€ 1.800,00

Plus 20% VAT
plus shipping

Applied Data Science and Artificial Intelligence for Executives

€ 1.800,00

Plus 20% VAT
plus shipping

Note for groups: If you are buying this product for multiple participants, you will be able to assign licenses after completing the order. Please select “Group” and the number of seats you require.



  • 40-hours hybrid training on applied data science and artificial intelligence for executives
  • Focus on acquiring expertise in building and managing data science teams and fostering data-driven organisations under the guidance of the lecturer
  • Level: Intermediate
  • Format: Blended

This immersive training programme equips executives and professionals with the knowledge and practical skills to harness the power of data science, artificial intelligence, and digital transformation in their organisations.

Through this training, you will gain a strong foundation in data science, AI, and machine learning while exploring statistical techniques, ethical considerations, and strategies for building a data-driven culture. You will learn how to effectively collect and manage data, navigate big data systems, and apply industry frameworks like CRISP-DM.

The in-person sessions in Vienna will help you to translate insights into action with hands-on workshops, collaborative data strategy exercises, and real-world AI applications. You will work on generative AI, business case discussions, and interactive challenges while expanding your professional network.

This programme is designed for professionals looking to bridge the gap between theory and practice, leveraging data to drive strategic decision-making and innovation in their industries.

Key facts about the training: 

  • 40 hours training course
  • 3 online sessions (8 hours/day)
  • 2 in-person sessions in Vienna (8 hours per day)
  • Language: English
  • Participants will receive a Certificate of Attendance upon completion of the training

Learning outcomes: 

  • Develop the ability to define complex data science and applied AI problems.
  • Gain skills in identifying and collecting essential data sources for analysis.
  • Understand the role of AI tools in automating and enhancing business processes.
  • Acquire expertise in building and managing data science teams and fostering data-driven organizations.

Read more about the course on TU Wien's website here.

 

Online Days (14.05.2025 – 16.05.2025)

Day 1 – 14.05.2025: Unlocking the Power of Data in Your Organisation

  • Demystifying Data Science: Unveiling the true potential of data science with industry applications; Busting common myths
  • Mastering Statistics for Data-Driven Decisions: Key analysis techniques; Measuring success through real-world examples.
  • AI and Machine Learning Unleashed: Navigating ML approaches, choosing the right one; Understanding neural networks in simple terms.
  • Building a Data-Driven Success Culture: Elements of a data-centric organisation; Insights on assembling elite data science teams; Interactive case studies.
  • Navigating AI Ethics: Exploring regulatory landscapes; What the EU AI Act means for your business

Day 2 – 15.05.2025: The Art of Data Collection: Getting It Right

  • Taming Big Data: Systems, Warehousing, and More: From database fundamentals to big data applications; Practical insights for real-world use.
  • Creative Data Collection Techniques: Mapping the data landscape; Harvesting insights from sensors and humans; Essentials of web scraping.
  • Interactive Challenge: Identify data sources in your organisation; Classifying data types and ensuring quality control across datasets.

Day 3 – 16.05.2025: Mastering the Data Science Lifecycle

  • The Data Science Lifecycle in Action: From business understanding to data normalisation; Streamlining processes with CRISP-DM.
  • Group Synthesis Exercise: Putting CRISP-DM elements together; Exploring algorithm types and deployment strategies.
  • Innovative Problem Solving with the Data Product Canvas: Apply practical frameworks to tackle organisational issues.

In-Person Days (17.06.2025 – 18.06.2025)

Day 4 – 17.06.2025: Transforming Ideas into Impactful Data Projects

  • Collaborative Data Canvas Workshop: Strategising data sources and methodologies collaboratively; Co-creating solutions with peers.
  • Generative AI: The New Frontier in Data Processing: Dive into AI tools like OpenAI; Discover their transformative potential.
  • Strategic Group Planning: Utilising your Data Canvas to design effective CRISP-DM strategies for targeted challenges.

Day 5 – 18.06.2025: Expand Your Network, Exchange of Ideas

  • Tailored Business Dialogue: Engaging discussions focused on company-specific contexts.
  • Interactive Data Science Challenge: Hands-on prompt engineering for cutting-edge text analysis.
  • Collaborative Showcases and Networking: Present group exercise outcomes in dynamic sessions; Connect with industry peers.

This workshop is aimed at executives and professionals who want to engage with the latest developments in artificial intelligence and digital transformation. The course provides in-depth knowledge in data science, artificial intelligence, and digital transformation, drawing on our experience with data-driven projects in industrial settings. The goal of the workshop is to learn how to practically apply theoretical concepts.

3 Online Days:

  • 14.05.2025
  • 15.05.2025
  • 16.05.2025

2 In-Person Days:

  • 17.06.2025
  • 18.06.2025

This training is available for individuals and groups of minimum 10 and maximum 25 participants.

The course fee contains course documentation. Upon completion of the hybrid training, participants will receive a Certificate of attendance.

The training is held by Dipl.-Ing. Andreas Steiner, BSc, Institute of Management Sciences, TU Wien.

Education:

  • Since 2023: PHD Candidate, Research Unit of PIM
  • Since 2023: Master Data Science, TU Wien
  • 2016-2023: Mechanical Engineering – Management, TU Wien

Professional experience:

  • Since 2018: Data Scientist, Aircraft Services, Celairion GmbH
  • Since 2023: Praedoc, PIM, TU Wien

Research areas:

  • Data-Driven Maintenance Strategies | IoT Integration for Real-Time Analysis
  • Predictive Analytics for Maintenance
  • Visual Computing and Neural Networks in Machine Learning

Learn more about the Research Unit Production and Maintenance Management (PIM) & Chair of Data-driven Maintenance Management.

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