Introduction to Large Language Models (LLMs) In Python from Udemy

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.

What's inside

Learning objectives

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

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

Syllabus

Introduction To The Course

Welcome To the Course

Data and Code

Python Installation

Start With Google Colaboratory Environment

Google Colabs and GPU

Installing Packages In Google Colab

Another Cloud To Work In: Saturn Cloud

Say Hello To The Saturn Interface

Brain Fail: Dealing With Memory Problems

Get Started With The LLMs and Their Infrastructure

What Is a Document Reading Virtual Assistant?

Get Access To the OpenAI API

Introduction to LangChain

Start Reading in and Exploring Data

Read in a Single PDF

Read In Multiple PDFs

A More Straightforward Way To Read in Multiple PDFs

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

Entity Matching

Keyword Extraction

What Is TF-IDF?

Text Similarity

Use LLMs To Learn From Your Text

Overview-The Summarisation Process

Abstract Summarizer

Answer Questions Based On Given Text-LangChain

Theoretical Undepinnings

Answer Questions With Llama-Index

Preliminary Prompt Engineering

What Is Prompt Engineering?

Prompt Engineering With Langchain

Basic Python Primer

Introduction to Numpy

What Is Pandas?

Basic Data Cleaning With Pandas

Basic Principles of Data Visualisation

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops professional skills and deep expertise in a particular topic or set of topics

Teaches skills, knowledge, and/or tools that are highly relevant to industry

Builds a strong foundation for beginners

Taught by industry experts

Offers a comprehensive study of science, math, and technology

Offers multi-modal learning experience

Career center

Learners who complete Introduction to Large Language Models (LLMs) In Python will develop knowledge and skills that may be useful to these careers:

Natural Language Processing Engineer

Natural Language Processing Engineers specialize in developing and implementing NLP models to extract insights from text data. This course will provide Natural Language Processing Engineers with a comprehensive understanding of LLM frameworks. They will learn how to use these frameworks for advanced NLP tasks such as text classification, named entity recognition, and machine translation, which are crucial for building sophisticated NLP systems.

See salaries and explore the career path for Natural Language Processing Engineer

Data Analyst

Data Analysts collect, clean, and analyze data to help businesses make informed decisions and obtain valuable insights. This course will help Data Analysts in building a foundation in working with large text-based datasets using Python and various LLM frameworks. By harnessing the power of LLMs, Data Analysts can automate data analysis tasks, extract meaningful insights from unstructured text data, and derive actionable intelligence from various sources.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

Machine Learning Engineers are responsible for developing, deploying, and maintaining machine learning models. This course will help Machine Learning Engineers in gaining expertise in using LLMs for natural language processing tasks. They will learn how to implement LLM frameworks to automate tasks such as text summarization, question answering, and sentiment analysis, which are essential for developing robust machine learning models.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use data to solve business problems and uncover valuable insights. This course will help Data Scientists in expanding their skillset by introducing them to LLMs and their applications in data science. They will learn how to use LLMs for data exploration, feature engineering, and predictive modeling, which are essential for building effective data science solutions.

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Research Scientist

Research Scientists conduct research in various scientific fields, including computer science, natural language processing, and artificial intelligence. This course will help Research Scientists in exploring the cutting-edge advancements in LLM technology. They will learn how to leverage LLMs for their research, enabling them to develop innovative solutions and make significant contributions to their field of study.

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Software Engineer

Software Engineers design, develop, and maintain software applications. This course will help Software Engineers in building a foundation in LLM integration and implementation. They will learn how to leverage LLMs to enhance the functionality of their applications, such as adding natural language processing capabilities, improving user experience, and automating tasks.

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Technical Writer

Technical Writers create and maintain technical documentation, such as user manuals, white papers, and training materials. This course will help Technical Writers in enhancing their ability to communicate complex technical information effectively. They will learn how to use LLMs to generate clear and concise documentation, improve readability, and adapt to different audiences.

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Product Manager

Product Managers are responsible for managing the development and launch of new products. This course will help Product Managers in understanding the potential of LLMs and their impact on product development. They will learn how to incorporate LLMs into their product strategy, identify use cases, and gather user feedback to ensure successful product launches.

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Content Strategist

Content Strategists develop and execute content strategies to achieve business objectives. This course will help Content Strategists in creating more engaging and effective content. They will learn how to use LLMs to generate ideas, optimize content for search engines, and analyze user engagement, enabling them to develop successful content strategies.

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Information Architect

Information Architects design and organize information systems to ensure usability and accessibility. This course will help Information Architects in enhancing the user experience of information systems. They will learn how to use LLMs to improve information retrieval, create intuitive navigation structures, and optimize content for different platforms.

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Business Analyst

Business Analysts identify and analyze business needs to improve processes and systems. This course may be useful for Business Analysts who want to explore the potential of LLMs in process optimization. They will learn how to use LLMs to analyze data, identify inefficiencies, and develop recommendations for improvement.

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UX Designer

UX Designers create user interfaces and experiences for websites and applications. This course may be useful for UX Designers who want to learn how to incorporate LLMs into their designs. They will learn how to use LLMs to improve user interactions, personalize content, and conduct user testing.

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Marketing Manager

Marketing Managers develop and execute marketing strategies to promote products and services. This course may be useful for Marketing Managers who want to leverage LLMs for marketing campaigns. They will learn how to use LLMs to generate marketing content, analyze customer data, and optimize targeting for better results.

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Customer Success Manager

Customer Success Managers ensure customer satisfaction and retention. This course may be beneficial for Customer Success Managers who want to use LLMs to enhance customer interactions. They will learn how to use LLMs to provide personalized support, resolve customer issues, and identify opportunities for upselling and cross-selling.

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Sales Manager

Sales Managers lead sales teams and develop sales strategies. This course may be helpful for Sales Managers who want to use LLMs to improve sales performance. They will learn how to use LLMs to generate leads, qualify prospects, and close deals more efficiently.

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