Aspects of Advanced Analytics (2020)

Welcome to Aspects of Advanced Analytics




Description:

Big Data is being collected in ever larger amounts, e.g., from the (geo-social) web, social media, sensors/IoT devices in cyber-physical systems, or scientific experiments. However, it is necessary to go beyond merely storing and querying data to get a full overview and understanding. Instead, advanced analytics (data mining, prediction, forecasting,..) is applied to the huge data volumes to extract trends and patterns, and use historical data to predict future events, so-called predictive analytics. Recently, optimization has been added on top, resulting in so-called prescriptive analytics that prescribes the best course of action given the data and associated predictions and optimization goals. Other types of advanced analytics concern specific types of data such as sensor time series.
Traditional data analytics systems do not scale, and/or support only some of the tasks, or do not support the deep requirements for specific types of data, resulting in poor scalability, poor developer productivity and/or lack of functionality.
This course will cover selected aspects of advanced analytics including concepts, algorithms, and systems, with focus on 2 emerging areas: prescriptive analytics and time series analytics. The course will feature a mix of theoretical concepts and algorithms with practical hands-on exercises using specific advanced analytics systems on a number of realistic case datasets.

Prerequities: 

A general background in computer science, and general familiarity with database management and analytics, as can be achieved through undergraduate courses in databases and data mining/machine learning, is expected. Participants who have taken graduate data management and/or analytics courses will benefit from this additional background.


Organizer: Professor Torben Bach Pedersen


Lecturers: Postdoc Laurynas Siksnys, Postdoc Nguyen Ho, Professor Torben Bach Pedersen


ECTS: 2

Time: December 9-11

Place: Aalborg (this course will take place with physical attendance)

Zip code: 

City: 

Number of seats: 20

Deadline: November 18

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.