23 August 2024
on course website
Artificial Intelligence and Machine Learning: Theory and Practice
In our age of burgeoning smart technology and automation we are already seeing the transformative potential of Artificial Intelligence and Machine Learning in fields as diverse as finance, medicine, and manufacturing. This course offers a hands-on introduction to this future-focused area of research.
You will begin with an introduction to the basics of programming in Python, in particular understanding object-oriented programming and its importance to deep learning. You will quickly proceed to an introduction to artificial intelligence, examining the fundamentals of supervised machine learning, including linear regression, logistic regression, neural networks, and gradient descent. In the second week of the course you will explore image processing, investigating transformations, convolutional filters, and edge detection, before an introduction to convolutional neural networks and some prominent CNN architectures such as VGG and ResNet. In the final part of the course, you will look at the core concepts of natural language processing, including sequence modeling, autoregressive models, and recurrent neural networks.
This intensive course offers both a theoretical introduction to artificial intelligence and machine learning concepts, and an opportunity to put this knowledge into action in solving small-scale practical problems from diverse domains.
This course would suit STEM students in undergraduate or entry-level postgraduate study. Basic knowledge of calculus and linear algebra is required, and some experience of coding is recommended. Prior experience of artificial intelligence, machine learning, or the Python programming language is not required.
By the end of this course, you will:
- Understand theoretical concepts of artificial intelligence and machine learning.
- Know how basic artificial intelligence and machine learning tools are used in practice.
- Know how to implement basic algorithms and train small networks for practical problems.
- Be able to identify and use relevant artificial intelligence and machine learning tools in research.
- Know how to implement and deploy artificial intelligence and machine learning algorithms on Google Cloud.
LMH Summer Programmes are designed to be eligible for credit, and we recommend the award of 7.5 ECTS / 4 US / 15 CATS for this course.
GBP 3980: This includes:
- All tuition, including lectures, seminars, and tutorials.
- Assessment, transcript of academic performance, and certificate.
- A co-curricular programme of skills workshops and guest speakers.
- Access to the Lady Margaret Hall College Library.
- Bed & Breakfast accommodation throughout your programme.
- Lunch and dinner in the College Dining Hall Monday to Friday.
- A full Social & Cultural Programme, including two excursions to other English cities per three-week programme session.
- A high-quality printed class photograph.
- Formal Graduation banquet.
on course website