Machine Learning and Artificial Intelligence Services on AWS (Amazon Cloud)



Overview

Being the world’s most comprehensive and broadly adopted cloud platform, AWS offers a wide range of services. It is not a surprise that a large number of customers are using such services to become more agile, productive and reduce costs.

One of the powerful aspects of AWS is that it provides ready-to-use machine learning and artificial intelligence services. These services are based on well trained and tested models that make it easy for users to just provide data to receive the output they are looking for (e.g. a prediction).

Some of those services include platforms for text/image/video data processing and analysis. In addition, the services also include text-to-speech and speech-to-text engines. You will learn how to use these services via the AWS Console and, if time permits, programmatically using Python. Training covers the high-level idea behind the deep learning models powering the services and practical aspects of those services.

By the end of the course you will have access to all course material (e.g. slides, code examples and so on).

Please note: This course requires a user account on AWS.

This course will close for enrolment 2 days prior to the start date

Programme details

9.45am
Registration and welcome

10.00am
Introduction, AWS account setup and basic concepts:

  • AWS account creation and configuration
  • Amazon Transcribe
  • Amazon Translate
  • Python code examples for using the above services

11.20am
Break

11.40am
Comprehend, Lex and Polly:

  • Amazon Comprehend
  • Amazon Lex
  • Amazon Polly
  • Python code examples for using the above services

1.00pm
Lunch

2.00pm
Rekognition and Textract:

  • Overview of Amazon Rekognition
  • Object and Scene Detection
  • Facial Analysis
  • Face/Celebrity recognition
  • Face comparison
  • Text extraction from image and PDF files
  • Python code examples for using the above services

3.20pm
Break

3.40pm
SageMaker for Machine Learning:

  • Overview of Amazon SageMaker
  • Different types of instances and their pricing
  • Create a Notebook Instance
  • SageMaker’s builtin machine/deep learning algorithms
  • How to build, train and deploy a SageMaker machine/deep learning algorithm

4.40pm
Course conclusion and wrap up

5.00pm
Course ends

Fees

Description Costs
Tuition fee £95.00

Funding

If you are in receipt of a UK state benefit or are a full-time student in the UK you may be eligible for a reduction of 50% of tuition fees.

Concessionary fees for short courses

Tutor

Dr Noureddin Sadawi

Tutor

Dr Noureddin Sadawi specialises in machine/deep learning and data science. He has several years’ experience in various areas involving data manipulation and analysis. He received his PhD from the University of Birmingham. He is the winner of two international scientific software development contests - at TREC2011 and CLEF2012.

Noureddin is an avid scientific software researcher and developer with a passion for learning and teaching new technologies. He is an experienced scientific software developer and data analyst. Over the last few years, he has been using R and Python as his preferred programming languages.

He has also been involved in several projects spanning a variety of fields such as bioinformatics, textual/image/video data analysis, drug discovery, omics data analysis and computer network security. He has taught at multiple universities in the UK and has worked as a software engineer in different roles. Currently he holds the following part-time roles: senior content developer and lecturer at the University of London; international trainer with O'Reilly and Pearson; short course trainer and instructor at Goldsmiths University, London as well as a lecturer at the University of Oxford. He is the founder of SoftLight LTD, a London-based company that specialises in data science and machine/deep learning where he works as a consultant providing advice and expertise in these areas. Currently he is a member of the organising committee of this international conference: https://ilcict.ly/. A list of his publications can be found here.

IT requirements

The University of Oxford uses Microsoft Teams for our learning environment, where students and tutors will discuss and interact in real time. Joining instructions will be sent out prior to the start date. We recommend that you join the session at least 10-15 minutes prior to the start time – just as you might arrive a bit early at our lecture theatre for an in-person event.

If you have not used the Microsoft Teams app before, once you click the joining link you will be invited to download it (this is free). Once you have downloaded the app, please test before the start of your course. If you are using a laptop or desktop computer, you will also be offered the option of connecting using a web browser. If you connect via a web browser, Chrome is recommended.

Please note that this course will not be recorded.

Terms & conditions for applicants and students

Information on financial support