PickAClass · AI, Tech & Engineering

AI & Machine Learning

Learn the fundamentals of artificial intelligence and machine learning, from classical algorithms to model deployment. Covers supervised, unsupervised, and reinforcement learning.

11 subcategories · 980 courses total

AI & ML Foundations

Start your journey into artificial intelligence by learning the fundamental concepts, history, and different types of machine learning algorithms.

204 courses

Deep Learning

Dive into the world of artificial neural networks. Learn to build, train, and optimize deep learning models for complex tasks using frameworks like TensorFlow and PyTorch.

85 courses

Time Series Forecasting

Analyze and predict future values based on time-ordered data. Master classical methods like ARIMA and modern deep learning approaches like LSTMs for forecasting.

85 courses

Computer Vision

Enable machines to see and interpret the visual world. Learn about image classification, object detection, and segmentation using deep learning.

83 courses

Natural Language Processing (NLP)

Teach computers to understand, process, and generate human language. Cover topics from text preprocessing and sentiment analysis to transformers and large language models.

82 courses

Unsupervised Learning

Discover hidden patterns and structures in unlabeled data. Explore techniques like clustering, dimensionality reduction, and association rule mining.

80 courses

AI Ethics and Governance

Understand the societal impact of artificial intelligence. Learn about fairness, accountability, transparency, and bias in AI systems, and explore principles for responsible development.

80 courses

Supervised Learning

Master the most common type of machine learning. Learn to build models that make predictions based on labeled data, covering regression and classification tasks.

79 courses

Generative AI

Explore the cutting-edge of AI that creates new content, from text and images to code. Understand models like GANs, VAEs, and large language models.

79 courses

MLOps (Machine Learning Operations)

Learn the principles and practices for deploying, monitoring, and maintaining machine learning models in production. Bridge the gap between data science and DevOps.

79 courses

Reinforcement Learning

Learn to build intelligent agents that make optimal decisions through trial and error. Explore concepts like Q-learning, policy gradients, and their applications.

44 courses