What Will You Learn?
How to apply LLMs to real-world problems in natural language processing (NLP) using popular libraries, such as Hugging Face and LangChain.
How to add domain knowledge and memory into LLM pipelines using embeddings and vector databases.
Understand the nuances of pre-training, fine-tuning, and prompt engineering, and apply that knowledge to fine-tune a custom chat model
How to evaluate the efficacy and bias of LLMs using different methods.
How to implement LLMOps and multi-step reasoning best practices for an LLM workflow.
About This Course
Provider: Edx
Format: Online
Duration: 60 hours to complete [Approx]
Target Audience: Intermediate
Learning Objectives: By the end of this free course, you will have built an end-to-end LLM workflow that is ready for production
Course Prerequisites: NA
Assessment and Certification: Earn a Certificate upon completion from the relevant Provider
Instructor: Databricks
Key Topics: Workflow Management, Natural Language Processing
Topic Covered:
- - Applications with LLMs
- - Embeddings, Vector Databases and Search
- - Multi-stage Reasoning
- - Fine-tuning and Evaluating LLMs
- - Society and LLMs: Bias and Safety
- - LLMOps
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