Advanced Unsupervised Learning Learning Path

Learn Transformers, explained: Understand the model behind GPT, BERT, and T5

State-of-the-Art Machine Learning Papers Implementation

This course teaches you how to use R to apply clustering, dimensionality reduction, and anomaly detection techniques to explore and analyze unlabeled datasets, including algorithms like k-means, hierarchical clustering, and DBSCAN.

Learn DeepLearning.AI Unsupervised Learning, Recommenders, Reinforcement Learning

A nine-module course covering the role of machine learning and AI in financial services. It delves into key methodologies, algorithm selection, and includes case studies with functional code.

An intermediate-level course for data scientists and ML engineers on building models with limited labeled data. It covers zero-shot and few-shot learning techniques, applying pre-trained models, semantic embeddings, and transfer learning.

This professional certificate teaches how to build and train deep learning models using PyTorch. It covers applying transfer learning and fine-tuning to pretrained models for computer vision and natural language processing.

A three-day lecture-based course providing engineers with deep knowledge and hands-on experience with machine learning design and modelling techniques in an industrial context.

For those with some machine learning experience, this course provides a deeper dive into deep learning with TensorFlow. It covers advanced topics like building custom neural networks, and working with text and sequence data.

An advanced course focusing on the practical application of data science and machine learning to solve real-world cybersecurity problems. It includes over 30 hands-on labs.

Professional Machine Learning Engineer Certification

IBM Watson Machine Learning Professional Certificate

Learn DeepLearning.AI Advanced Learning Algorithms