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Overview
What you will study
This Advanced End-to-End Machine Learning course offered by University of St Andrews introduces you to basic neural networks using the scikit-learn Python package, covering the key concepts, techniques and technologies for training and prediction using multilayer perceptrons and the Keras Python package.
The course also includes specialised and advanced coverage of modern Deep Learning techniques and tools, based on both the Keras and TensorFlow Python packages.
Advanced Python code is supplied and explained for each topic. Your primary learning outcome is the ability to deploy and assess the state-of-the-art technologies that underpin modern AI-based machine learning and data science.
Programme Structure
The program focuses on:
- custom neural net models using Tensorflow
- deep computer vision using convolutional neural networks
- modelling time-series data with recurrent neural networks
- artificial intelligence (AI) generation of images using autoencoders
- generative adaptive networks
- diffusion techniques
Key information
Duration
- Part-time
- 41 days
Start dates & application deadlines
- StartingApplication deadline not specified.
More details
End date: Sunday 17 August
Language
English
Delivered
Online
- Self-paced
Campus Location
- St Andrews, United Kingdom
Disciplines
Machine Learning View 12 other Short Courses in Machine Learning in United KingdomWhat students do after studying
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Academic 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
- The course is suitable for advanced Python programmers
- The course is aimed at professionals with a high level of numeracy who are seeking to understand the core concepts, methods and technologies that underpin modern Deep Learning using artificial neural networks (ANNs).
Technological requirements
- A good internet connection is more important than powerful computational equipment.
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
-
International Applies to you
Applies to youNon-residents1800 GBP / full≈ 1800 GBP / full -
Domestic Applies to you
Applies to youCitizens or residents1800 GBP / full≈ 1800 GBP / full
Additional Details
Book before 7 July to get access to the course for a discounted price of £950.
Funding
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