Introduction to Large Language Models (LLMs) In Python

Introduction to Large Language Models (LLMs) In Python, available at $19.99, has an average rating of 4.35, with 31 lectures, based on 1050 reviews, and has 4700 subscribers.

You will learn about Learn to work with Jupyter notebooks in a brand new cloud ecosystem-Saturn Cloud Read in multiple PDFs into Python Implement common natural language processing (NLP) techniques including entity recognition and keyword extraction Get acquainted with common Large Language Model (LLM) frameworks including LangChain Implement LLM frameworks for abstract summarisation and answering questions This course is ideal for individuals who are Students with prior exposure to NLP analysis or Those interested in using LLM frameworks for learning more about your texts or Students and practitioners of Artificial Intelligence (AI) It is particularly useful for Students with prior exposure to NLP analysis or Those interested in using LLM frameworks for learning more about your texts or Students and practitioners of Artificial Intelligence (AI).

Enroll now: Introduction to Large Language Models (LLMs) In Python

Summary

Title: Introduction to Large Language Models (LLMs) In Python

Price: $19.99

Average Rating: 4.35

Number of Lectures: 31

Number of Published Lectures: 31

Number of Curriculum Items: 31

Number of Published Curriculum Objects: 31

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Learn to work with Jupyter notebooks in a brand new cloud ecosystem-Saturn Cloud
Read in multiple PDFs into Python
Implement common natural language processing (NLP) techniques including entity recognition and keyword extraction
Get acquainted with common Large Language Model (LLM) frameworks including LangChain
Implement LLM frameworks for abstract summarisation and answering questions

Who Should Attend

Students with prior exposure to NLP analysis
Those interested in using LLM frameworks for learning more about your texts
Students and practitioners of Artificial Intelligence (AI)

Target Audiences

Students with prior exposure to NLP analysis
Those interested in using LLM frameworks for learning more about your texts
Students and practitioners of Artificial Intelligence (AI)

Unlock the potential of large language models (LLM) with my comprehensive course: “Introduction to Large Language Models (LLMs) In Python.” With a focus on LLM frameworks such as OpenAI, LangChain, and LLMA-Index, this course empowers you to build your own Document-Reading Virtual Assistant. Whether you’re new to LLM implementation or seeking to advance your AI skills, this course offers an invaluable opportunity to explore the cutting-edge field of AI.

Course Highlights:

– Cloud-Based Python Environment: Harness the power of Saturn Cloud, a cloud-based Python environment, to implement robust LLM implementations.

– Practical Text Analysis: Learn to implement essential Natural Language Processing (NLP) techniques, including entity recognition and keyword extraction, to deconstruct the text documents

– Leveraging LLM Frameworks: Discover standard techniques for LLM frameworks, including LangChain, OpenAI and LLAMA-Index, for abstract summarization and querying.

Why Enroll in This Course?

By enrolling in this course, you’re embarking on a journey to become an expert in harnessing the potential of text data with Large Language Models (LLMs). Driven by the vision of our experienced instructor, who holds an MPhil from the University of Oxford and a data-intensive PhD from Cambridge University, you’ll receive the guidance needed to navigate the complexities of LLM implementation.

Beyond the course content, you’ll benefit from continuous support, ensuring you extract the maximum value from your investment. Join our community of learners, immerse yourself in LLM analysis, and advance your expertise in AI and data science.

Enroll Now to Unlock the Power of Text Data With LLMs!

Course Curriculum

Chapter 1: Introduction To The Course

Lecture 1: Welcome To the Course

Lecture 2: Data and Code

Lecture 3: Python Installation

Lecture 4: Start With Google Colaboratory Environment

Lecture 5: Google Colabs and GPU

Lecture 6: Installing Packages In Google Colab

Lecture 7: Another Cloud To Work In: Saturn Cloud

Lecture 8: Say Hello To The Saturn Interface

Lecture 9: Brain Fail: Dealing With Memory Problems

Chapter 2: Get Started With The LLMs and Their Infrastructure

Lecture 1: What Is a Document Reading Virtual Assistant?

Lecture 2: Get Access To the OpenAI API

Lecture 3: Introduction to LangChain

Chapter 3: Start Reading in and Exploring Data

Lecture 1: Read in a Single PDF

Lecture 2: Read In Multiple PDFs

Lecture 3: A More Straightforward Way To Read in Multiple PDFs

Lecture 4: Learn More About Your Documents: Why We Need A Preliminary NLP Analysis

Lecture 5: Entity Matching

Lecture 6: Keyword Extraction

Lecture 7: What Is TF-IDF?

Lecture 8: Text Similarity

Chapter 4: Use LLMs To Learn From Your Text

Lecture 1: Overview-The Summarisation Process

Lecture 2: Abstract Summarizer

Lecture 3: Answer Questions Based On Given Text-LangChain

Lecture 4: Theoretical Undepinnings

Lecture 5: Answer Questions With Llama-Index

Chapter 5: Preliminary Prompt Engineering

Lecture 1: What Is Prompt Engineering?

Lecture 2: Prompt Engineering With Langchain

Chapter 6: Basic Python Primer

Lecture 1: Introduction to Numpy

Lecture 2: What Is Pandas?

Lecture 3: Basic Data Cleaning With Pandas

Lecture 4: Basic Principles of Data Visualisation

Instructors

Minerva Singh
Bestselling Instructor & Data Scientist(Cambridge Uni)

Rating Distribution

1 stars: 59 votes
2 stars: 54 votes
3 stars: 121 votes
4 stars: 346 votes
5 stars: 470 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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