Enroll Course: https://www.coursera.org/learn/generative-ai-engineering-and-fine-tuning-transformers
The field of Generative AI is rapidly evolving, and staying ahead requires the right skills and knowledge. I recently took the Coursera course titled “Generative AI Engineering and Fine-Tuning Transformers,” and it proved to be an invaluable resource for anyone looking to build a career in AI engineering. The course is designed to be highly practical, focusing on real-world applications of large language models (LLMs) and the tools used to fine-tune them.
The curriculum is well-structured, starting with foundational concepts such as transformers, model frameworks, and platforms like Hugging Face and PyTorch. The module on fine-tuning covers essential techniques, including model quantization, and guides you through using pre-trained models to customize LLMs for specific tasks. One of the most exciting parts is the Parameter Efficient Fine-Tuning (PEFT) section, where you learn about innovative methods like LoRA and QLoRA that allow effective model training with fewer resources.
Throughout the course, hands-on labs reinforce learning by giving you practical experience in training and fine-tuning models. This approach is perfect for those aiming to develop job-ready skills in generative AI. I highly recommend this course for AI enthusiasts, developers, and data scientists who want to deepen their understanding of transformer models and enhance their skillset in AI engineering.
Enroll Course: https://www.coursera.org/learn/generative-ai-engineering-and-fine-tuning-transformers