Advanced Artificial Intelligence and Machine Learning: Computer Vision
Oxford, United Kingdom
DURATION
3 Weeks
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
10 May 2024*
EARLIEST START DATE
15 Jul 2024
TUITION FEES
GBP 3,980 / per course **
STUDY FORMAT
Distance Learning, On-Campus
* Applications are processed and offers are made on a rolling basis, and many courses fill up far in advance of the deadline so we recommend applying as early as possible.
** For a 3-week residential programme the fee is £3,980, including accommodation and meals. For a 3-week online programme the fee is £1,360.
Introduction
From self-driving cars and augmented reality to intelligent medical imaging helping doctors identify diseases more quickly, computer vision is a rapidly growing field within artificial intelligence and machine learning. In this course, students who are already familiar with the key theoretical foundations of artificial intelligence and machine learning will dive deeper into the exciting capabilities of this area of research and its applications.
You will begin with computer vision algorithms for classification, recognition, detection, and their implementation in deep learning libraries, before exploring autoencoders and variational autoencoders, and gaining insights into the training and application of generative adversarial networks. You will proceed to an in-depth examination of diffusion models, including score-based diffusion models, latent diffusion models, and Stable Diffusion. The final part of the course explores even more advanced topics, including the representation of 3D objects, vision transformers, video classification, and text-to-image generation.
This intensive course offers students theoretical understanding and practical experience in a range of advanced computer vision concepts and techniques, offering career skills as well as excellent foundations for future research.
Dates and Availability
Available as a Residential or Online course on the following dates:
Session 2: 15th July to 2nd August 2024
Ideal Students
This course would suit STEM students with intermediate-level experience in artificial intelligence, machine learning, and computer vision concepts and techniques, including those undertaking, or looking ahead to, graduate-level study or research.
Specifically, students in this course must have experience with the following topics:
- Knowledge of the deep learning libraries.
- Understanding of deep learning and convolutional neural networks.
- Strong background in optimization and probability.
- Familiarity with the Python programming language.
Admissions
Scholarships and Funding
Lady Margaret Hall does not offer scholarships or grants for participation in the LMH Summer Programmes, but many students find they are able to seek financial assistance from their home university or academic department. The best first point of contact is likely the Study Abroad / International Education Office at your university.
Program Outcome
By the end of this course, you will:
- Understand computer vision algorithms for classification, recognition, and detection, and their implementation in deep learning libraries.
- Know the different types of generative adversarial networks and their distinct contributions to controlled data synthesis and image generation.
- Be able to identify different diffusion models and assess their advantages in generative modeling.
- Be able to demonstrate awareness and understanding of the latest key research areas in computer vision.