LLMs and AI Agents: Build Practical AI Systems
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.
What's included
This package can be delivered through live 1:1 coaching sessions or asynchronous support, depending on your preferences, schedule, and learning style. Support typically includes conceptual explanation, practical examples, system design feedback, workflow planning, tool walkthroughs, and clear next steps. If you already have an AI idea, research workflow, automation task, or prototype, we can use that as the main focus. If not, I can provide simple examples and structured exercises. Before we begin, you can share your background, goals, and any relevant materials. Whether through live sessions or asynchronous feedback, you will receive personalized guidance, practical direction, and recommended resources or exercises when helpful.
- 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
Meet your expert
Jamal E.
AI Researcher at Cambridge | ML & Neuroimaging Expert
I am a computational neuroscientist and AI researcher with experience in machine learning, data science, and AI. Over the years, I have worked across academia and applied research, building quantitative models for complex real-world problems. I now help people navigate careers in AI, research, and data science, especially those trying to move between academia and industry. My approach is practical, honest, and tailored to each person’s strengths and goals
