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  2. Large Language Models

Large Language Models Courses

Large language models (LLMs) courses cover topics like natural language processing, text generation, and model training. You’ll learn about the architectures behind models such as GPT and BERT, how they process and generate text, and the implications of their use. Expect to explore methods for fine-tuning these models and applying them in different contexts.

Popular Large Language Models Courses and Certifications


  • P

    Packt

    Decoding Large Language Models

    Skills you'll gain: Large Language Modeling, LLM Application, Fine-tuning, Model Deployment, Model Training, Transfer Learning, Generative Model Architectures, Prompt Engineering, Model Optimization, Generative AI, AI Integrations, Model Evaluation, Deep Learning, Natural Language Processing, Recurrent Neural Networks (RNNs), AI Security, Responsible AI, Scalability, Machine Learning

    Advanced · Course · 3 - 6 Months

  • J

    Johns Hopkins University

    Advanced Statistics for Data Science

    Skills you'll gain: Statistical Hypothesis Testing, Regression Analysis, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Statistics, Probability, R Programming, Biostatistics, Data Analysis, Data Science, Probability Distribution, Derivatives

    4.4 stars, 802 reviews, Advanced, Specialization, 3 - 6 Months

    ★ 4.4 (802) · Advanced · Specialization · 3 - 6 Months

  • I

    IBM

    Generative AI for NLP with PyTorch

    Skills you'll gain: PyTorch (Machine Learning Library), Fine-tuning, Convolutional Neural Networks, Deep Learning, Natural Language Processing, Embeddings, Hugging Face, Supervised Learning, Classification Algorithms, Data Preprocessing, Predictive Modeling, Machine Learning, Data Processing, Artificial Intelligence and Machine Learning (AI/ML), Statistical Methods, Probability & Statistics, Machine Learning Algorithms

    4.4 stars, 2.1K reviews, Advanced, Specialization, 3 - 6 Months

    ★ 4.4 (2.1K) · Advanced · Specialization · 3 - 6 Months

    Category: New
    New
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  • D

    Duke University

    MLOps | Machine Learning Operations

    Skills you'll gain: Fine-tuning, MLOps (Machine Learning Operations), Model Deployment, Cloud Deployment, Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Hugging Face, GitHub Copilot, Responsible AI, Data Manipulation, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis

    4.1 stars, 654 reviews, Advanced, Specialization, 3 - 6 Months

    ★ 4.1 (654) · Advanced · Specialization · 3 - 6 Months

    Status: Trending right now
    Trending right now
  • I

    IBM

    IBM RAG and Agentic AI

    Skills you'll gain: Prompt Engineering, AI Orchestration, AI Workflows, LangGraph, Agentic Workflows, LangChain, Retrieval-Augmented Generation, LLM Application, Tool Calling, Agentic systems, Model Context Protocol, Generative AI Agents, Generative AI, AI Security, Vector Databases, Responsible AI, Embeddings, Large Language Modeling, AI Integrations, Software Development

    4.6 stars, 1.2K reviews, Advanced, Professional Certificate, 3 - 6 Months

    ★ 4.6 (1.2K) · Advanced · Professional Certificate · 3 - 6 Months

    Status: Top AI program
    Top AI program
  • What brings you to Coursera today?

  • A

    Amazon Web Services

    AWS Generative AI Developer Advanced

    Skills you'll gain: Prompt Engineering, Retrieval-Augmented Generation, Personally Identifiable Information, Dashboard Creation, Token Optimization, Generative AI Agents, Responsible AI, AI Workflows, Generative AI, Agentic systems, Enterprise Architecture, API Design, API Gateway, Performance Tuning, Amazon Web Services, Artificial Intelligence and Machine Learning (AI/ML), Cloud Applications, Artificial Intelligence, Cloud Platforms, Machine Learning

    Advanced · Professional Certificate · 3 - 6 Months

    Status: Top AI program
    Top AI program
    Category: New
    New
  • I

    IBM

    IBM AI Enterprise Workflow

    Skills you'll gain: Feature Engineering, Model Deployment, Data Visualization, Data Ethics, Exploratory Data Analysis, Model Evaluation, Unsupervised Learning, Data Presentation, Tensorflow, Application Deployment, Dimensionality Reduction, Model Training, Probability Distribution, Apache Spark, Statistical Hypothesis Testing, Supervised Learning, Design Thinking, Data Science, Machine Learning, Python Programming

    4.4 stars, 399 reviews, Advanced, Specialization, 3 - 6 Months

    ★ 4.4 (399) · Advanced · Specialization · 3 - 6 Months

  • E

    ESSEC Business School

    Strategic Business Analytics

    Skills you'll gain: Data-Driven Marketing, Marketing Analytics, Business Analytics, Forecasting, Peer Review, Statistical Methods, Data Presentation, Customer Analysis, Case Studies, R (Software), Information Technology, Presentations, Analytics, Digital Transformation, Advanced Analytics, Marketing Strategies, Complex Problem Solving, Analysis, R Programming, Data Analysis

    4.4 stars, 1.3K reviews, Advanced, Specialization, 3 - 6 Months

    ★ 4.4 (1.3K) · Advanced · Specialization · 3 - 6 Months

  • U

    University of Colorado Boulder

    High-Performance and Parallel Computing

    Skills you'll gain: Bash (Scripting Language), Distributed Computing, Scalability, Memory Management, Computer Systems, Computer Science, File I/O, Big Data, File Systems, Scripting, Performance Tuning, Linux, C++ (Programming Language), C (Programming Language)

    3.8 stars, 190 reviews, Advanced, Specialization, 3 - 6 Months

    ★ 3.8 (190) · Advanced · Specialization · 3 - 6 Months

  • G

    Google Cloud

    BigQuery ML: From Forecasting to LLMs

    Skills you'll gain: Google Gemini, Retrieval-Augmented Generation, Model Deployment, Google Cloud Platform, Generative AI, LLM Application, MLOps (Machine Learning Operations), Predictive Analytics, Embeddings, Predictive Modeling, Data Analysis, Time Series Analysis and Forecasting, Forecasting, Applied Machine Learning, Model Training, Data Preprocessing, Model Evaluation, Machine Learning, Classification Algorithms, SQL

    4.6 stars, 1.3K reviews, Advanced, Specialization, 3 - 6 Months

    ★ 4.6 (1.3K) · Advanced · Specialization · 3 - 6 Months

    Category: New
    New
  • A

    Amazon Web Services

    AWS ML Engineer Associate Curriculum Overview (ML Engineer)

    Advanced · Course · 1 - 4 Weeks

    Category: New
    New
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How to choose the right Large Language Models course

Start with what you want to do. If you want to implement conversational agents, choose courses focusing on dialogue systems and natural language understanding. If you're interested in Hugging Face Transformers, check for courses that cover model fine-tuning and deployment using that library. Compare these options to find the best fit for your needs.


Best Large Language Models courses from IBM

Top-rated Large Language Models courses offered by IBM on Coursera.

  1. 1
    Generative AI for NLP with PyTorch
    IBMAdvanced3 - 6 Months4.4(2,128)IBM
  2. 2
    IBM RAG and Agentic AI
    IBMAdvanced3 - 6 Months4.6(1,176)IBM
  3. 3
    IBM AI Enterprise Workflow
    IBMAdvanced3 - 6 Months4.4(399)IBM

Best Large Language Models certificate programs

Earn a certificate in Large Language Models from top universities and companies.

  1. 1
    Advanced Statistics for Data Science
    Johns Hopkins UniversityAdvanced3 - 6 Months4.4(802)Specialization
  2. 2
    MLOps | Machine Learning Operations
    Duke UniversityAdvanced3 - 6 Months4.1(654)Specialization
  3. 3
    AWS Generative AI Developer Advanced
    Amazon Web ServicesAdvanced3 - 6 Months2.8(4)Professional Certificate

Frequently Asked Questions about Large Language Models

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:

  1. Preview the first module of many large language models courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

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.‎

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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