AI and Deep Tech for Sustainable Innovation: ISO-Driven Approach

Purpose and Aims: This course is designed to equip learners with practical skills in AI-driven Deep Tech innovation, focusing on sustainability, ISO standards, and commercialization strategies. Participants will gain a deep understanding of how artificial intelligence (AI), robotics, and biotech drive technological transformation, while integrating ISO 56002 (Innovation Management), ISO 42001 (AI Governance), and ISO 9001 (Quality Management) to ensure structured and responsible innovation.

Target Audience:
Undergraduate-level learners (bachelor’s students) seeking to develop expertise in Deep Tech and AI applications.
Postgraduate-level learners (master’s students) looking to expand their knowledge in innovation management and sustainability within the Deep Tech sector.
Professionals and researchers interested in applying ISO standards to AI-driven innovation and sustainable technology development.

Learners will be able to:
Apply ISO 56002 and ISO 42001 principles to AI-driven Deep Tech innovation.
Integrate sustainability and ESG (Environmental, Social, Governance) principles into Deep Tech solutions.
Understand AI’s role in Deep Tech industries, including robotics, biotech, and quantum computing.
Develop scalable and quality-driven business models aligned with ISO 9001 (Quality Management).
Navigate funding opportunities, including EIT Deep Tech Talent programs, venture capital, and research grants.

The course consists of five modules:
Introduction to Deep Tech and AI – Overview of emerging technologies and their societal impact.
Innovation Management and ISO Standards – Applying structured methodologies to Deep Tech projects.
Sustainability and ESG in Deep Tech – Ensuring ethical AI and sustainable technology development.
Commercialization of Deep Tech Solutions – Scaling innovations through funding and industry partnerships.
Capstone Project – Developing a real-world AI-driven Deep Tech solution with expert feedback.

Teaching and Assessment:
Blended learning format: 30% live expert-led sessions, 40% self-paced online learning, and 30% group collaboration.
Assessment methods: quizzes (30%), applied assignments (30%), and a final capstone project (40%) evaluated by industry experts.
Interactive elements: case studies, guest lectures, and industry challenges ensure practical application.
Practical Information
Format: Online
Duration: 50 hours (including self-study)
Certification: EIT Deep Tech Talent Recognition
Final Outcome: Participants gain practical knowledge to apply AI, ISO standards, and sustainability frameworks to real-world Deep Tech challenges, positioning them for future roles in academia, industry, and entrepreneurship.