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The [course_title] course covers the fundamentals of deep learning with a special focus on TensorFlow.

Deep learning is a subset of machine learning in Artificial Intelligence (AI) and is concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. On the other hand, TensorFlow is an open-source software library for dataflow programming across a range of tasks. It is Google’s internally developed framework for deep learning.

The course teaches basic network architectures, including dense, convolutional and recurrent networks, and training techniques such as dropout or batch normalisation. Upon completion, you will be able to solve a couple of typical problems with neural networks and able to explore TensorFlow resources.


This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.


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Course Credit: Google

Course Curriculum

Diploma in TensorFlow and Deep learning
Lecture 1 01:06:00
Lecture 2 02:36:00
Lecture 3 00:57:00
Lecture 4 00:51:00
Lecture 5 00:53:00
Lecture 6 00:36:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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