Duration

5 Weeks

Starting Date

Jun 2019

About Course

Data Analytics

This course is designed to equip participants to understand the data science field, data analysis and the various methods, processes, tools and algorithms used to extract and identify data from both structured and unstructured sources. 

They will learn how to organise, analyse and interpret data,  including information recognition,preparation for processing of data, creating reports and presentation of findings. 

The course will be delivered over 6 classroom days in addition to independent study and research, and will constitute lectures, presentations, tasks and assignments. Pedagogical practices in the course include student ownership and active participation, activities of searching, sharing and elaborating knowledge, conducting tasks and critical reflection on one’s own activity.

Course contents:

1.Data fundamentals
2.Data science tools
3.Data collection management
4.Data wrangling
5.Summarising
6.Collating and presenting data

Partner

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Kajaani University of Applied Sciences (KAMK)

Finland has one of the most innovative and progressive higher education systems in the world.Kajaani University of Applied Sciences (KAMK) is a leading Finnish university in the implementation of new academic and research methodologies in the ICT industry.

KAMK’s Advanced IT Studies is a reputable and globally accepted certificate program serving as a valuable supplement to post-graduates and professionals. Taught by leading faculty from across the globe, this study program constitutes a series of courses that train experts who are familiar with different data sources, to fluently pre-process big data (combine, clean, detect anomalies) and to train them to independently extract value out of data (data centre platforms, data analytics, machine learning, artificial intelligence, web applications).

This program enables experts having strong practical skills to implement solutions and applications in practice.

The courses will be delivered in a blended ecosystem constituting weekend classes, online lectures, research, independent study, group assignments and tests.

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Fee

On Request

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