LLM University by Cohere
Their comprehensive curriculum aims to give you a rock-solid foundation in NLP, equipping you with the skills needed to develop your own applications. Whether you want to learn semantic search, generation, classification, embeddings, or any other NLP technique, this is the place for you! We cater to learners from all backgrounds, covering everything from the basics to the most advanced topics in large language models (LLMs), ensuring you can harness the full potential of LLMs. Plus, you'll have the opportunity to work on hands-on exercises, allowing you to build and deploy your very own models.
The Curriculum
In this course, you will learn everything about Large Language Models (LLMs), including:
- How do LLMs work?:
Learn about their architecture and their moving pieces, including transformer models, embeddings, similarity, and attention mechanisms.
- What are LLMs useful for?:
Learn about many real-world applications of LLMs, including:
- Semantic search
- Text generation
- Text classification
- Analyzing text using embeddings
- How can I use LLMs to build and deploy my apps?:
Learn how to use LLMs to build applications. This course will teach you:
- How to use Cohere's endpoints: Classify, Generate, and Embed.
- How to build apps, including semantic search models, text generators, etc.
- (Coming soon...) How to deploy these apps on many platforms.
Link: https://docs.cohere.com/docs/llmu
Navigational hashtags: #armknowledgesharing #armcourses
General hashtags: #deeplearning #dl #transofrmers #transformer #llm #largelanguagemodels #largelanguagemodel #textgeneration #semanticsearch #classification #textclassification #embeddings
@data_science_weekly
Their comprehensive curriculum aims to give you a rock-solid foundation in NLP, equipping you with the skills needed to develop your own applications. Whether you want to learn semantic search, generation, classification, embeddings, or any other NLP technique, this is the place for you! We cater to learners from all backgrounds, covering everything from the basics to the most advanced topics in large language models (LLMs), ensuring you can harness the full potential of LLMs. Plus, you'll have the opportunity to work on hands-on exercises, allowing you to build and deploy your very own models.
The Curriculum
In this course, you will learn everything about Large Language Models (LLMs), including:
- How do LLMs work?:
Learn about their architecture and their moving pieces, including transformer models, embeddings, similarity, and attention mechanisms.
- What are LLMs useful for?:
Learn about many real-world applications of LLMs, including:
- Semantic search
- Text generation
- Text classification
- Analyzing text using embeddings
- How can I use LLMs to build and deploy my apps?:
Learn how to use LLMs to build applications. This course will teach you:
- How to use Cohere's endpoints: Classify, Generate, and Embed.
- How to build apps, including semantic search models, text generators, etc.
- (Coming soon...) How to deploy these apps on many platforms.
Link: https://docs.cohere.com/docs/llmu
Navigational hashtags: #armknowledgesharing #armcourses
General hashtags: #deeplearning #dl #transofrmers #transformer #llm #largelanguagemodels #largelanguagemodel #textgeneration #semanticsearch #classification #textclassification #embeddings
@data_science_weekly
Large Language Model Course
The LLM course is divided into three parts:
🧩 LLM Fundamentals covers essential knowledge about mathematics, Python, and neural networks.
🧑🔬 The LLM Scientist focuses on building the best possible LLMs using the latest techniques.
👷 The LLM Engineer focuses on creating LLM-based applications and deploying them.
Links:
- Direct link
- Content Guide link
- Topic Guide link
Navigational hashtags: #armknowledgesharing #armcourses
General hashtags: #llm #llms #largelanguagemodel #largelanguagemodels #transofrmer #transformers #deeplearning #dl #nlp #naturallanguageprocessing
@data_science_weekly
The LLM course is divided into three parts:
🧩 LLM Fundamentals covers essential knowledge about mathematics, Python, and neural networks.
🧑🔬 The LLM Scientist focuses on building the best possible LLMs using the latest techniques.
👷 The LLM Engineer focuses on creating LLM-based applications and deploying them.
Links:
- Direct link
- Content Guide link
- Topic Guide link
Navigational hashtags: #armknowledgesharing #armcourses
General hashtags: #llm #llms #largelanguagemodel #largelanguagemodels #transofrmer #transformers #deeplearning #dl #nlp #naturallanguageprocessing
@data_science_weekly