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Which Engineering Branch Is Best For Future?


Which Engineering Branch Is Best For Future

When planning one’s education, it is important to keep the future in mind. What industries are thriving, and which ones offer the best salaries? It’s particularly essential to keep such questions in mind when looking into engineering courses. Engineers use science, mathematics, and technology to solve problems. The work of those professionals applies everywhere including how people work, means of travel, communication, staying healthy and entertainment. Today, the engineering discipline offers more career options than any other field out there. Initially, there were four main engineering branches, i.e., mechanical, civil, electrical and chemical. Nowadays, the number of branches has increased significantly.

Which engineering branch is best for the future? The best engineering branch for the future is probably Data Science & Machine Learning. That’s because software engineering has experienced continuous growth over the last few years and it’s not showing any signs of stopping. Other promising fields for the future include Automation & Robotics Engineering, Alternative Energy Engineering and Civil Engineering.

When making decisions on a career path, it’s hard to know whether a chosen industry will continue to grow or become redundant. Anyhow, it’s clear that the trend is moving toward IT (information technology) and automation. And that’s expected to remain the case for many years to come. Traditional engineering disciplines like civil and petroleum are still in high demand. However, the fastest-growing fields today are in the IT-sphere. In this article, I look at engineering branches and their scope, average engineering salary, and the best engineering field for the future.

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Which Engineering Branch Is Best For Future?

The following are the best engineering branches for the future:

Data Science and Machine Learning

As a branch of software engineering, Data Science involves creating useful information based on big data. Big data is simply large amounts of data, and they can come from a range of sources like e-commerce, healthcare or financial industries. The data science field utilizes both statistical and software engineering concepts to collect analyze and present data. The data is presented in a meaningful way that allows the final user to optimize the specific services.

Machine learning falls under data science, and it’s used to make future predictions based on past data. Algorithms in machine learning predict, and assess the accuracy of the predictions. After that, the engineer optimizes the algorithm to enhance the precision of the prediction moving forward.

Automation and Robotics Engineering

Robotic systems have for long been used in handling menial repetitive tasks that do not need man’s attention to detail. But, with continuous advancements, robotic systems are starting to go from single arm-welding and assembly units to complex humanoid machines. Robotics engineers are involved in the design, creation, testing and implementation stages of robotics systems. A robotics engineer is usually an electronics, mechanical, or mechatronic engineer.

The modern world is moving closer to an automated state. So, the only secure jobs are those within the automation industry.

Petroleum Engineering

A petroleum engineer works on drilling methods, design of drilling equipment, and implementation of drilling plans for crude oil extraction. The field of petroleum engineering has seen great demand over the last few years. Currently, it’s projected to continue growing over the coming ten years.

In spite of the push to use electrical cars and clean energy, oil still remains a valuable commodity in numerous industries. However, there’s a moral dilemma when joining the petroleum field, because of the increasing environmental crisis the earth is facing.

Civil Engineering

The branch of civil engineering is among the oldest engineering disciplines and it continues to experience high demand every year. Civil engineers are responsible for building the infrastructure relied upon by countries across the world.

Civil engineering has numerous sub-categories, which make it hard to saturate the market. Therefore, it’s an excellent career to pursue. The main civil engineering branches are structural, environmental, and transportation engineering.

Electrical Engineering

The field of electrical engineering is yet another traditional engineering branch that shows consistent demand. It’s a very broad discipline that primarily includes power, instrumentation, and electronics engineering. The wide range of career paths within the field of electrical engineering means job opportunities are always in plenty.

Alternative Energy Engineering

The increased pressure being inflicted on the earth because of climatic change has created a push to clean and renewable energy. For instance, the demand for solar energy appliances has grown dramatically, leading to lower panel costs. Without a doubt, alternative clean energy is essential for the future. Although coal-powered stations still make up the majority of worldwide energy production, their growth has stagnated. The use of alternative energy is becoming more popular.

Mining Engineering

Mining engineers usually design open-pit and belowground mines and supervise their excavation and extraction. Additionally, the design techniques for processing and transporting the extracted materials to a range of processing plants. The demand for iron is predicted to start falling in the next few years, But, the demand for metals used in electronics and batteries (e.g., copper, nickel, and lithium) is set to continue rising.

Project Engineering

Project engineers manage technical projects, which might include design, procurement, manufacture and transportation of simple elements to complex treatment plants. The engineer’s role is multidisciplinary and needs fundamental technical knowledge of each facet of a project.

The field of project engineering is critical and necessary in all branches of engineering. It’s not a subject that’s explicitly studied since any engineering degree can result in a project engineering post. But, taking up further studies in project management is recommended after undergraduate studies to enhance overall efficiency.

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Types of Engineering and Salaries USA and the UK

Here’s what some types of engineers earn on average in the United States and the United Kingdom per year.

  • Machine Learning Engineer: $111,911 (US) and £52,000 (UK)
  • Robotics Engineer: $81,857 (US) and £31,585 (UK)
  • Petroleum Engineer: $101,636 (US) and £44,080 (UK)
  • Civil Engineer: $65,433 (US) and £31,074 (UK)
  • Electrical Engineer: $74,691 (US) £31,889 (UK)
  • Mining Engineer: $76,108 (US) £40,000 (UK)
  • Alternative Energy Engineer: $90,000 (US) £39,305 (UK)
  • Project Engineer: $68,065 (US) £32,739 (UK)

Engineering Branches and Their Scope

The field of engineering is broad. Below, I take a look at the primary branches of engineering and their sub-disciplines.

  • Chemical Engineering: It involves the use of biological, chemical and physical sciences in the conversion of raw materials into more valuable forms. The sub-disciplines of chemical engineering are bimolecular engineering, materials engineering, molecular engineering, process engineering, and corrosion engineering.
  • Civil Engineering: It deals with the design, construction and maintenance of built environments. The branch is divided further into environmental engineering, geotechnical engineering, structural engineering, mining engineering, transport engineering, utility engineering, and water resources engineering.
  • Electrical Engineering: Here, engineers study and apply concepts of electricity, electronics as well as electromagnetism. Sub-disciplines in this branch are electronic engineering, computer engineering, power engineering, and optical engineering.
  • Mechanical Engineering: Mechanical engineers design and analyze heat and mechanical energy for use in machines and mechanical systems. Its sub-categories are acoustical engineering, manufacturing engineering, optomechanical engineering, thermal engineering, sports engineering, vehicle engineering, power plant engineering, and energy engineering.
  • Interdisciplinary fields of engineering: Aerospace, agricultural, applied, biomedical, biological, building services, energy, information, industrial, mechatronics, military, Nano, nuclear, petroleum, project, railway, software, systems, and textile engineering.

Best Engineering Field for the Future

Most engineering jobs come with good job opportunities and salaries. However, it’s clear that occupations like data science and automation have the highest demand. Additionally, those jobs offer higher than average wages.

Data Science and Machine Learning is probably the greatest engineering field for the future. It comes with many job opportunities and high salaries. To become a machine learning engineer, most employers prefer applicants with a master’s degree in computer science. But, this field is relatively new and the amount of available top tech talents is insufficient. So, many companies are willing to make exceptions when hiring new machine learning engineers.

However, to stand a better chance, possible candidates should familiarize themselves with the standard application of machine learning algorithms. Additionally, machine learning engineers need to know several programming languages including Python, Java, R, C++, C, JavaScript, Scala and Julia.

The following is a list of the job requirements for a machine learning engineer:

  • Master’s or Doctorate in math, computer science or statistics
  • Knowledge and experience working with programming languages(e.g., Python) and programming tools (e.g. MATLAB)
  • Work experience with vision processing, Gaussian processes, reinforcement learning and neural networks
  • In-depth understanding of probability and statistics
  • A solid understanding of mathematical concepts including complex algorithms for machine learning and communication
  • Advanced engineering knowledge
  • Robust analytical skills
  • Experience working with large datasets in a high throughput setting
  • Linux Sysadmin abilities
  • Knowledge of distributed systems tools such as Etcd and zookeeper.
  • Extensive understanding of machine learning assessment metrics and best practices
  • Experience operating messaging tools such as Kafka
  • Competency with infrastructure as code
  • Machine learning engineers usually perform the following roles:
  • Develop machine learning models
  • Work together with data engineers to create data and model pipelines
  • Utilize machine learning and data science methods as well as distributed systems
  • Develop production-level code
  • Link code to production
  • Partake on code reviews
  • Enhance current machine learning models
  • Take charge of the whole lifecycle i.e., research, design, testing, development, deployment, control and maintenance.
  • Create project outcomes and isolate problems
  • Implement machine learning algorithms
  • Communicate complex methods to business leaders
  • Perform an analysis of large and complex amounts of data to derive useful insights
  • Research best practices to help improve machine learning infrastructure

The salaries for machine learning engineers vary depending on the role and location. However, the wages are generally excellent and are expected to increase as the demand for machine learning engineers continues to increase.

It’s worth mentioning that while machine learning engineering is a valid option, other engineering fields are also excellent. All in all, the choice of an engineering career comes down to personal interest and what a person wants to achieve many years from now.

Terry Tregorius

Terry is passionate about travel and finding new great places to live, work and visit. He specializes in the UK where he lives with his family. Read more articles by Terry Tregorius

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