Mastering Generative AI: LLMs, Prompt Engineering & More!
Last Verified on September 5th, 2024
Last Verified on September 5th, 2024
In this course, you will explore a wide range of essential topics, including:
· Python Programming: Learn the fundamentals of Python, the go-to language for AI development, and become proficient in data manipulation using libraries like Pandas and NumPy.
· Natural Language Processing (NLP): Dive into the world of NLP, mastering techniques for text processing, feature extraction, and leveraging powerful libraries like NLTK and SpaCy.
· Deep Learning and Transformers: Understand the architecture of Transformer models, which are at the heart of many state-of-the-art AI applications. Discover the principles of deep learning and how to implement neural networks using TensorFlow and PyTorch.
· Large Language Models (LLMs): Gain insights into LLMs, their training, and fine-tuning processes. Learn how to effectively use these models in various applications, from chatbots to content generation.
· Retrieval-Augmented Generation (RAG): Explore the innovative concept of RAG, which combines retrieval techniques with generative models to enhance AI performance.
· Prompt Engineering: Master the art of crafting effective prompts to improve the interaction with LLMs and optimize the output for specific tasks.
· Vector Databases: Discover how to implement and utilize vector databases for storing and retrieving high-dimensional data, a crucial skill in managing AI-generated content.
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