Andrew Ng Unveils New Free Course on Llama 2 with Meta

A recent addition to the DeepLearning.AI course catalogue is Meta's "Engineering with Llama 2." This course allows you to explore prompt engineering using the company's Llama 2 models. The course is tailored for beginners, requiring just one hour. Led by instructor Amit Sangani, senior director of partner engineering, Meta, the course is currently available for free for a limited time.

You can sign up for the course here.

Participants will gain insights into the best practices associated with prompting Llama 2 models, focusing on practical applications. The curriculum encourages interaction with three key models: Meta Llama 2 Chat, Code Llama, and Llama Guard. These models serve distinct purposes, ranging from conversation and coding assistance to content moderation through Llama Guard.

The primary learning objectives of the course involve familiarizing oneself with the Llama 2 collection, adopting best practices in prompt engineering, and building applications using these models. Through a simple API call, participants will explore the diverse outputs of the Llama 2 models, gaining a nuanced understanding of their capabilities.

The course instructs participants on leveraging Llama 2 models as personal assistants, providing guidance for day-to-day tasks. Additionally, it delves into advanced prompt engineering techniques such as few-shot prompting for sentiment analysis and chain-of-thought prompting for logical problem-solving. Code Llama is introduced as a collaborative partner for pair programming, facilitating both learning and code improvement.

The course also throws light on the responsible use of LLMs by incorporating Llama Guard, which screens user prompts and model responses for potentially harmful content. Importantly, participants are informed that Llama 2 models and their weights are available for free download, including quantized versions for local machine deployment. The course also encourages involvement in an active open-source community that utilizes Llama 2 for building diverse applications.