I’m launching a new training calendar and the first item on the list is an Artificial Intelligence & Machine Learning batch that must dive straight into advanced territory. The cohort already has solid foundations, so the sessions need to centre on Deep Learning—building, tuning and deploying neural-network models with real-world datasets. If you’re also comfortable branching into Reinforcement Learning or NLP later, that flexibility will be a plus for the longer roadmap, but the immediate priority is Deep Learning mastery. The sessions will be delivered live (online or hybrid can be arranged), and I’ll rely on you to: • Shape a clear, week-by-week syllabus covering CNNs, RNNs, transformers, optimisation tricks, model interpretability and MLOps basics using Python, TensorFlow or PyTorch • Provide concise slide decks, hands-on notebooks (Jupyter/Colab) and at least three graded mini-projects that mirror industry use-cases • Guide learners through code reviews and Q&A, then wrap up with a capstone evaluation and feedback report All teaching material must be original or properly licensed, and ready for hand-off at the end of the engagement. If the collaboration goes smoothly, I’ll slot you into upcoming tracks—Data Science, Cloud, DevOps, Blockchain and more—so consider this a springboard into a longer partnership. Let’s discuss your availability, the class schedule and any tooling preferences so we can lock the dates and get the curriculum finalised.