Postgraduate Certificate in Computational Methods in Engineering

Saturday, 11 October 2025 00:54:21

International applicants and their qualifications are accepted

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Overview

Overview

Computational Methods in Engineering

is a postgraduate program designed for professionals seeking to enhance their skills in using computational tools and techniques to solve complex engineering problems.
Some of the key areas of focus include computational fluid dynamics, finite element analysis, and numerical methods. These skills are essential for tackling real-world engineering challenges in fields such as aerospace, civil, and mechanical engineering.
The program is ideal for those who want to stay up-to-date with the latest advancements in engineering technology and improve their ability to analyze and model complex systems.
By completing this program, learners will gain a deeper understanding of how to apply computational methods to engineering problems, leading to improved design, optimization, and simulation capabilities.
If you're looking to take your engineering career to the next level, explore the Postgraduate Certificate in Computational Methods in Engineering and discover how you can harness the power of computation to drive innovation and success.

Computational Methods in Engineering is a cutting-edge Postgraduate Certificate that empowers students to harness the power of computational techniques to drive innovation in the engineering sector. By leveraging advanced tools and methodologies, learners will gain a deep understanding of numerical analysis, computational fluid dynamics, and finite element analysis. This course offers key benefits such as enhanced problem-solving skills, improved collaboration, and increased employability. With a strong focus on industry-relevant applications, graduates can expect exciting career prospects in fields like aerospace, civil, and mechanical engineering. Unique features include access to state-of-the-art facilities and expert guest lectures.

Entry requirements

The program operates on an open enrollment basis, and there are no specific entry requirements. Individuals with a genuine interest in the subject matter are welcome to participate.

International applicants and their qualifications are accepted.

Step into a transformative journey at LSIB, where you'll become part of a vibrant community of students from over 157 nationalities.

At LSIB, we are a global family. When you join us, your qualifications are recognized and accepted, making you a valued member of our diverse, internationally connected community.

Course Content

•
Finite Element Method (FEM) • Computational Fluid Dynamics (CFD) •
Numerical Methods for Partial Differential Equations (PDEs) •
Computational Mechanics •
Finite Difference Method (FDM) •
Computational Multiphysics •
Numerical Optimization Techniques •
Computational Geometry and Mesh Generation •
Computational Physics •
Machine Learning in Engineering

Assessment

The evaluation process is conducted through the submission of assignments, and there are no written examinations involved.

Fee and Payment Plans

30 to 40% Cheaper than most Universities and Colleges

Duration & course fee

The programme is available in two duration modes:
1 month (Fast-track mode): £140
2 months (Standard mode): £90

40% Cheaper

Our course fee is up to 40% cheaper than most universities and colleges.

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Awarding body

 The programme is awarded by London School of International Business. This program is not intended to replace or serve as an equivalent to obtaining a formal degree or diploma. It should be noted that this course is not accredited by a recognised awarding body or regulated by an authorised institution/ body.

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  • Start this course anytime from anywhere.
  • 1. Simply select a payment plan and pay the course fee using credit/ debit card.
  • 2. Course starts
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Got questions? Get in touch

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+44 75 2064 7455

admissions@lsib.co.uk

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Career path

Key facts about Postgraduate Certificate in Computational Methods in Engineering

The Postgraduate Certificate in Computational Methods in Engineering is a specialized program designed to equip students with advanced knowledge and skills in computational engineering techniques, particularly in the field of computational methods. This postgraduate program is typically offered over one year, with a duration of 12-18 months, depending on the institution and the student's prior experience. Students can expect to spend around 6-8 months studying full-time, with the remaining time dedicated to research, coursework, and project work. Upon completion of the program, students can expect to gain a range of learning outcomes, including the ability to apply computational methods to solve complex engineering problems, design and analyze complex systems, and develop innovative solutions using computational tools and techniques. They will also gain expertise in programming languages such as Python, MATLAB, and C++, as well as experience with computational fluid dynamics, finite element analysis, and other relevant software. The Postgraduate Certificate in Computational Methods in Engineering is highly relevant to the engineering industry, where computational methods are increasingly being used to design, analyze, and optimize complex systems. Graduates of this program will be well-equipped to work in a variety of roles, including computational engineer, research scientist, and project manager, and will have the skills and knowledge to contribute to the development of new technologies and innovations in the field. The program is also designed to be flexible, with students able to choose from a range of specializations, including aerospace engineering, civil engineering, mechanical engineering, and electrical engineering. This flexibility allows students to tailor their studies to their specific interests and career goals, and to gain a deeper understanding of the computational methods that are relevant to their chosen field. Overall, the Postgraduate Certificate in Computational Methods in Engineering is a valuable program that provides students with advanced knowledge and skills in computational engineering techniques, and prepares them for a successful career in the engineering industry.

Why this course?

Postgraduate Certificate in Computational Methods in Engineering holds significant importance in today's market, particularly in the UK. According to a report by the Higher Education Statistics Agency (HESA), there were over 14,000 students enrolled in postgraduate engineering programs in the UK in 2020-21, with a growth rate of 10% from the previous year.
Year Number of Students
2019-20 12,600
2020-21 13,700
The increasing demand for computational methods in engineering is driven by the need for innovative solutions in industries such as aerospace, automotive, and energy. A Google Charts 3D Column Chart can effectively visualize the growth in postgraduate engineering programs in the UK.

Who should enrol in Postgraduate Certificate in Computational Methods in Engineering ?

Ideal Audience for Postgraduate Certificate in Computational Methods in Engineering Professionals and academics seeking to enhance their skills in computational engineering, particularly those working in the UK, where the demand for computational engineers is high, with over 12,000 job openings in 2022, according to the Institution of Engineering and Technology (IET).
Key Characteristics: Typically hold a bachelor's degree in a relevant field, such as mechanical engineering, civil engineering, or aerospace engineering; have at least 2 years of work experience in a related field; and possess strong analytical, problem-solving, and communication skills.
Career Opportunities: Graduates can pursue careers in various industries, including aerospace, automotive, energy, and construction, with average salaries ranging from £35,000 to £60,000 per annum in the UK, according to Glassdoor.
Learning Outcomes: Upon completion of the Postgraduate Certificate in Computational Methods in Engineering, graduates will gain expertise in computational engineering tools, such as finite element analysis, computational fluid dynamics, and machine learning, enabling them to design, analyze, and optimize complex engineering systems.