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Large Language Models Courses

Study large language models for advanced natural language processing. Learn to build and apply models like GPT-3 for various NLP tasks.

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Find the best Large Language Models course for your goals

  • Status: Preview
    Preview
    D

    DeepLearning.AI

    Generative AI with Large Language Models

    Skills you'll gain: Generative AI, Large Language Modeling, Prompt Engineering, PyTorch (Machine Learning Library), Python Programming, Applied Machine Learning, Scalability, Natural Language Processing, Responsible AI, Machine Learning, Reinforcement Learning, Performance Tuning

    4.8
    Rating, 4.8 out of 5 stars
    ·
    3.5K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    G

    Google Cloud

    Introduction to Large Language Models

    Skills you'll gain: Large Language Modeling, Prompt Engineering, LLM Application, Generative AI, Prompt Patterns, Generative Model Architectures

    4.4
    Rating, 4.4 out of 5 stars
    ·
    1.1K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    Duke University

    Large Language Model Operations (LLMOps)

    Skills you'll gain: Prompt Engineering, Databricks, Large Language Modeling, LLM Application, Generative AI, Performance Analysis, Apache Airflow, Workflow Management, Amazon Bedrock, Data Lakes, ChatGPT, Extract, Transform, Load, OpenAI, Multimodal Prompts, MLOps (Machine Learning Operations), AWS SageMaker, Performance Tuning, Scalability, Database Management Systems, Generative Model Architectures

    4.4
    Rating, 4.4 out of 5 stars
    ·
    223 reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    V

    Vanderbilt University

    Prompt Engineering for ChatGPT

    Skills you'll gain: Prompt Engineering, ChatGPT, Prompt Patterns, LLM Application, Productivity, OpenAI, Generative AI, Artificial Intelligence, Large Language Modeling, Artificial Intelligence and Machine Learning (AI/ML), Creative Thinking, Creative Problem-Solving, Problem Solving

    4.8
    Rating, 4.8 out of 5 stars
    ·
    6.8K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free
    Free
    D

    DeepLearning.AI

    Finetuning Large Language Models

    Skills you'll gain: Large Language Modeling, LLM Application, Prompt Engineering, AI Personalization, Network Model

    4.6
    Rating, 4.6 out of 5 stars
    ·
    569 reviews

    Intermediate · Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    I

    IBM

    Generative AI Engineering with LLMs

    Skills you'll gain: Prompt Engineering, Large Language Modeling, Generative AI, LLM Application, PyTorch (Machine Learning Library), Generative AI Agents, Natural Language Processing, Data Pipelines, Artificial Intelligence, Text Mining, Data Ethics, Deep Learning, Performance Tuning, Applied Machine Learning, Data Processing, Artificial Neural Networks, Reinforcement Learning, Document Management, Database Management Systems, Data Storage Technologies

    4.5
    Rating, 4.5 out of 5 stars
    ·
    697 reviews

    Intermediate · Specialization · 3 - 6 Months

What brings you to Coursera today?

  • Status: New
    New
    Status: Free Trial
    Free Trial
    P

    Pearson

    Quick Start Guide to Large Language Models (LLMs)

    Skills you'll gain: Prompt Engineering, Large Language Modeling, LLM Application, ChatGPT, Natural Language Processing, Generative AI Agents, OpenAI, Generative Model Architectures, Multimodal Prompts, Generative AI, Responsible AI, Artificial Intelligence and Machine Learning (AI/ML), AI Personalization, Cost Management, Deep Learning, Application Deployment, Artificial Intelligence, Case Studies, Reinforcement Learning, Machine Learning

    Intermediate · Specialization · 1 - 4 Weeks

  • Status: Preview
    Preview
    D

    Duke University

    Foundations of Local Large Language models

    Skills you'll gain: Responsible AI, Generative AI, LLM Application, Cloud Applications, Application Deployment, Large Language Modeling, Data Ethics, Prompt Engineering, Risk Management Framework, Open Source Technology, Rust (Programming Language)

    4.1
    Rating, 4.1 out of 5 stars
    ·
    18 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM AI Engineering

    Skills you'll gain: Prompt Engineering, Large Language Modeling, PyTorch (Machine Learning Library), Unsupervised Learning, Generative AI, Supervised Learning, Keras (Neural Network Library), Feature Engineering, Reinforcement Learning, LLM Application, Deep Learning, Generative AI Agents, Applied Machine Learning, Natural Language Processing, Tensorflow, Artificial Neural Networks, Machine Learning Methods, Machine Learning, Python Programming, Data Science

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    21K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • G

    Google Cloud

    Transformer Models and BERT Model

    Skills you'll gain: Large Language Modeling, Natural Language Processing, Generative Model Architectures, Artificial Neural Networks

    4.1
    Rating, 4.1 out of 5 stars
    ·
    121 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free
    Free
    D

    DeepLearning.AI

    LangChain Chat with Your Data

    Skills you'll gain: LangChain, LLM Application, Large Language Modeling, Extract, Transform, Load, Data Processing, Data Import/Export, Semantic Web, Generative AI, Prompt Engineering, Document Management

    4.8
    Rating, 4.8 out of 5 stars
    ·
    636 reviews

    Beginner · Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    H

    H2O.ai

    Large Language Models

    Skills you'll gain: Large Language Modeling, LLM Application, Artificial Neural Networks, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Data Management, Prompt Engineering, Training Programs, Data Validation, Data Cleansing, Program Evaluation, Natural Language Processing, Applied Machine Learning, MLOps (Machine Learning Operations), Data Transformation, Verification And Validation, Data Quality, Performance Tuning, Data Processing

    3.4
    Rating, 3.4 out of 5 stars
    ·
    12 reviews

    Intermediate · Specialization · 3 - 6 Months

Large Language Models learners also search

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In summary, here are 10 of our most popular large language models courses

  • Generative AI with Large Language Models: DeepLearning.AI
  • Introduction to Large Language Models: Google Cloud
  • Large Language Model Operations (LLMOps): Duke University
  • Prompt Engineering for ChatGPT: Vanderbilt University
  • Finetuning Large Language Models: DeepLearning.AI
  • Generative AI Engineering with LLMs: IBM
  • Quick Start Guide to Large Language Models (LLMs): Pearson
  • Foundations of Local Large Language models: Duke University
  • IBM AI Engineering: IBM
  • Transformer Models and BERT Model: Google Cloud

Frequently Asked Questions about Large Language Models

Browse the LLM courses below—popular starting points on Coursera.

  • Generative AI with Large Language Models: DeepLearning.AI
  • Introduction to Large Language Models: Google Cloud
  • Large Language Model Operations (LLMOps): Duke University
  • Finetuning Large Language Models: DeepLearning.AI
  • Generative AI Engineering with LLMs: IBM
  • Large Language Models: H2O.ai
  • Foundations of Local Large Language models: Duke University‎

Coursera’s courses on Large Language Models offer learners insights and skills related to cutting-edge AI technologies:

  • Fundamental concepts of natural language processing (NLP) and how LLMs are developed and utilized.
  • Techniques for training, fine-tuning, and deploying LLMs such as GPT (Generative Pre-trained Transformer).
  • Understanding the ethical considerations and societal impacts of LLMs.
  • Skills in integrating LLMs with various applications to enhance user interaction and automate tasks.
  • Best practices for managing data privacy and security when using LLMs.
  • Exploration of recent advancements and potential future developments in LLM technology.‎

Courses on LLMs are accessible to learners with diverse backgrounds:

  • Beginners with an interest in AI and machine learning can start with introductory courses that provide a basic understanding of NLP and LLMs.
  • Those with some technical experience can enhance their knowledge with courses focused on specific aspects of LLM development and deployment.
  • Advanced learners can engage with complex topics related to the cutting-edge applications and ethical implications of LLMs.‎

Upon completing LLM courses, learners can obtain credentials:

  • Professional certificates that indicate participation in courses focused on LLMs and their applications.
  • Specializations that cover technical, ethical, and practical aspects of LLMs, aimed at broadening understanding and application skills.
  • Certificates that learners may include in their portfolios to reflect their engagement with advanced AI concepts.‎

Skills in LLMs can open up various career opportunities in the tech industry, particularly in roles focused on AI and machine learning:

  • AI Research Scientist, working on the development of new language models and NLP techniques.
  • Machine Learning Engineer, implementing and scaling LLMs for commercial or research applications.
  • Data Scientist, leveraging LLMs for data analysis and insight generation.
  • NLP Specialist, focusing on improving interaction between humans and computers through language.
  • Ethical AI Advocate, analyzing and addressing the societal impacts of AI technologies like LLMs.‎

Looking to enhance your team's LLM skills? Coursera provides tailored enterprise solutions for teams ranging of 5-125 employees. Our offerings include advanced analytics, customized learning paths, and collaborative tools. To explore our LLM training options and make a purchase, please visit our Coursera for Teams page.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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