Learn about deep learning with online courses and programs

Deep learning course curriculum

Build your knowledge of deep learning with virtual instruction that includes hands-on practice and projects inspired by real world scenarios. An online deep learning course can enable you to:

• Master the fundamentals of deep learning, including the different types of neural networks for supervised and unsupervised learning.

• Build different types of deep architectures, including convolutional networks, recurrent networks, and autoencoders.

• Understand how to use deep learning for different applications such as object recognition and computer vision, image and video processing, and more.

• Practice deep learning at scale with accelerated hardware and GPUs.

• Build models and algorithms using deep learning libraries such as Keras and PyTorch.

To understand deep learning, individuals can benefit from knowledge of electrical and computer engineering, computer science, and similar subjects. edX offers online courses that allow learners to study a variety of topics, including those related to deep learning, software engineering, and much more. ‌Sign up for an accelerated or enroll in a full degree program and start working toward a bachelor's degree or (for more advanced learners) a master’s degree in a relevant subject. You can also explore executive education programs specifically designed for busy professionals.

Explore careers in deep learning

Deep learning has found applications across various industries, driving advancements and revolutionizing traditional practices. Some of the fields that utilize deep learning include:

• Data science and machine learning: Data scientists use deep learning algorithms to analyze and interpret vast datasets, extracting valuable insights and patterns to support data-driven decision making.

• Autonomous systems: In fields such as self-driving cars and drones, deep learning is crucial for perception, decision making, and control, enabling these systems to navigate and operate autonomously.

• Healthcare and medical imaging: Deep learning is used for medical image analysis, disease detection, and prediction, aiding radiologists and clinicians in diagnosing and treating patients.

• Finance and trading: In finance, deep learning models are employed for fraud detection, risk assessment, stock market analysis, and algorithmic trading.

• Entertainment and gaming: Game developers use deep learning for character animation, behavior modeling, and enhancing gameplay experiences.

• Manufacturing: Deep learning is used for predictive maintenance, quality control, and process optimization in manufacturing settings.

As deep learning continues to advance, its applications will likely expand to other fields, offering promising career opportunities in cutting-edge technology and innovation.