Role Overview
This position focuses on teaching adult learners how to apply artificial intelligence and machine learning to real operational challenges. Day to day, you will lead interactive sessions, demonstrate how to connect AI services with practical business workflows, and coach learners through building functional automation projects. Your work matters because it helps professionals move from theory to tangible implementations, enabling organisations to adopt AI responsibly and effectively.
Key Responsibilities
- Deliver engaging training sessions covering core AI concepts, machine learning pipelines, prompt engineering, and intelligent automation techniques.
- Demonstrate how to integrate APIs, no-code and low-code platforms, and AI services into realistic business scenarios.
- Facilitate practical labs where learners build and debug automation workflows, from data ingestion to model inference.
- Guide learners through portfolio projects that solve actual business problems, offering technical feedback and troubleshooting support.
- Assess learner progress through assignments, hands-on exercises, and project reviews, adjusting delivery to different skill levels.
- Regularly refresh course content to align with evolving AI tools, industry best practices, and responsible-use guidelines.
- Collaborate with other trainers to develop case studies, data sets, and live demonstrations that keep training relevant and engaging.
Requirements & Qualifications
- Degree or diploma in Computer Science, Data Science, Artificial Intelligence, or a closely related discipline.
- Hands-on experience with Python, including machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch.
- Working knowledge of API integration, RESTful services, and automation tools like Zapier, Power Automate, or n8n.
- Solid understanding of data preparation, feature engineering, model evaluation, and generative AI concepts.
- Familiarity with responsible AI principles, including bias awareness, explainability, and data privacy considerations.
- Prior experience teaching, mentoring, or presenting technical topics to non-technical audiences is a plus.
- A portfolio or demonstrated track record of AI, machine learning, or automation projects is required.
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