LLMs and Industry Best Practices

Explore the transformative power of Large Language Models (LLMs) in this advanced course designed to equip you with the skills and knowledge to excel in the world of AI and machine learning.

Delve deep into the architecture, practical applications, and manipulation of LLMs. Learn how to fine-tune LLMs with your data and deploy models.

Get hands-on experience with SDKs, model evaluation, data curation, and multimodal models, and stay at the forefront of LLM technology with discussions on open problems and guest lectures from industry experts.

By the end of this course, you'll be prepared for advanced LLM-related roles and projects in the ever-evolving field of AI.

Advanced NLP Course or Equivalent (Deep Learning familiarity)

Successful completion of an advanced Natural Language Processing (NLP) course or an equivalent program is required. This should include coverage of key topics such as attention mechanisms, transformer model architectures, and their applications in NLP.

Programming Proficiency

Proficiency in a programming language commonly used in machine learning and deep learning, such as Python, is essential. Students should be able to write, understand, and modify code for training and evaluating machine learning models.

Experience with Deep Learning Frameworks

Familiarity with popular deep learning frameworks such as TensorFlow or PyTorch is required. Students should be able to implement and experiment with neural network architectures.