Deep Learning Specialist Learning Path

Comprehensive ML course covering regression, classification, clustering, deep learning, NLP, reinforcement learning.

Master TensorFlow 2 and Keras. ANNs, CNNs, RNNs, GANs, deployment.

This course, part of the Deep Learning Specialization, focuses on convolutional neural networks (CNNs) and their application to computer vision tasks like image classification. You will learn to build and train CNNs and apply them to visual detection and recognition tasks.

This course covers the basic principles of machine translation, focusing on statistical and neural machine translation, including the current state-of-the-art neural machine translation technology which uses deep learning methods.

This beginner-level course introduces the concepts of linear algebra that are relevant to AI, machine learning, and deep learning.

Part of the DeepLearning.AI TensorFlow Developer Professional Certificate, this course teaches you how to solve time series and forecasting problems in TensorFlow. You'll learn best practices for preparing data, and explore how RNNs and ConvNets can be used for prediction.

A professional certificate program from IBM that covers the fundamentals of AI engineering, including machine learning, deep learning, and AI ethics. It has a strong focus on practical, job-ready skills.

A guided project that teaches the fundamentals of using TensorFlow for image classification. You will build, train, and evaluate a neural network to classify images from the CIFAR-10 dataset.

A hands-on project where you'll train a Bidirectional Neural Network and LSTMs based deep learning model to detect fake news from a given news corpus. This is a practical skill for media companies to automatically predict the authenticity of news articles.

This specialization provides a deep dive into modern methods for analyzing time series and sequential data, with a focus on deep learning models and their applications.

Offered by Michigan State University, this specialization provides a thorough introduction to game design and development using Unity. It is a series of courses that includes hands-on projects where you build multiple 2D and 3D games.

A three-course specialization from the University of Michigan that teaches beginning and intermediate concepts of statistical analysis using Python, covering data design, exploration, and modeling.

Generative Adversarial Networks (GANs) Specialization

Deep Learning A-Z: Hands-On Neural Networks

Natural Language Processing with Deep Learning

Chatbot Development with Python and Deep Learning

This course covers RNNs, LSTMs, and GRUs in TensorFlow. It includes projects on time series prediction, music generation, language translation, image captioning, spam detection, and action recognition.

Learn DeepLearning.AI Build Basic Generative Adversarial Networks (GANs)

Learn DeepLearning.AI Neural Networks and Deep Learning