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Cranfield University: Computational Intelligence for Data Analytics option - MSc in Computational and Software Techniques in Engineering
| Institution | Cranfield University View institution profile |
|---|---|
| Department | Cranfield University |
| Web | https://www.cranfield.ac.uk |
| study@cranfield.ac.uk | |
| Telephone | +44 (0)1234 758083 |
| Study type | Taught |
MSc
Summary
Computationally intelligent data handling algorithms are crucial in a wide range of sectors that require fast and automated decision-making. These industries typically include financial, manufacturing, aerospace, automotive and defence.
This specialist option of the MSc Computational and Software Techniques in Engineering will enable you to develop a solid base of computer science skills and focused expertise, necessary to develop fast algorithms capable of dealing with a range of complex problems where intelligent decision-making or future predictions are based on understanding of data collections
| Level | RQF Level 7 |
|---|---|
| Entry requirements | A first or second class UK honours degree (or equivalent), in aeronautical, mechanical or electrical engineering or computer science or be applying as part of a recognised double-degree programme with their home EU institution. Entry level C programming experience is advisable but not required. Applications from candidates with lesser qualifications but with considerable relevant work experience will be considered. |
| Location | Cranfield Campus College Road, Cranfield Bedfordshire Milton Keynes MK43 0AL |
Summary
Computationally intelligent data handling algorithms are crucial in a wide range of sectors that require fast and automated decision-making. These industries typically include financial, manufacturing, aerospace, automotive and defence.
This specialist option of the MSc Computational and Software Techniques in Engineering will enable you to develop a solid base of computer science skills and focused expertise, necessary to develop fast algorithms capable of dealing with a range of complex problems where intelligent decision-making or future predictions are based on understanding of data collections
| Level | RQF Level 7 |
|---|---|
| Entry requirements | A first or second class UK honours degree (or equivalent), in aeronautical, mechanical or electrical engineering or computer science or be applying as part of a recognised double-degree programme with their home EU institution. Entry level C programming experience is advisable but not required. Applications from candidates with lesser qualifications but with considerable relevant work experience will be considered. |
| Location | Cranfield Campus College Road, Cranfield Bedfordshire Milton Keynes MK43 0AL |
Summary
In today's data-driven world, where vast amounts of information are generated every second, intelligent data analytics and advanced computing techniques are essential for building systems that can make fast, accurate, and automated decisions. The surge of data from IoT devices, social media, and business transactions has created an urgent need for AI-powered methods to process and interpret this data in real time. Mastering the ability to analyse and extract insights from these massive data sets — whether in batch or real-time — can provide significant competitive advantages in industries such as finance, manufacturing, retail, aerospace, automotive, and defence. In this course, you will develop a strong foundation in computer science, artificial intelligence and data analytics, essential for designing and validating cutting-edge algorithms. These skills will enable you to tackle complex challenges where AI-driven decision-making and predictive models are powered by Big Data, helping you apply effective, real-world solutions. This specialist pathway within the MSc Computational and Software Techniques in Engineering focuses on the key technologies for Big Data processing, including high-performance computing and cloud-based infrastructures. You will also dive deep into algorithm development, machine learning, and data analytics. Additionally, the course offers hands-on experience with industry-standard tools like Hadoop and Spark, ensuring you gain practical expertise in solving real-world problems using modern AI techniques.
| Level | RQF Level 7 |
|---|---|
| Entry requirements | A first or second class UK honours degree (or equivalent), in aeronautical, mechanical or electrical engineering or computer science or be applying as part of a recognised double-degree programme with their home EU institution. Entry level C programming experience is advisable but not required. Applications from candidates with lesser qualifications but with considerable relevant work experience will be considered. |
| Location | Cranfield Campus College Road, Cranfield Bedfordshire Milton Keynes MK43 0AL |
Summary
In today's data-driven world, where vast amounts of information are generated every second, intelligent data analytics and advanced computing techniques are essential for building systems that can make fast, accurate, and automated decisions. The surge of data from IoT devices, social media, and business transactions has created an urgent need for AI-powered methods to process and interpret this data in real time. Mastering the ability to analyse and extract insights from these massive data sets — whether in batch or real-time — can provide significant competitive advantages in industries such as finance, manufacturing, retail, aerospace, automotive, and defence. In this course, you will develop a strong foundation in computer science, artificial intelligence and data analytics, essential for designing and validating cutting-edge algorithms. These skills will enable you to tackle complex challenges where AI-driven decision-making and predictive models are powered by Big Data, helping you apply effective, real-world solutions. This specialist pathway within the MSc Computational and Software Techniques in Engineering focuses on the key technologies for Big Data processing, including high-performance computing and cloud-based infrastructures. You will also dive deep into algorithm development, machine learning, and data analytics. Additionally, the course offers hands-on experience with industry-standard tools like Hadoop and Spark, ensuring you gain practical expertise in solving real-world problems using modern AI techniques.
| Level | RQF Level 7 |
|---|---|
| Entry requirements | A first or second class UK honours degree (or equivalent), in aeronautical, mechanical or electrical engineering or computer science or be applying as part of a recognised double-degree programme with their home EU institution. Entry level C programming experience is advisable but not required. Applications from candidates with lesser qualifications but with considerable relevant work experience will be considered. |
| Location | Cranfield Campus College Road, Cranfield Bedfordshire Milton Keynes MK43 0AL |
Located in the rural village of Cranfield, Cranfield University is a specialist postgraduate institution and a global leader in technology, engineering, management and applied research. Its green campus offers a peaceful, focused environment for study, while remaining well connected—just 40 minutes from London by train.
Cranfield delivers education exclusively at postgraduate level, with over 5,000 students from around the world and a strong staff-to-student ratio that supports personalised learning. The University is widely recognised for its close collaboration with industry, governments and organisations, ensuring its teaching and research are highly relevant and impactful.
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