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Specialisation Studies

Big Data Analytics

Prepare yourself for undertaking research at the cutting edge of creating intelligent services

Information

Educational level: Master (EQF7)

Date: 6.4.2017-31.3.2018

ECTS: 30

Language: English

Price: 250 €

Programme Co-ordinator: Magnus Westerlund, Programme Director, Department of Business Management and Analytics

”Intelligent software solutions is the opportunity for the coming decade.”

MAGNUS KAJ MIKAEL

Magnus Westerlund, Programme Director

Application

17.1-19.3.2017

Submit application

Today the same amount of information is created by computers and users around the world in 48 hours, as was created from the beginning of humanity until year 2003. Software encompasses an increasing amount of industries, and as Internet of Things (IoT) solutions become more common, big data analytics must be used to process the data they generate. To find patterns in and being able to handle this enormous amount of data opens for better and more precise fact-based decision-making. Companies and organisations have already realized the opportunities this brings and there is a continuously growing demand of trained big data analytics developers today.

Big Data Analytics specialisation studies gives you an in-depth understanding of how to make use of data in order to create insights. The intended student for these specialisation studies is someone with a programming background who wants to understand how to employ machine learning methods in a business environment. The program is arranged so that you rapidly gain a broad understanding of the essential concepts of big data analytics; descriptive and predictive modelling, as well as optimization. The program emphasizes the importance of understanding how to build analytical solutions with production level code.

As a student you will be involved in projects connected to real-world problems that includes elements of both group work and individual achievements. The focus on real-world problems emphasizes disruptive problem solving through analytics service development. Communication and business acumen is emphasized both through data visualization and traditional pitching.

Study alongside work

The Specialization Studies in Big Data Analytics are tailored so that you can attend them alongside full-time employment. During each course you will attend approximately six afternoon lectures at Arcada University of Applied Sciences in Arabianranta, Helsinki, mainly Thursdays and Fridays between 13-18 every other week. The rest of your studies are conducted independently.

Programme Contents

This programme will cover the following subjects. For more information see the curriculum from the link above.

  • Introduction to Analytics and Optimization, 5 ECTS
  • Big Data Analytics, 5 ECTS
  • Machine Learning for Predictive Problems, 5 ECTS
  • Visual Analytics, 5 ECTS
  • Machine Learning for Descriptive Problems, 5 ECTS
  • Analytical Service Development, 5 ECTS

These specialisation studies offer you


1.

Research at the cutting edge of creating intelligent services, working alongside scholars and industry in their area.

2.

Grounding in the scope and theories of machine learning and the challenges of analytics service design

3.

Develop detailed knowledge and understanding of how these disciplines blend together in tackling the real problems that face organisations

4.

Development of these disciplines in your organisation, be it in a theoretical, empirical or policy-oriented manner

A word with one of our current students

Salvatore Della Vecchia

Salvatore della Vecchia

Data analyst at Infotool, Helsinki, student of BDA at Arcada

What made you apply to the specialisations studies in BDA at Arcada?

It was my boss who found out about these studies and suggested I’d attend. It’s a good opportunity for our company. From our current projects it’s clear that there is a high demand for skilled professionals who has the latest knowledge in extracting analysis and insights from data. We provide business intelligence and know just how much big data analytics has developed these last few years, so this was a great way to gain the latest skills.

How would you describe your studies?

One thing I really appreciate is that the education isn’t just theoretical, but we get to work with real data sets. I’m just about to start the last course where we work with actual data from a real company, which is both really interesting and the best way to learn. I appreciate Arcada’s approach to education, that it’s important to study the theory, but equally important to get to do real programming and utilize what you’ve learned. This was something that I missed at my university in Italy, where the studies were mainly theoretical.

How has it been to study alongside work?

Of course the studies are intense and you have to be prepared to work hard, but it’s worth it. The content has been great. I’ve especially enjoyed going through visual analytics techniques and advanced data mining – something that is hard to find a place to study, since not many are using these advanced techniques yet. To sum it up, yes, I would definitely recommend these studies to others!

Timetable

The curriculum consists of six courses (5 ECTS credits each) that focus on how to program intelligent services using analytical and machine learning methods.

Date Module
Spring 2017 Introduction to Analytics and Optimization
Spring/Summer 2017 Big Data Analytics
Autumn 2017 Machine Learning for Predictive Problems
Autumn 2017 Visual Analytics
Winter 2017 Machine Learning for Descriptive Problems
Winter 2017-18 Analytical Service Development

For more information about these modules see the curriculum from the link in the menu at the top of the page.

Application

You can apply to this programme during the application time 17.1-19.3.2017.

Submit your application and Arcada will contact you with further information.

Apply now!

Submit application

The Curriculum

The curriculum consists of six courses (5 ECTS credits each) that focus on how to program intelligent services using analytical and machine learning methods. Each of the courses are thought through solving programming problems were the students can make use of Arcada’s Nvidia-sponsored Big Data Lab. The lab enables students to learn how to make use of GPU-accelerated models for processing big data.

During each course you will attend approximately six afternoon lectures at Arcada University of Applied Sciences in Arabianranta, Helsinki, mainly Thursdays and Fridays between 13-18 every other week. The rest of your studies are conducted independently.


Module 1

Introduction to Analytics and Optimization

In this course, you will be introduced to the concepts and methods in information analytics, with a special focus on the notion of optimization as the basis of prescriptive analytics and for creating the learning machine. You will be introduced to the process of problem solving in analytics from data understanding and preprocessing, through modelling choices and implementation until the interpretation, visualization and utilization of the analysis. We will look at typical real-life applications of information analytics from various domains (marketing, finance, and others depending also on the student’s backgrounds and interests). The course will provide hands-on lectures to performing the steps of modelling and analysis.


Module 2

Big Data Analytics

You are given an overview of machine learning and how to utilize big data. The methods for descriptive and predictive modelling are introduced for small data, and you are then given an explanation for how similar models can be modified to work with big data. You will be introduced to the analytical process; big data tooling, data-related requirement handling, domain knowledge, modelling and verification of results.


Module 3

Machine Learning for Predictive Problems

You learn a practical approach for predicting with Machine Learning with all the steps starting from data acquisition and preparation, search for optimal parameters, to comparison of different methods and evaluation of results. You can employ a linear model for regression and classification, train neural networks, build data features with deep learning, represent and process natural text with numerical methods.


Module 4

Visual Analytics

You learn how to lead in turbulent times through data-driven management. You also learn to understand how to become an agent of change for transforming data into insights. People are often visual beings and therefore the focus of the course is on reducing information, through algorithms, that can then be visualized. You develop an understanding of visual analytical methods as a communication medium for business intelligence.


Module 5

Machine Learning for Descriptive Problems

You learn to efficiently handle massive datasets and extract hidden knowledge from data. You understand how to employ classification and clustering algorithms on three different types of data: text, streaming and graph. You acquire knowledge of methods and programming tools for processing big data on distributed/cloud systems.


Module 6

Analytical Service Development

You develop an understanding for planning the analytical process; data-related requirement handling, domain knowledge/modelling expertise and verification of results. Each student completes an industry cap-stone project as part of the course.

Need more information?
Ask us anything!

Magnus Westerlund, Programme Director
Department of Business Management and Analytics
magnus.westerlund@arcada.fi
tel. 0207 699 540

For more information about the application process, please contact

Stig Blomqvist, Further Education Planner
Arcada Further Education
stig.blomqvist@arcada.fi
tel. 0207 699 501