Deep Learning Specialization
Master Deep Learning, and Break into AI
Об этой специализации
If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach. You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice. AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work. We will help you master Deep Learning, understand how to apply it, and build a career in AI.
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- Intermediate Specialization.
- Some related experience required.
Neural Networks and Deep Learning
- 4 weeks of study, 3-6 hours a week
- English, Chinese (Traditional), Chinese (Simplified), Portuguese (Brazilian), Korean, Turkish, Japanese
О курсеIf you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "superpower" tha
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
- 3 weeks, 3-6 hours per week
- English, Chinese (Traditional), Chinese (Simplified), Korean, Turkish
О курсеThis course will teach you the "magic" of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand what drives performance, and be able to more systematically get good results. You will also
Structuring Machine Learning Projects
- 2 weeks of study, 3-4 hours/week
- English, Korean, Chinese (Traditional), Chinese (Simplified)
О курсеYou will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been taught elsewhere, and is
Convolutional Neural Networks
- 4 weeks of study, 4-5 hours/week
- English, Chinese (Traditional), Korean
О курсеThis course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging fro
- English, Chinese (Simplified)
О курсеThis course will teach you how to build models for natural language, audio, and other sequence data. Thanks to deep learning, sequence algorithms are working far better than just two years ago, and this is enabling numerous exciting applications in
Co-founder, Coursera; Adjunct Professor, Stanford University; formerly head of Baidu AI Group/Google Brain
Teaching Assistant - Younes Bensouda Mourri
Mathematical & Computational Sciences, Stanford University, deeplearning.ai
Head Teaching Assistant - Kian Katanforoosh
Lecturer of Computer Science at Stanford University, deeplearning.ai, Ecole CentraleSupelec
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