Exploring the Depths of Large Language Models in Generative AI
Generative AI
| Intermediate
- 14 videos | 1h 48m 11s
- Includes Assessment
- Earns a Badge
It's important to understand the intricacies of large language models (LLMs) and their pivotal role in the realm of generative artificial intelligence (AI). This course offers an exploration of the architecture, training, and fine-tuning of LLMs. Begin by learning how to implement various techniques tailored for specific generative tasks and delve into the integration of multimodal AI approaches, combining text and visuals. This course not only stresses the technical aspects but also confronts the ethical dilemmas, spotlighting bias and fairness in AI applications. Next, through a blend of theory, demonstrations, and emerging research discussions, explore how the full potential of LLMs can be harnessed and how to prepare for the next wave of AI innovations.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this course
Analyze the architectural components of large language models (llms) and their role in generative artificial intelligence (ai)
Evaluate the impact of different training approaches on the performance and generative capabilities of large language models
Implement techniques to fine-tune large language models for specific generative tasks
Analyze the challenges and limitations of large language models in generative ai applications
Compare and contrast various techniques for controllable and conditioned text generation using large language models
Define and differentiate between general purpose llms and domain-specific llms, and recognize reasons to build domain-specific llms -
Design and implement methods for fine-tuning large language models with domain-specific datasets
Identify advanced techniques for multimodal generative ai, incorporating both text and images
Outline the use of design and implement methods for fine-tuning large language models with domain-specific datasets
Identify methods for handling bias and promoting fairness in large language models for generative ai
Evaluate strategies for optimizing large language model architectures and training procedures to enhance generative performance
Outline emerging research trends in large language models and their future implications for generative ai applications
Summarize the key concepts covered in this course
IN THIS COURSE
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52sIn this video, we will discover the key concepts covered in this course. FREE ACCESS
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10m 45sDuring this video, discover how to analyze the architectural components of large language models (LLMs) and their role in generative artificial intelligence (AI). FREE ACCESS
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3. Evaluating the Impact of Training Approaches9m 42sFind out how to evaluate the impact of different training approaches on the performance and generative capabilities of large language models. FREE ACCESS
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4. Implementing Fine-tuning Techniques10m 6sIn this video, you will learn how to implement techniques to fine-tune large language models for specific generative tasks. FREE ACCESS
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5. Analyzing Challenges in LLMs9m 7sDiscover how to analyze the challenges and limitations of large language models in generative AI applications. FREE ACCESS
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6. Controllable Text Generation6m 45sAfter completing this video, you will be able to compare and contrast various techniques for controllable and conditioned text generation using large language models. FREE ACCESS
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7. General Purpose vs. Domain-specific LLMs10m 18sUpon completion of this video, you will be able to define and differentiate between general purpose LLMs and domain-specific LLMs, and recognize reasons to build domain-specific LLMs. FREE ACCESS
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8. Executing Domain-specific Fine-tuning9m 44sIn this video, you will learn how to design and implement methods for fine-tuning large language models with domain-specific datasets. FREE ACCESS
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9. Multimodal Generative AI10m 22sAfter completing this video, you will be able to identify advanced techniques for multimodal generative AI, incorporating both text and images. FREE ACCESS
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10. Multimodal Implementation8m 47sUpon completion of this video, you will be able to outline the use of design and implement methods for fine-tuning large language models with domain-specific datasets. FREE ACCESS
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11. Handling Bias in LLMs5m 43sAfter completing this video, you will be able to identify methods for handling bias and promoting fairness in large language models for generative AI. FREE ACCESS
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12. Optimizing LLM Architectures6m 43sUpon completion of this video, you will be able to evaluate strategies for optimizing large language model architectures and training procedures to enhance generative performance. FREE ACCESS
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13. Emerging Trends in LLMs8m 33sAfter completing this video, you will be able to outline emerging research trends in large language models and their future implications for generative AI applications. FREE ACCESS
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14. Course Summary44sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
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