Electrical engineering involves electrical energy and information transfer. The engineers in this field learn to design electrical devices, study analog and digital circuits, and specialize in various areas such as autonomous vehicles, robotics, remote sensing and alternative energies. On the other hand, computer engineering deals with computer hardware and software, video game consoles, biomedical applications, and control systems in airplanes and cars. The field combines aspects of computer science and electrical engineering. A degree in electrical computer engineering is a blend of both courses.
Electrical computer engineering is a rapidly evolving field in technology globally. These engineers are involved in areas including designing medical equipment such as surgical robots to identify patients’ diseases, and creating sustainable energy systems to curb climate change.
Electrical computer engineers play a huge role in machine learning, and that is the focus of this article. We start with the basics of machine learning and artificial intelligence (AI) and then link them to specific roles that engineers play in bringing them to life.
What is machine learning?
AI is a concept for creating intelligent machines that simulate human thinking, behavior and capability. In contrast, machine learning is a subset of AI that allows computers to learn from data independently. For this section, we’ll use the term machine learning. When specific data is given, a machine learning algorithm can recognize patterns and learn from data to make predictions about new data with the help of clever statistics. When it comes to execution and delivery, there is much more to machine learning than the surface definition. Within the field are three types of machine learning algorithms: unsupervised, supervised and reinforcement learning.
Unsupervised learning
Unsupervised learning has no right answers or historical labels to compare information to. Rather, the algorithm looks at the information and concludes. This method helps find attributes to sort groups, such as identifying what consumers can be targeted by the same marketing campaign.
Supervised learning
This method trains the algorithms by entering an input and a desired outcome to create labeled examples. The machine can find errors by comparing the actual outcome with the one that it knows should be correct based on the information originally entered. An example is the algorithm detecting credit card fraud, which can spot unusual charges by comparing them to the expected transactions.
Reinforcement learning
Although reinforcement learning is not as popular as the previous two methods, it is a crucial part of the field. This algorithm learns through trial and error. It chooses the option that results in the greatest reward. This method is mainly used in navigation, gaming and robotics.
Machine learning is gaining importance and popularity because companies and government agencies have large amounts of data that must be sorted and analyzed to ensure maximal results. The data used in these algorithms includes things such as past buyer information, loaner information, diabetes rates, survey information, murder rates, website information, and more. Machine learning not only reveals trends in the information but also predicts things about future behavior.
Application of machine learning
Machine learning is more common today than you might think. You can find elements of it daily, even without knowing. Have you ever wondered why after seeing a movie on Netflix, the app starts suggesting similar movies in the genre? This is machine learning in its purest form. It understands that you like the movie and suggests other aspects that it thinks you might enjoy. The same is true for ecommerce websites, where you get recommendations for similar products after a purchase.
However, while these are common examples, the field is much more than entertainment and shopping. Machine learning is found in other areas such as self-driving cars (which are taking over the automotive industry), wearable medical devices, agriculture, public safety, etc.
Machine learning and electrical and computer engineering
Because the field of machine learning is rapidly expanding, it needs professionals from all walks of life to put their heads together. Experts in computer engineering, electrical engineering and software engineering are at the forefront of the development. With their knowledge from various fields, they pool their resources together to contribute meaningfully.
The three basic skills needed to excel in machine learning are coding languages, applied math and algorithms, advanced signal processing techniques, and probability and statistics. Companies such as Amazon, Facebook, Nike, Spotify and IBM hire electrical computer engineers with experience in machine learning. The job prospects are always expanding. Although this blended field is relatively new, the pay is still high. Professionals earn competitive pay like their counterparts in other fields of technology.
Are you an engineer or an aspiring engineer? If so, here are five reasons to study electrical and computer engineering.
- Become an innovator
Electrical and computer engineering students are at the forefront of future technologies. As they are experts in math and science, they deploy this expertise to design affordable, accessible, efficient and sustainable solutions to everyday problems. Some of the world’s global innovators such as Nikola Tesla, Esther M. Conwell, Heinrich Hertz and Bill Gates have been electrical or computer engineers.
- Make an impact in the world
Inventors are people who create products for society. Although these products come at a price, they make our life easier. Without them, we’ll be running in circles, and life would be boring. That said, electrical and computer engineers are indispensable to society. Think about any modern gadget you own, and you can thank an engineer for contributing their quota to seeing it happen. This should motivate you to pursue a career in the field!
- Opportunities in multiple countries
Engineering is one field that admits people with different interests but doesn’t restrict their choices. With a Master of Engineering in Electrical and Computer Engineering from Kettering University Online, you are equipped with the technical expertise to play an integral role in developing electric and autonomous vehicles, dynamic systems and robotics. The program seeks to meet the growing demands within the automotive and advanced mobility industry. This course is ideal for working professionals as it is 100% online. The world is a global village, and technologies that work in one country will work in another. Therefore, the skills obtained from a master’s program benefit professionals who want to work in any part of the world.
- High salaries
Considering the demand for electrical and computer engineers, the pay remains a major motivation to be in the field. These experts painstakingly acquire the necessary skills by passing exams and excelling in the practical elements. When certified, they don’t need to go into the labor market looking for jobs as companies scout for them to meet the demand. It is easier for them to climb the career ladder when they eventually get into the field. While the entry-level salary may be less enticing, the offers become juicier as you climb up the ladder. A degree in electrical and computer engineering opens endless doors. The field is so vast that it can be tempting to specialize in two or three areas.
- Versatility
There is practically no technology firm in which you don’t find these engineers. You can find them in construction, manufacturing, transport, entertainment, automation, aerospace, bioengineering and telecommunications companies. These engineers are also at the forefront of producing electric bikes suitable for off-road terrain.
Application of AI in computer science and engineering
As technology improves, the application of AI widens. It is impossible to guess how the field will evolve in the next decade. However, we know that it will change and improve computer science and engineering through advanced programming techniques and data organization. Computers function by following a set of programming instructions, and AI is a field that helps transform this process into something more dynamic.
Here are eight ways that the application of AI is changing things in the electrical and computer industry.
- Self-modifying coding
AI has now been fully inculcated into programming languages to create self-modifying groups of code. This is now directed by benchmarks such as a score to try new combinations that reach the goal consistently. Over time, this ability to make intelligent programs allows updates to be created or errors to be patched.
- Robotics
Robots have a set of programming that allows them to function like humans. Because they function in various settings, they are programmed with specific instructions to excel in those areas. AI plays a major role in manufacturing these advanced machines, and electrical and computer engineers are equal to the task. They have mastered robotics to such a degree that they are able to take advantage of many of the newer applications of AI.
- Speech and language processing
It is normal to have computers that speak and respond to us when we speak to them. We ask questions, and they are willing to supply accurate answers. Computers that do this can recognize, signal and process a set of instructions. With AI, it feels like a more complete and natural interaction. These machines go beyond basic answers when you want them to, and are as human as possible.
- Data mining
In computing, data is mined to analyze and find certain anomalies, patterns and other values within a large volume of information. AI makes this process more efficient and even comes up with unforeseen responses to aid those who must view the data and make decisions.
- Visualizations and visual data
Computer programs now make visualizations based on certain variables, but introducing AI enhances the process. By having smart programs guiding users through visual analytics and making decisions for interpreting and organizing data, AI helps create a new visual aid.
- Marketing programs
AI has simplified marketing such that humans no longer struggle with those areas that proved difficult some years ago. It now handles areas such as search engine optimization (SEO), customer service and content marketing. This is appreciated more by businesses that don’t want to invest so much into building marketing or public relations departments. While they invest in experienced professionals, they do not want to spend so much to the detriment of their profit. Because this field is still in its infancy, it may take time before programs replicate traditional marketing campaigns.
- Image recognition
As computers keep getting better at recognizing voice commands, the ability of a program to remember and decode an image is also appealing. Today, computers have applications for everything, including graphic design. Large databases of tagged images are available to tech giants such as Facebook and Google. These huge volumes of data are used creatively to create computer programs that recognize what they see, even if it’s the first time.
- Cloud computing
The ability to store and access data in the cloud is changing how people access information from many locations. This latest technology has eliminated the need for traditional physical storage tied to a place. AI helps the process become more organized and systematic. Users can get more intelligent responses when storing and accessing their files from cloud-based networks such as Amazon.
The top three soft skills for electrical and computer engineers
Before you can become an electrical and computer engineer, you must have attained a degree. You are trained in the practical areas as well as the theoretical aspects of the field. While these technical skills are crucial to the progress of your career, engineers also require certain soft skills to help them climb up the ladder. Before applying for a job in electrical and computer engineering, make sure that you possess the following skills.
- Communication
The best engineers in the field can express complex and abstract ideas to technical and non-technical professionals. Considering that you probably work in an environment with people from diverse professions, it is unfair to communicate using your industry jargon. The engineer’s job is not superior to that of other experts, so there’s no need to exert superiority in language use. If you work in a multidisciplinary environment, you’ll notice how non-technical staff react when you communicate in this way. Also, take note of how seamless the job is when you are clear and straight to the point.
- Adaptability
The electrical and computer engineering field is constantly searching for experts who can blend into different business and organizational settings. The field also needs those who can quickly get used to changes in the work environment. Because technology is constantly changing, only those who can adapt to these changes will make the best of it. When projects do not go as planned, strategies must be updated and upgraded regularly to meet the current pace. Whether you are an engineer or aspiring to be one, start getting used to the fact that things may not always go as planned. If they do, congratulations! If they don’t, it is important to be able to find your way around it.
- Creativity
It is one thing to have the technical skills to design new systems and another to creatively build one that solves a new problem. Technology has made life easier. These days, we have multiple solutions targeted at a problem. If you have a problem with writing a cover letter, there’s an AI writing tool to help you out. If you need your heart rate to be monitored without going to the hospital, there are wristbands and smartwatches that help with that. It takes a creative mind to build a solution that solves a problem. One of the fastest ways to enhance creative thinking is to look at problems from a different perspective. Only then will you find a solution that is different from the status quo. Tech giants make so much money by providing solutions to new problems. They understand how thrilling this is to the public. Of course, these ideas sell in no time as we constantly search the internet for solutions to our problems.
The field of electrical and computer engineering is still emerging. With machine learning and AI added to its fold, more people are developing an interest in it. It is both lucrative and satisfying. Let us know if you are interested in this career path in the comments section.
