Transfer Learning Courses and Certifications

H2O.ai

H2O ai Large Language Models (LLMs) - Level 1

Dive into foundational concepts of Large Language Models, exploring neural networks, transformer architecture, and practical applications while mastering pre-training and fine-tuning techniques.

• Coursera
• 1 hour 14 minutes
• Self-Paced
• Paid Course

Coursera

Deep Learning with PyTorch

Master neural networks, CNNs, RNNs, and LSTMs using PyTorch for computer vision and NLP tasks with advanced optimization techniques and real-world applications.

• Coursera
• 1 day 2 hours 18 minutes
• Self-Paced
• Paid Course

Introduction to Transformer Models for NLP: Unit 1

Explore transformer architectures, attention mechanisms, and transfer learning with BERT and GPT models for advanced NLP applications using PyTorch.

• Coursera
• 3 hours 25 minutes
• Self-Paced
• Paid Course

Packt

Advanced Machine Learning and Deep Learning

Master advanced machine learning and deep learning techniques, from neural networks to CNNs and RNNs. Apply knowledge through hands-on labs, covering regression, classification, and specialized topics like autoencoders and transfer learning.

• Coursera
• 7 hours 22 minutes
• Self-Paced
• Paid Course

Coursera Career Certificate

Transformers Unleashed: Master the Architecture of Modern AI

Master transformer-based AI systems—from building neural networks and NLP pipelines to deploying scalable ML models in cloud environments using TensorFlow, CI/CD workflows, and enterprise-grade architecture.

• Coursera
• 16 weeks, 4 hours/week
• Self-Paced
• Paid Course
• 6 courses

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
• Self-Paced
• Paid Course

Coursera

Building and Optimizing AI Models

Master the full AI model lifecycle—design neural networks, apply transfer learning, optimize deep learning workflows, and benchmark performance using Python and TensorFlow.

• Coursera
• 7 hours 33 minutes
• Self-Paced
• Paid Course

Coursera Career Certificate

Multimodal Intelligence - Vision, Audio & Language in Action

Master multimodal AI by processing vision, audio, and text data, fine-tuning transformers, building ETL pipelines, and deploying production-ready inference services on Kubernetes with CI/CD.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 5 courses

Packt

Deep Learning: Convolutional Neural Networks with TensorFlow

Unlock the potential of deep learning by mastering Convolutional Neural Networks and Transfer Learning with hands-on TensorFlow and Keras experience for image and text classification.

• Coursera
• 5 hours 14 minutes
• Self-Paced
• Paid Course

Coursera Career Certificate

Eyes on AI - Computer Vision Engineering

Master computer vision engineering by building, optimizing, and deploying AI systems for real-world applications like autonomous vehicles and medical imaging using PyTorch and MLOps practices.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 4 courses

Packt

Machine Learning – Modern Computer Vision & Generative AI

Master modern computer vision and generative AI techniques, from image classification to Stable Diffusion. Build practical skills in transfer learning, object detection, and AI-driven image generation using KerasCV and Python.

• Coursera
• 9 hours 1 minute
• Self-Paced
• Paid Course

Packt

Deep Learning with Keras and Practical Applications

Master deep learning with Keras: from wine quality prediction to advanced image classification using CNNs, transfer learning, and GPU acceleration. Optimize models, implement data augmentation, and deploy in real-world scenarios.

• Coursera
• 9 hours 44 minutes
• Self-Paced
• Paid Course

Coursera Career Certificate

Vision & Audio AI Systems

Master production-ready AI systems that unify visual and audio data through advanced multimodal techniques, ETL pipelines, fusion algorithms, and transformer fine-tuning.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 2 courses

Khalifa University

Deep Learning for Computer Vision: Techniques & Applications

Master deep learning for computer vision using PyTorch—build CNNs, implement VGG, ResNet, YOLO, and U-Net, and tackle object detection and image segmentation with real datasets.

• Coursera
• 7 weeks, 2 hours a week
• Self-Paced
• Paid Course

Packt

AI Engineering and Deployment

Master TensorFlow, CNNs, RNNs, and AI agent frameworks like AutoGPT to build, deploy, and scale ML models with ethical considerations for real-world applications.

• Coursera
• 8 hours 58 minutes
• Self-Paced
• Paid Course