Executive Development Programme in AI Technologies: Teaching Advancements
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โข Fundamentals of Artificial Intelligence (AI): This unit will cover the basics of AI, including its history, key concepts, and technologies. It will provide students with a solid foundation for understanding more advanced AI topics.
โข Machine Learning (ML): This unit will delve into the details of ML, a subset of AI that enables systems to learn and improve from experience without being explicitly programmed. It will cover various ML algorithms and techniques, such as supervised and unsupervised learning.
โข Deep Learning (DL): DL is a powerful ML technique that uses artificial neural networks with many layers. This unit will explore DL architectures, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), and their applications in areas like computer vision and natural language processing (NLP).
โข AI in Business: Applications and Use Cases: This unit will examine how AI can be used to drive business value and innovation. It will cover various AI applications, such as chatbots, predictive analytics, and recommendation systems, and explore how they can be used to improve customer engagement, operational efficiency, and decision-making.
โข Ethics and AI: As AI becomes more prevalent, it is essential to consider the ethical implications of its use. This unit will explore issues such as bias, privacy, transparency, and accountability in AI, and discuss strategies for mitigating these risks.
โข AI Strategy and Leadership: This unit will help students develop a strategic approach to AI implementation, including identifying opportunities for AI adoption, assessing risks and benefits, and creating a roadmap for AI integration. It will also cover leadership and team management in an AI-driven organization.
โข AI Technologies and Tools: This unit will provide an overview of the latest AI technologies and tools, such as TensorFlow, PyTorch, and Keras, and teach students how to use them to build and deploy AI applications. It will also cover data management and governance, and best practices for AI project management.
โข AI Research and Development (R
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Zugangsvoraussetzungen
- Grundlegendes Verstรคndnis des Themas
- Englischkenntnisse
- Computer- und Internetzugang
- Grundlegende Computerkenntnisse
- Engagement, den Kurs abzuschlieรen
Keine vorherigen formalen Qualifikationen erforderlich. Kurs fรผr Zugรคnglichkeit konzipiert.
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Dieser Kurs vermittelt praktisches Wissen und Fรคhigkeiten fรผr die berufliche Entwicklung. Er ist:
- Nicht von einer anerkannten Stelle akkreditiert
- Nicht von einer autorisierten Institution reguliert
- Ergรคnzend zu formalen Qualifikationen
Sie erhalten ein Abschlusszertifikat nach erfolgreichem Abschluss des Kurses.
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