Description
Course Introduction to Large Language Models (LLMs) In Python. An Introduction to Large Language Models (LLM) in Python.” Focusing on LLM frameworks such as OpenAI, LangChain and LLMA-Index, this course allows you to build your own document reading virtual assistant. Whether you are new to LLM implementation or looking to develop your AI skills, this course offers a valuable opportunity to explore advanced areas of AI. Highlights of the course:
– Cloud-based Python environment: Leverage the power of Saturn Cloud, a cloud-based Python environment, to run robust LLM implementations.
Practical Text Analysis: Learn to implement essential Natural Language Processing (NLP) techniques, including entity recognition and keyword extraction, to deconstruct text documents.
– Using LLM frameworks: Explore standard techniques for LLM frameworks, including LangChain, OpenAI, and LLAMA-Index for abstraction and querying.
By enrolling in this course, you begin a journey to become an expert in harnessing the potential of textual data with Large Language Models (LLM). From the perspective of our experienced tutor, who holds an MA from Oxford University and a data-driven PhD from Cambridge University, you’ll get the guidance you need to navigate the complexities of running an LLM. Beyond the course content, you’ll benefit from ongoing support, ensuring you extract maximum value from your investment. Join our community of learners, immerse yourself in the LLM Analytics and develop your expertise in artificial intelligence and data science.
What you will learn in the Introduction to Large Language Models (LLMs) In Python course
-
Learn to work with Jupyter notebooks in a brand new cloud ecosystem – Saturn Cloud
-
Read in multiple PDF files in Python
-
Implementation of common Natural Language Processing (NLP) techniques including entity recognition and keyword extraction
-
Learn about popular Large Language Model (LLM) frameworks, including LangChain
-
Implement LLM frameworks for summarizing abstracts and answering questions
This course is suitable for people who
- Students previously exposed to NLP analysis
- Those interested in using LLM frameworks to learn more about their texts
- Artificial intelligence (AI) students and workers
Introduction to Large Language Models (LLMs) in Python
- Publisher: Udemy
- teacher: Minerva Singh
- Training level: beginner to advanced
- Training duration: 2 hours and 45 minutes
- Number of courses: 31
Course headings
Prerequisites of the Introduction to Large Language Models (LLMs) In Python course
- Prior experience of using Jupyter notebooks
- Prior exposure to Natural Language Processing (NLP) concepts will be helpful but not compulsory
- An interest in using Large Language Models (LLMs) for your own documents
Course images
Sample video of the course
Installation guide
After Extract, view with your favorite Player.
Subtitle: None
Quality: 720p
download link
File(s) password: www.downloadly.ir
Size
1.1 GB
Be the first to comment