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This package is designed for students, researchers, analysts, founders, and professionals who want to understand and build practical AI systems using large language models and AI agents. We will work together to understand how LLM-based systems work beyond simple prompting. Depending on your goals, we can cover LLM fundamentals, prompt design, structured outputs, tool use, agentic workflows, planning, memory, evaluation, reliability, and practical system design. The focus is on helping you understand how to design useful AI workflows for real projects, research, business tasks, or product ideas. We can work conceptually, hands-on, or directly on your own idea or prototype.
A clear understanding of how LLMs and AI agents work A practical framework for designing LLM-powered workflows Guidance on prompt design, structured outputs, tool use, and agentic workflows Support with building or planning your own AI assistant, automation, or prototype Feedback on your AI project, product idea, research workflow, or technical design A clear next-step plan for learning, implementation, or deployment
Schedule a call with a Leland team member who can help you explore your options.
Schedule a call
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Jamal also coaches for Data Science and AI for Data & Analytics. View all.

Joined February 2026
AI Researcher at Cambridge | ML & Neuroimaging Expert
I'm a researcher at the University of Cambridge working on AI for neuroimaging. I have a PhD in Computational Neuroscience and nearly 10 years of experience building ML models across healthcare, energy, and tech. I've worked with everything from deep learning and computer vision to time-series forecasting and fraud detection. I can help you understand AI concepts, build models, or solve data science problems in a practical way.
6h of coaching