Overview
The first course of this TensorFlow 2 for Deep Learning Specialization offered by Coursera in partnership with Imperial College London will guide you through the fundamental concepts required to successfully build, train, evaluate and make predictions from deep learning models, validating your models and including regularisation, implementing callbacks, and saving and loading models.
The second course will deepen your knowledge and skills with TensorFlow, in order to develop fully customised deep learning models and workflows for any application. You will use lower level APIs in TensorFlow to develop complex model architectures, fully customised layers, and a flexible data workflow. You will also expand your knowledge of the TensorFlow APIs to include sequence models.
The final course specialises in the increasingly important probabilistic approach to deep learning. You will learn how to develop probabilistic models with TensorFlow, making particular use of the TensorFlow Probability library, which is designed to make it easy to combine probabilistic models with deep learning. As such, this course can also be viewed as an introduction to the TensorFlow Probability library.
Prerequisite knowledge for this Specialization is python 3, general machine learning and deep learning concepts, and a solid foundation in probability and statistics (especially for course 3).
Applied Learning Project
Within the Capstone projects and programming assignments of this Specialization, you will acquire practical skills in developing deep learning models for a range of applications such as image classification, language translation, and text and image generation.
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Visit programme websiteProgramme Structure
Courses include:
- Getting started with TensorFlow 2
- Customising your models with TensorFlow 2
- Probabilistic Deep Learning with TensorFlow 2
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 3 months
- 10 hrs/week
Start dates & application deadlines
Language
Delivered
- Self-paced
Disciplines
Computer Sciences Artificial Intelligence Machine Learning View 265 other Short Courses in Machine Learning in United StatesExplore more key information
Visit programme websiteAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Intermediate Level
- Python 3
- Knowledge of general machine learning concepts
- Knowledge of the field of deep learning
- Probability and statistics
Make sure you meet all requirements
Visit programme websiteTuition Fee
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 3 months. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 3 months.
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Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.