QUALIFICATIONS:

• Proven hands-on experience in AI, particularly in large language models and generative AI applications.
• Proficiency with Python, LangChain, and relevant AI frameworks and tools.
• Strong knowledge of RAG, embedding fine-tuning, and prompt engineering.
• Excellent communication skills, with the ability to convey complex technical concepts clearly.
• Prior teaching experience in AI or data science is highly desirable.
• Passionate about education and inspiring student growth.

• Design and develop an engaging AI curriculum, teaching students the core principles of generative AI, including Prompt Engineering, RAG, Embeddings, and Agents.
• Instruct students on building RAG systems and agents using LangChain, guiding them from prototyping to production deployment.
• Teach fine-tuning techniques for embeddings and Llama 3.1, with a focus on both cloud and on-premises deployment.
• Lead modules on LLM Ops, training students on effective monitoring and optimization for language model systems.
• Evaluate student projects, providing targeted feedback to foster progress and skill development.
• Stay updated on advancements in AI to ensure that course content and teaching methodologies remain relevant and effective.