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.

Google Cloud
Skills you'll gain: Large Language Modeling, Google Gemini, Prompt Engineering, LLM Application, Generative AI
Beginner · Course · 1 - 4 Weeks

Vanderbilt University
Skills you'll gain: Prompt Engineering, ChatGPT, Prompt Patterns, LLM Application, Productivity, OpenAI, AI Enablement, Generative AI, Artificial Intelligence, Large Language Modeling, Creativity, Problem Solving, Context Management, Verification And Validation
Beginner · Course · 1 - 3 Months

Duke University
Skills you'll gain: Prompt Engineering, Databricks, Large Language Modeling, Model Deployment, LLM Application, Generative AI, Performance Analysis, Retrieval-Augmented Generation, Generative Model Architectures, Apache Airflow, Workflow Management, Hugging Face, Amazon Bedrock, Vector Databases, Data Lakes, ChatGPT, Extract, Transform, Load, OpenAI, Multimodal Prompts, MLOps (Machine Learning Operations)
Beginner · Specialization · 3 - 6 Months

Skills you'll gain: Prompt Engineering, Exploratory Data Analysis, Prompt Patterns, LangChain, Large Language Modeling, Retrieval-Augmented Generation, Model Evaluation, Unsupervised Learning, Generative Model Architectures, PyTorch (Machine Learning Library), ChatGPT, Generative AI, Restful API, LLM Application, Keras (Neural Network Library), Data Transformation, Supervised Learning, Responsible AI, Vector Databases, Data Import/Export
Beginner · Professional Certificate · 3 - 6 Months

Skills you'll gain: Prompt Engineering, Large Language Modeling, Generative AI, AI Security, Gemini, AI Enablement, Google Workspace, Productivity Software, Artificial Intelligence and Machine Learning (AI/ML), LLM Application, Model Evaluation, AI Workflows, Workplace inclusivity, Social Impact, Operational Efficiency, Human Factors, Critical Thinking, Analysis, Data Security, Natural Language Processing
Beginner · Specialization · 3 - 6 Months

Real Madrid Graduate School Universidad Europea
Skills you'll gain: Data Presentation, Matplotlib, Data Synthesis, Probability Distribution, Data Processing, Data Integration, Data Literacy, Performance Analysis, Exploratory Data Analysis, Statistical Analysis, Probability, Applied Machine Learning, Analysis, Image Analysis, Descriptive Analytics, AI Enablement, Business Analytics, Statistical Methods, Data Collection, Machine Learning
Beginner · Specialization · 3 - 6 Months

DeepLearning.AI
Skills you'll gain: Retrieval-Augmented Generation, LangChain, LLM Application, ChatGPT, Large Language Modeling, Embeddings, Data Processing, Data Import/Export, Vector Databases, Prompt Engineering, Document Management
Beginner · Project · Less Than 2 Hours

Skills you'll gain: Matplotlib, NumPy, Embeddings, Data Visualization, Natural Language Processing, Semantic Web, Data Manipulation, Linear Algebra, Seaborn, Deep Learning, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Python Programming, Text Mining, Data Science, Data Processing, Applied Machine Learning, Unstructured Data, Markov Model, Data Preprocessing
Beginner · Specialization · 3 - 6 Months

DeepLearning.AI
Skills you'll gain: LLM Application, Large Language Modeling, Embeddings, Prompt Engineering, Data Processing, Big Data, Applied Machine Learning, Vector Databases
Beginner · Project · Less Than 2 Hours

Duke University
Skills you'll gain: Retrieval-Augmented Generation, Responsible AI, Generative AI, Cloud Deployment, LLM Application, Model Deployment, Application Deployment, Large Language Modeling, Hugging Face, Data Ethics, Prompt Engineering, Model Evaluation, Risk Management Framework, Rust (Programming Language)
Beginner · Course · 1 - 4 Weeks

Skills you'll gain: Generative AI, Generative Model Architectures, Generative Adversarial Networks (GANs), OpenAI, Hugging Face, Large Language Modeling, Prompt Engineering, IBM Cloud, Deep Learning, Natural Language Processing
Beginner · Course · 1 - 4 Weeks

Vanderbilt University
Skills you'll gain: Prompt Engineering, ChatGPT, Prompt Patterns, Verification And Validation, Ideation, Data Presentation, LLM Application, Productivity, OpenAI, Document Management, Responsible AI, AI Enablement, Generative AI, Creativity, Large Language Modeling, Risk Management Framework, Artificial Intelligence, Problem Solving, Data Analysis, Information Management
Beginner · Specialization · 1 - 3 Months
Large language models (LLMs) are advanced artificial intelligence systems designed to understand and generate human-like text. They utilize vast amounts of data and sophisticated algorithms to learn patterns in language, enabling them to perform a variety of tasks, such as translation, summarization, and content creation. The importance of LLMs lies in their ability to enhance communication, automate processes, and provide insights across numerous fields, including education, healthcare, and business. As organizations increasingly rely on data-driven decision-making, understanding LLMs becomes essential for leveraging their capabilities effectively.
Careers in large language models are diverse and growing rapidly. You might consider roles such as AI Research Scientist, Machine Learning Engineer, Data Scientist, or Natural Language Processing (NLP) Specialist. These positions often involve developing and implementing LLMs for various applications, including chatbots, recommendation systems, and content generation tools. Additionally, roles in product management and AI ethics are emerging as organizations seek to responsibly integrate LLMs into their operations. With the right skills and knowledge, you can position yourself for a rewarding career in this dynamic field.
To work effectively with large language models, you should focus on acquiring a blend of technical and analytical skills. Key areas include programming languages such as Python, familiarity with machine learning frameworks like TensorFlow or PyTorch, and a solid understanding of natural language processing concepts. Additionally, knowledge of data handling, model evaluation, and ethical considerations in AI is crucial. Courses that cover these topics can help you build a strong foundation and prepare you for practical applications in the field.
There are several excellent online courses available for learning about large language models. Notable options include the Large Language Models Specialization, which provides a comprehensive overview of LLMs, and the Generative AI and Large Language Models course, focusing on practical applications. For those interested in a structured learning path, the Quick Start Guide to Large Language Models (LLMs) Specialization is also a great choice.
Yes. You can start learning large language models on Coursera for free in two ways:
If you want to keep learning, earn a certificate in large language models, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.
To learn about large language models, start by identifying your current skill level and areas of interest. You can begin with introductory courses, such as the Introduction to Large Language Models, which provide a solid foundation. As you progress, consider more specialized courses that focus on specific applications or technologies. Engage with hands-on projects to apply what you learn, and participate in online communities to connect with others in the field. This approach will help reinforce your understanding and build your confidence.
Courses on large language models typically cover a range of topics, including the fundamentals of natural language processing, the architecture of LLMs, training techniques, and evaluation methods. You may also explore practical applications, such as building chatbots, content generation, and ethical considerations in AI. Advanced courses might explore into specific frameworks and tools used in the industry, providing you with the skills needed to implement LLMs effectively.
For training and upskilling employees or the workforce in large language models, consider courses like the Building Production-Ready Apps with Large Language Models course, which focuses on practical implementation. Additionally, the H2O AI Large Language Models (LLMs) - Level 1 course provides foundational knowledge that can be beneficial for teams looking to integrate LLMs into their projects. These courses can help organizations enhance their capabilities and stay competitive in the evolving landscape of AI.