ICBMIS 2019

Data Science

Data Science

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Programme Duration

1 year

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Semesters

2 Semesters

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Level

Post Graduate

Criteria 

Our blended learning experience is open to graduates, post graduates and working professionals.

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Academic Year

2020-2021

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Fees per year

AED 17,000

Why choose this field?

From assisting management to make data-driven decisions to becoming a competent and strategic data analyst, data is a complex and essential part of any organisation. As we move to become a more data-driven world, the analytical skills needed to process information continue to be in high demand.

The programme aims to provide students with training in data science methods, with a focus on statistical perspectives, giving students knowledge and understanding to formulate and develop statistical models in a logical manner.

Programme description

Over 9 courses with a total of 52 credits, our Data Science programme prepares students with the latest job-ready skills needed to pursue roles like data analyst, business analyst, data scientist, machine learning engineer, data mining engineer, data architect, data engineer and more.

The programme covers an introduction to data science, visualization techniques, decision-making and predictive analysis, data modeling optimisation and big data analytics. Each module is designed to give students a comprehensive understanding of the field of data science, while also applying learnt skills to projects that will help build a portfolio of work. The course also covers tools like R, R studio, Tableau, Python, Hadoop, Spark, Hive and SQL, along with industry relevant projects.

Career opportunities

On completing this programme, students can build successful careers in a number of industries including IT, retail, healthcare, telecom, insurance, academia, supply chain, logistics and hospitality. It is ideal for working professionals in IT, analytics, big data and machine learning to grow their existing skill set and cover a growing area.

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What will students learn?

Learning outcome

Students will learn to comprehend organisational data, develop processes for managing data and use data to make key business decisions.

Learning outcome 2

Master the use of data visualisation and predictive models to increase the accuracy of predictions.

Learning outcome 3

Gain expertise to use a wide range of modern statistical tools and software like R, Python, Spark, Hadoop and Tableau.

Learning outcome 4

Create and validate regression models that can be used to determine the effects on a decision and its likely outcomes.

What will students achieve?

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