Language Models Courses and Certifications

Large Language Models with Semantic Search

Enhance search capabilities using LLMs, exploring dense retrieval and reranking techniques to improve relevance and effectiveness beyond traditional keyword-based methods.

• Coursera
• 1 hour 3 minutes
• On-Demand
• Paid Course

Quick Start Guide to Large Language Models (LLMs): Unit 1

Explore NLP evolution, master attention mechanisms, and build RAG systems using ChatGPT, Llama, and T5 while developing prompt engineering skills for effective LLM communication.

• Coursera
• 6 hours 18 minutes
• On-Demand
• Paid Course

Microcredential

Quick Start Guide to Large Language Models (LLMs)

Master building and deploying GPT, Llama, T5, and BERT at scale with step-by-step guidance, real-world case studies, fine-tuning techniques, and practical applications.

• Coursera
• 4 weeks, 5 hours a week
• On-Demand
• Paid Course
• 3 courses

Pragmatic AI Labs

Applied Local Large Language Models

Unlock the power of Local Large Language Models: master deployment, setup, and integration techniques for efficient LLM utilization on your machine using cutting-edge tools and interfaces.

• edX
• 4 weeks, 3-6 hours a week
• On-Demand
• Free Online Course (Audit)

H2O.ai

H2O ai Large Language Models (LLMs) - Level 2

Master advanced LLM techniques through data preparation, fine-tuning, and model optimization. Learn QnA dataset creation, quantization, and LoRA while using H2O LLM Studio for practical NLP applications.

• Coursera
• 3 hours 24 minutes
• On-Demand
• Paid Course

H2O.ai

H2O ai Large Language Models (LLMs) - Level 3

Master advanced H2O ai Generative AI tools and techniques, from creating custom h2oGPT models to evaluating performance metrics, enhancing your AI workflow capabilities for real business applications.

• Coursera
• 2 hours
• On-Demand
• Paid Course

Packt

Decoding Large Language Models

Unlock the architecture, training, and deployment of Large Language Models through hands-on expertise in fine-tuning, evaluation, and real-world integration strategies.

• Coursera
• 20 hours 28 minutes
• On-Demand
• Paid Course

Packt

Natural Language Processing - Deep Learning Models in Python

Master deep learning models for NLP with Python, implementing neural networks, CNNs, and RNNs for text classification, embeddings, and sequential data processing using TensorFlow.

• Coursera
• 10 hours 33 minutes
• On-Demand
• Paid Course

Working with large language models using Azure

Master generative AI development with Azure, covering LLMs, prompt engineering, RAG pipelines, fine-tuning, and end-to-end application deployment for real-world solutions.

• Coursera
• 20 hours 33 minutes
• On-Demand
• Paid Course

Whizlabs

Azure AI & ML: Optimize Language Models for AI Applications

Master Azure AI & ML model deployment, optimization, and MLOps workflows. Build production-ready solutions using Azure AI Foundry, AutoML, and advanced monitoring techniques.

• Coursera
• 8 hours 19 minutes
• On-Demand
• Paid Course

Quick Start Guide to Large Language Models (LLMs): Unit 2

Master optimization, fine-tuning, and AI alignment techniques to customize LLMs for specific needs while balancing performance and cost through advanced prompt engineering.

• Coursera
• 5 hours 24 minutes
• On-Demand
• Paid Course

Quick Start Guide to Large Language Models (LLMs): Unit 3

Master advanced LLM architectures, multimodal integration, reinforcement learning alignment, fine-tuning optimization, and cloud deployment strategies for high-performing models.

• Coursera
• 8 hours 7 minutes
• On-Demand
• Paid Course

Edureka

Fine-Tuning & Optimizing Large Language Models

Master parameter-efficient fine-tuning, context engineering, and deployment strategies for large language models using modern tools like Hugging Face and LoRA adapters.

• Coursera
• 13 hours 45 minutes
• On-Demand
• Paid Course

Linguistics for Token Classification in spaCy

Master linguistic concepts and semantic analysis for token classification using spaCy, from syntactic dependencies to custom NLP pipeline components and entity recognition techniques.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

Packt

Natural Language Processing - Probability Models in Python

Master probability-based NLP techniques in Python, from spam detection and sentiment analysis to text summarization and topic modeling, with hands-on implementation of algorithms like Naive Bayes, LDA, and TextRank.

• Coursera
• 6 hours 52 minutes
• On-Demand
• Paid Course