What are the best LLM courses online?

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

What skills can I learn from courses on Large Language Models (LLMs) on Coursera?

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.

Do I need prior experience in artificial intelligence to start learning about LLMs on Coursera?

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.

What certifications and credentials can I earn through LLM courses on Coursera?

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.

What career opportunities can be pursued with skills in Large Language Models?

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.

How can I purchase LLM training courses for my team?

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.

Top Large Language Models Courses - Learn Large Language Models Online

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Large Language Models

Large Language Models Courses

Large Language Models courses can help you learn natural language processing, text generation techniques, and model evaluation methods. You can build skills in fine-tuning models, understanding tokenization, and implementing ethical AI practices. Many courses introduce tools like TensorFlow and PyTorch, along with libraries such as Hugging Face Transformers, that support developing and deploying AI applications that leverage large language models.

Popular Large Language Models Courses and Certifications

Status: Free Trial
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
4.5
Rating, 4.5 out of 5 stars
1.2K reviews
Beginner · Course · 1 - 4 Weeks
Status: Free Trial
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
7.2K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
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
4.5
Rating, 4.5 out of 5 stars
258 reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
IBM
IBM Generative AI Engineering
Skills you'll gain: Prompt Engineering, Exploratory Data Analysis, Data Wrangling, LangChain, Prompt Patterns, Large Language Modeling, Unsupervised Learning, PyTorch (Machine Learning Library), Generative AI, Restful API, Keras (Neural Network Library), Data Transformation, Supervised Learning, Flask (Web Framework), Data Analysis, Data Cleansing, Data Manipulation, Responsible AI, LLM Application, Data Import/Export
4.6
Rating, 4.6 out of 5 stars
96K reviews
Beginner · Professional Certificate · 3 - 6 Months
Status: Free Trial
IBM
Introduction to Artificial Intelligence (AI)
Skills you'll gain: Responsible AI, Generative AI, Natural Language Processing, Business Intelligence, Content Creation, Risk Mitigation
4.7
Rating, 4.7 out of 5 stars
22K reviews
Beginner · Course · 1 - 4 Weeks
Status: Free Trial
IBM
Generative AI: Foundation Models and Platforms
Skills you'll gain: Generative AI, Generative Model Architectures, OpenAI, Large Language Modeling, LLM Application, Prompt Engineering, Deep Learning, Responsible AI, Natural Language Processing
4.7
Rating, 4.7 out of 5 stars
292 reviews
Beginner · Course · 1 - 4 Weeks

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Status: Free
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
653 reviews
Beginner · Project · Less Than 2 Hours
Status: Free Trial
Packt
Natural Language Processing with Real-World Projects
Skills you'll gain: Pandas (Python Package), Matplotlib, NumPy, Data Visualization, Machine Learning Algorithms, Natural Language Processing, Semantic Web, Data Manipulation, Linear Algebra, Seaborn, Deep Learning, Machine Learning, Python Programming, Text Mining, Data Science, Data Processing, Supervised Learning, Applied Machine Learning, Unstructured Data, Markov Model
4.8
Rating, 4.8 out of 5 stars
9 reviews
Beginner · Specialization · 3 - 6 Months
Status: Preview
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)
4.2
Rating, 4.2 out of 5 stars
19 reviews
Beginner · Course · 1 - 4 Weeks
Status: Free
DeepLearning.AI
Large Language Models with Semantic Search
Skills you'll gain: LLM Application, Large Language Modeling, Data Processing, Big Data, Applied Machine Learning, Semantic Web, Natural Language Processing
Beginner · Project · Less Than 2 Hours
Status: Free Trial
Vanderbilt University
Prompt Engineering
Skills you'll gain: Prompt Engineering, ChatGPT, Prompt Patterns, Ideation, Verification And Validation, Data Presentation, LLM Application, Productivity, OpenAI, Document Management, Responsible AI, Generative AI, Large Language Modeling, Risk Management Framework, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Creative Thinking, Problem Solving, Data Analysis, Information Management
4.8
Rating, 4.8 out of 5 stars
8.3K reviews
Beginner · Specialization · 1 - 3 Months
Status: New
Packt
LLM Engineer’s Handbook
Skills you'll gain: Large Language Modeling, MLOps (Machine Learning Operations), Prompt Engineering, AWS SageMaker, Extract, Transform, Load, Data Pipelines, CI/CD, Supervised Learning, Application Deployment, Scalability, Performance Tuning
Beginner · Course · 1 - 3 Months

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

Introduction to Large Language Models: Google Cloud
Prompt Engineering for ChatGPT: Vanderbilt University
Large Language Model Operations (LLMOps): Duke University
IBM Generative AI Engineering: IBM
Introduction to Artificial Intelligence (AI): IBM
Generative AI: Foundation Models and Platforms: IBM
LangChain Chat with Your Data: DeepLearning.AI
Natural Language Processing with Real-World Projects: Packt
Foundations of Local Large Language models: Duke University
Large Language Models with Semantic Search: DeepLearning.AI

Frequently Asked Questions about Large Language Models

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

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.‎

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.