Transfer Learning Courses and Certifications

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

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

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

EDUCBA

Deep Learning with TensorFlow: Build Neural Networks

Master TensorFlow fundamentals and build neural networks from perceptrons to CNNs, implementing transfer learning for real-world image classification tasks.

• Coursera
• 5 hours 19 minutes
• Self-Paced
• 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
• 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

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

Coursera Credential

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

Coursera Credential

Satellite Imagery, Remote Sensing & Machine Learning

Master satellite imagery analysis and machine learning to transform raw Earth observation data into actionable environmental insights for GIS, climate, and sustainability applications.

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

Coursera Credential

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

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 Credential

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

Coursera Credential

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

Coursera

Zero-Shot & Few-Shot Learning: Master AI with Minimal Data

Master AI techniques that enable models to perform effectively with minimal labeled data through zero-shot and few-shot learning approaches for real-world applications.

• Coursera
• 3 hours 52 minutes
• Self-Paced
• Paid Course

Packt

From Recipe to Chef - Become an LLM Engineer

Master LLM engineering from fundamentals to deployment, covering data processing, model training, fine-tuning, prompt engineering, and building production-ready AI applications.

• Coursera
• 8 hours 30 minutes
• Self-Paced
• Paid Course