Course Finder

Computational Analysis of Big Data

Computational Analysis of Big Data


Computational Analysis of Big Data

About this course

Walmart started using big data even before the term became recognized. Today, industries, governments, social media platforms, finance, and organizations alike use data and analytics to predict future needs to optimize sales, minimize cost, and maximize reach. With a hands-on approach and by working with problem-solving exercises that focus on practical implementations, this course introduces you to a large set of computational tools and techniques for dealing with large-scale data.

Syllabus

Syllabus Section A – Fall 2024

Go to syllabus

This is the most recent syllabus for this course

Syllabus Section B – Fall 2024

Go to syllabus

This is the most recent syllabus for this course

Syllabus Section C – Fall 2024

Go to syllabus

This is the most recent syllabus for this course

Pre-requisites

One year of computer science at university level and a course in algorithms and data structures. Knowledge of at least one programming language (e.g. Python, Javascript, Java, C++, Matlab).

Faculty

Lucian Leahu

Faculty

Ph.D. in Computer Science, Cornell University (2012). Previous experience as Assistant Professor at ITU Copenhagen (2015-2018), ERCIM Postdoctoral Fellow at the Swedish Institute of Computer Science (2012-2013),an and Project Leader in the Media Technology and Interaction Design Department at the Royal Institute of Technology (2014). With DIS since 2019.

Panagiota Katsikouli

Faculty

Ph.D. in Informatics, University of Edinburgh (2018). Currently lecturing as Faculty Member at the Open Institute of Technology (2023-present) and involved in Teaching and Research at the University of Copenhagen (2020–present). Previous experience as post-doctoral Researcher at the Technical University of Denmark (2019-2020), University College of Dublin (2019), and INRIA Lyon (2018-2019). Teaching and Research. With DIS since 2023.

Nicolai Frost Kolborg Jacobsen

Faculty

Head of Data Science at Corti (2019–present), leading a team to build a system that leverages Automatic Speech Recognition output to measure call quality. M.Sc. Dual Degree in Data Science, Technical University of Denmark & Korea Advanced Institute of Science and Technology (2017 and 2018, respectively). B.Sc. in Natural Science and IT, University of Copenhagen (2015).. Previous experience building forecasting models as Data Scientist at Scales (2018) and optimized equipment distribution with Python and integer programming as Business Intelligence Consultant at IQVIA (2015–2018). With DIS since 2022.

We’ll support you every step of the way.
Do you need advice?