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“Generative AI for the Legal Profession” is a specialized program designed to bridge the gap between legal practice and AI technology. Participants will learn how GenAI, powered by large language models and prompt engineering, is transforming key areas like contract drafting, case law summarization, regulatory compliance, and client advisory services.
The program also covers risk management, AI ethics, and regulatory frameworks to ensure the safe and effective deployment of AI in legal workflows. Tools like ChatGPT (OpenAI), Harvey AI, Lexis+ AI, Kira Systems, and Prompt Engineering frameworks will be incorporated into case studies and hands-on exercises.
To equip legal professionals and scholars with knowledge and skills to harness Generative AI (GenAI) for document drafting, legal research, contract analysis, and risk management, while addressing ethical considerations and regulatory compliance.
Integrate generative AI into the daily practice of law
Equip legal professionals to harness AI for efficiency, accuracy, and innovation
Foster ethical and regulatory understanding in AI deployments
Support collaboration between legal and technical teams for AI integration
Prepare participants to lead AI transformation within their organizations
Practicing lawyers across all specializations
Legal researchers and academics
Legal technologists and AI consultants
Law students and paralegals interested in tech-driven practice
Compliance professionals and policy analysts
Apply AI to automate and enhance legal research, drafting, and compliance
Develop skills in prompt engineering for tailored legal tasks
Evaluate AI tools critically for security, fairness, and regulatory compliance
Prototype AI applications for real-world legal problems
Earn a certificate validating your expertise in Generative AI for legal practice
Take your research to the next level with NanoSchool.
Get published in a prestigious open-access journal.
Become part of an elite research community.
Connect with global researchers and mentors.
Worth ₹20,000 / $1,000 in academic value.
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PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.
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