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Generative AI and Symbolic Reasoning

The course "Generative AI" provides an in-depth exploration of generative AI, focusing on both the theory and practical applications of transformers, large language models, and symbolic AI. By completing the course, learners will gain a comprehensive understanding of how these technologies work and how they can be integrated to solve complex problems and generate new content. Through real-world case studies, students will analyze the strengths and weaknesses of generative AI systems, preparing them for the challenges and opportunities they will face in AI leadership roles. What sets this course apart is its focus on the intersection of symbolic AI and generative processes, providing insights into how these models can be enhanced for explainability and control. By examining both stochastic and symbolic AI, learners will understand how these approaches complement each other in creating responsible, ethical, and sustainable AI systems. Whether you're looking to lead AI projects, integrate cutting-edge AI tools, or understand their broader implications, this course equips you with the skills needed to navigate the evolving landscape of generative AI.
Duration 5 Months
Institution Johns Hopkins University
Format Online

Eligibility Criteria

school

Academic Foundation

A recognized Bachelor’s degree or high school equivalent required for admission into Johns Hopkins University.

language

Language Proficiency

English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.

Detailed Fees Breakdown

Base Tuition Fee $195
Total Est. Investment $195

Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.

Academic Trajectory

Program Outcome

Graduates of the Generative AI and Symbolic Reasoning program at Johns Hopkins University are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.

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