Analytics and Data Science

1. Introduction to Deep Learning:
   • An overview of deep learning practice
   • Includes practical demonstrations and guidance of Tensorflow
2. Big Data:
   • Data protection, security, and ethics
   • Best practice analytics
   • Practical application of the Vertica Analytic Database
   • Overview of the Mongo Database
3. Introduction to Machine Learning:
   • An overview of machine learning methods
   • Decision trees, random forests, and gradient boosting
   • Instance based learning
   • Learning with small data sets
4. Introduction to R:
   • An overview of the R programme
   • How R is used and applied in a variety of practical situations

1. Deep Learning topics:
   • A more detailed insight into deep learning and neural networks
2. Natural Language Processing (NLP):
   • NLP in social media
   • Sentiment analysis
   • Information retrieval
3. Machine Learning topics:
   • Bandits, learning, and search
   • Interpreting classifiers
   • Learning under different training and testing distributions
   • Visual recognition and tracking
4. R topics and optimisation:
   • Machine Learning in R
   • Classifier Evaluation
   • Optimisation meets data science using Java

There are no specific eligibility requirements to book a place on the Summer School. We welcome attendees (students, researchers, academics and professionals) in the emerging fields of big data, data science and analytics who would like to find out more or be updated on the current trends and developments in this exciting and fast-developing field.

We accept applicants from all levels and experience from around the world and offer a range of introductory, intermediate and advanced courses to suit your needs.

Whilst we don't restrict access to courses, when selecting the courses that make up your programme please pay attention to our recommended prerequisites. These prerequisites are stipulated to ensure that all attendees make the best out of their time with us.

If you are unsure whether a certain published course is right for you, please do not hesitate to contact us at iadssum@essex.ac.uk and a member of the IADS team will be happy to advise you on whether a course is suitable for your requirements and skillsets.

What is included in the fees?

Applications for 2019 have now closed. To register your interest for 2020, please contact summer_schools_hub@essex.ac.uk

• Access to one or two weeks’ worth of courses, depending on your selection.
• A tailored programme and access to preparatory and bonus materials from our providers using a secure drive.
• Exclusive access to multiple keynote events provided over both weeks.
• Access to over five organised social activities designed to create long-lasting connections with fellow delegates and providers, including a local tour, games night, and our novel Summer School Speed Networking session.
• One ticket to the opening Evening Reception on Monday 29 July 2019.
• One ticket to a field-trip excursion to a popular British tourist destination on Saturday 3 August 2019.
• One ticket to the IADS Formal Dinner on Wednesday 7 August 2019.
• Complimentary car parking permit for the duration of your stay.
• Support from the IADS team before your arrival and throughout your stay.
• A delegate pack full of resources, information, and memorabilia from your time with us.
• Hardcopy certification upon completing your course, endorsed by the University of Essex and the Institute for Analytics and Data Science.

Please note the fee doesn't include accommodation. You will be able to optionally book this with us at a discounted rate.

Early registration (before 10 June 2019)

Standard registration (11 June 2019 - 9 July 2019)

Late registration (10 July 2019 - 22 July 2019)

You can book accommodation on our Colchester Campus (where the Summer School is taking place) at very affordable rates.

Our accommodation offers your own room with en-suite facilities, linen and shared access to a kitchen, utensils and crockery, so you can socialise with other delegates too.

Once payment for attendance has been accepted, you will be sent instructions as to how to book our optional discounted accommodation.