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Generative AI
Master transformers, large language models, and symbolic AI. Build responsible generative systems with improved explainability and control.
Course Cost
₹ 2,699
Intermediate
Skill Level
12 Hours
Self-paced Video lessons
This comprehensive course explores the theory and practical applications of generative AI technologies, focusing on the intersection of transformers, large language models (LLMs), and symbolic reasoning. You'll develop a deep understanding of how foundation models like ChatGPT function, their capabilities, and methods for fine-tuning them for specific applications. The course examines both the strengths and limitations of these systems, including challenges like hallucinations and vulnerabilities. Beyond stochastic models, you'll explore how symbolic AI can enhance generative processes through formal methods, relational calculus, and query optimization. By integrating these approaches, you'll learn to create more explainable, controllable, and responsible AI solutions. The curriculum balances theoretical concepts with real-world case studies, preparing you to lead AI projects that address complex problems across various domains while considering ethical implications and sustainability.
English
English
What you'll learn
Understand the architecture and functionality of transformers and large language models
Distinguish between different types of foundation models and their specific capabilities
Implement fine-tuning techniques to customize large language models for specific applications
Apply image generation methods using generative AI technologies
Identify and mitigate challenges like hallucinations and vulnerabilities in language models
Integrate symbolic reasoning with stochastic AI to create more explainable systems
Implement formal methods and relational calculus in generative AI solutions
Develop strategies for responsible AI deployment that addresses ethical considerations
Skills you'll gain
This course includes:
7 Hours PreRecorded video
6 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
CREATED BY
PROVIDED BY
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 3 modules in this course
This course provides an in-depth exploration of generative AI, focusing on both theoretical foundations and practical applications. The curriculum begins with an introduction to the field, establishing the distinctions between stochastic AI, expert systems, and symbolic AI. The second module delves into transformers and large language models (LLMs), covering their architecture, capabilities, and applications. Students learn about foundation models, the mechanics behind ChatGPT's intelligence, specialized LLMs, fine-tuning techniques, and image generation methods. This module also addresses critical challenges including model competence assessment, hallucinations, and security vulnerabilities. The final module focuses on symbolic generative AI, exploring how rule-based approaches complement and enhance stochastic models. Topics include formal methods, relational calculus, query optimization, and data integration techniques. Throughout the course, emphasis is placed on developing responsible, explainable AI systems that balance innovation with ethical considerations and regulatory compliance.
Course Introduction
Module 1 · 9 Minutes to complete
Transformers and Large Language Models
Module 2 · 5 Hours to complete
Symbolic Generative AI
Module 3 · 6 Hours to complete
Fee Structure
Payment options
Financial Aid
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
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Students
17
Courses
Ian McCulloh is associated with Johns Hopkins University and is involved in courses related to artificial intelligence, probability, and statistical methods. His expertise likely spans AI project management, social media analytics, and foundational concepts in AI. He may also be involved in teaching or research related to neuroscience and social computing. If Ian McCulloh is a specific instructor, more detailed information about his background or specific courses taught would be needed to provide a more accurate description.
Frequently asked Questions
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