Master of Science in Industrial Data Analytics (MScIDA) 12 months Postgraduate Programme By Lingnan University, Hong Kong |TopUniversities

Programme overview

Main Subject

Data Science and Artificial Intelligence

Degree

MSc

Study Level

Masters

Study Mode

On Campus

The demand for master programme regarding Industrial Data Analytics has never been more critical, considering today’s rapidly evolving industrial landscape. With the widespread adoption of advanced technologies like the Industrial Internet of Things (IIoT), smart sensors, and artificial intelligence (AI), industries urgently need to enhance their ability to collect, store, manipulate, integrate, visualize, analyse, and leverage vast amounts of data. This is essential for streamlining industrial processes, predicting maintenance needs, improving operational efficiency, facilitating decision-making and finally maintaining competitive advantages. Currently, there is a shortage of professionals with the specialized skills required to handle industrial data and apply analytics to address real-world challenges in industrial sectors such as manufacturing, energy, transportation, logistics, and healthcare.

This Master of Science in Industrial Data Analytics (MScIDA) programme can provide individuals with the data-driven knowledge, skills, and practical experience required to excel in these industrial sectors. It equips students with a solid understanding of data collection, storage, manipulation, integration, visualization, and analysis techniques. The programme also familiarizes students with industry-standard tools and technologies from automatic control, industrial engineering, computer science, applied mathematics, business management, etc. Through hands-on projects and real-world applications, students learn to apply data analytics to make informed decisions and derive actionable insights on behalf of specialized industrial sectors, preparing them to lead the way in smarter, more efficient industrial operations.

Programme overview

Main Subject

Data Science and Artificial Intelligence

Degree

MSc

Study Level

Masters

Study Mode

On Campus

The demand for master programme regarding Industrial Data Analytics has never been more critical, considering today’s rapidly evolving industrial landscape. With the widespread adoption of advanced technologies like the Industrial Internet of Things (IIoT), smart sensors, and artificial intelligence (AI), industries urgently need to enhance their ability to collect, store, manipulate, integrate, visualize, analyse, and leverage vast amounts of data. This is essential for streamlining industrial processes, predicting maintenance needs, improving operational efficiency, facilitating decision-making and finally maintaining competitive advantages. Currently, there is a shortage of professionals with the specialized skills required to handle industrial data and apply analytics to address real-world challenges in industrial sectors such as manufacturing, energy, transportation, logistics, and healthcare.

This Master of Science in Industrial Data Analytics (MScIDA) programme can provide individuals with the data-driven knowledge, skills, and practical experience required to excel in these industrial sectors. It equips students with a solid understanding of data collection, storage, manipulation, integration, visualization, and analysis techniques. The programme also familiarizes students with industry-standard tools and technologies from automatic control, industrial engineering, computer science, applied mathematics, business management, etc. Through hands-on projects and real-world applications, students learn to apply data analytics to make informed decisions and derive actionable insights on behalf of specialized industrial sectors, preparing them to lead the way in smarter, more efficient industrial operations.

Admission Requirements

6+
79+

1 Year
Sep

  • Candidates are required to submit references or letter(s) of recommendation for acceptance

Tuition fees

Domestic
36,860 USD
International
36,860 USD

Scholarships

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