image data, AI-generated content and deep fakes with GPT-2
  • Specialization 1: Advanced Game Design
    History of games & definitions, formal elements of games, game analysis & critique, the importance of game rules, level design vs. game design, enemy design, map design, technological constraints, balancing, progression, user experience - UX, narration, modding, user-generated content, testing, creating high-concepts (where does the idea come from?), evaluating own and other people's game design high-concepts, review and selection of a game concept for the development project.
     
  • Specialization 2: Content Creation and Design Aspects
    Creation of a storyboard, creation of a moodboard, creation and editing of 2D vector graphics, creation and editing of 2D pixel graphics, 3D modeling tools, procedural content generation, polygon modeling, UV layouts, basics of rendering, animation, rigging, basics of sound creation, midi, synthesizer, tracker, etc., acoustics, miking, recording, mixing, mastering
     
  • Specialization 3: Multiplayer and Realtime Networking
    Communication paradigms, client/server, peer to peer, distributed computing, grid computing, cloud gaming and streaming protocols, traffic analysis; latency and jitter compensation, network security, application-level proxies, gameworld clustering, anticheat methods, load balancing for server clusters, test and quality assurance methods for multiplayer games
     
  • Specialization 4: Multiplatform Development
    Mobile-specific topics (e.g. development environment, design, input), comparison of programming techniques on different operating systems and devices, cross-platform and multiplatform toolchain, web app & hybrid app development, OpenGL ES on Android, Metal on iOS, game engine optimization for mobile platforms, console architecture, differences between development for Windows and consoles, pipeline hazards, restricted pointers, data-oriented design, measurement and optimization

Graduates design, implement and integrate AI based systems and AI algorithms based on latest concepts, technologies, programming languages and tools. Machine learning, visual computing and mixed reality, interactive AI, processing of speech and multimedia data or intelligent control of virtual characters are some of the topics in their world. Design and development of support systems, simulation applications or computer games are just examples of fields of activity for an AI engineer. Graduates are in demand as high-quality software engineers, game developers, DevOps engineers or smart systems engineers in practically all industries.

Apply now

Program Director

Priv.-Doz. DI(FH) Dr. Bernhard Knapp

Program Director Master AI Engineering
+43 1 333 40 77 - 4588
Call E-Mail

Administrative Assistant

Wilson Carla

Carla Wilson, BA

Assistant Information Systems Management
T.: +43 1 333 40 77-8356
Call E-Mail