MS Degree in Artificial Intelligence
Many say intelligence is scarce, and just like many scarce things the world has started to develop alternatives. Artificial intelligence is not really an alternative for real intelligence, rather a facilitator. Hollywood blockbusters like The Age of Ultron have turned the concept of AI into a scary tale of machines vs man. However, people don’t realise we see AI all around us. Just very simple versions of it. Each time gmail predicts what word you are going to type next is a simple example of AI at work. Sooner or later most softwares in the world is going to have features which will predict your next step.
Development of AI requires actual humans and this is why there are degrees being offered in various parts of the world. Artificial Intelligence (AI) focuses on creating and training machines that find solutions to problems which normally require human intelligence. Artificial Intelligence systems can be powered by machine learning, deep learning, or operating rules.
Being a relatively new field, AI comes with both benefits and potential risks. It can optimise tasks and reduce human errors, but it might also lead to the disappearance of some types of jobs and the creation of new ones. Additionally, some scientists have expressed concerns regarding future self-aware AI machines, although we haven’t been able to develop them yet.
Some of the topics you can expect to study during a Master’s in Artificial Intelligence are: computer vision, natural language processing, speech recognition, software engineering principles, autonomous systems, machine learning, image analysis, signal and sound processing, ethics and social implications of AI, etc.
Top tech companies employ most AI professionals, who work on a variety of applications, systems, and machines. They create algorithms that offer people suggestions on services like YouTube or Netflix, develop, test, and improve self-driving cars and drones, or create digital personal assistants which provide useful information.
You need to have advanced knowledge of mathematics, algorithms, statistics, and probability to work in Artificial Intelligence. Another requirement is to have solid expertise in programming languages. After graduation, AI students find work as AI researchers, AI specialists, machine learning engineers, computational linguists, robotics engineers, etc.
What’s the best degree for artificial intelligence jobs?
Here are some common degrees for AI jobs that you can receive at the graduate levels:
Some schools offer programs specifically in AI, though this major is more uncommon than some other technology degrees. In these programs, students learn about many parts of artificial intelligence, such as cognitive systems, natural language processing, pattern recognition, game theory, analysis of algorithms and data structures. Some schools combine this degree with machine learning, which is a related concept that refers to using statistical models that program machines to learn progressively by referencing data. Compared with other related majors, an AI program typically has more emphasis on learning concepts to develop these types of applications.
A computer science degree is a common choice for students who want to work in artificial intelligence. Many schools offer computer science programs with a track in AI or machine learning. This specialisation allows students to take various classes in AI to help prepare them for careers in this field. For example, students completing a computer science program with an artificial intelligence specialisation may take classes such as robotics, database systems, visual computing and cognitive science. This coursework can provide students with comprehensive knowledge of the computer systems used in AI.
A data science program teaches students how to write code for computers that can access, manage and manipulate information in a database, which is a collection of data. Because AI relies on data for computers to perform tasks, this degree can be an excellent option for students who want to work in these jobs. Students completing a degree in data science may take a variety of courses, such as statistics, data analysis, mathematics and information science. Typically, these programs also offer classes related to artificial intelligence, such as data mining, machine learning and statistical computing.
Artificial intelligence draws heavily on mathematical concepts, which makes this degree helpful for students who want to have a career in this field. While working toward this degree, students typically take courses in applied mathematics, which may include computational methods and algorithms. It’s helpful for mathematics students to take some technology courses, such as programming, and related classes in AI or machine learning to learn about these techniques. Some schools combine a mathematics and data science degree, which can be a good choice for those who want to work in AI.
This degree can provide students with knowledge of the statistical models that artificial intelligence uses to develop applications that simulate human behaviour. A degree in statistics can be particularly helpful for jobs in machine learning, which uses statistical methods to program computers to make accurate predictions. A statistics degree can also be beneficial for students who want to work in AI research, which involves studying statistical models to create new applications. Many students choose to major in both statistics and computer science, so they can also take courses to learn more about computer systems.
What careers are there for artificial intelligence majors?
Here are some common career paths for professionals who major in artificial intelligence or a related area:
Data scientists collect and organise data and analyse this information to make predictions. They develop algorithms to create artificial intelligence systems that can use data to perform tasks. These professionals may also study the outcomes of these applications to generate insights and make modifications to improve their performance. Businesses in many industries, such as information technology and finance, hire data scientists who can help them analyse data to identify opportunities for growth.
Machine learning Engineer
Machine learning engineers are responsible for creating programs that allow computers to respond and react to various situations without programming. They create and write code for machines to apply predictive models based on statistical methods. With these algorithms, computers gradually become more proficient in making recommendations. For example, a machine learning engineer may develop voice recognition software that becomes more responsive to a person’s voice. These professionals can work in various industries, including automotive, finance and supply chain management.
Computer engineers create, develop and test computer software and hardware systems. They design hardware components, such as processors or routers, and write software programs for computers. These professionals ensure the hardware and software systems function correctly together. Many of these professionals choose to specialise in AI. For example, a computer engineer may be responsible for building a robotics system that can automate certain tasks. Computer engineers can find jobs in many areas, such as aeronautics, research and technology.
Robotics engineers use their computer science and engineering skills to design, build and test robotic devices. Robotics is a branch of AI that focuses on programming devices to interact in a real-world environment. These devices require special hardware that robotics engineers develop and test for efficiency. They also create the electrical components that allow the robotic device to function physically. For example, a robotics engineer may develop a robot that can perform medical procedures. These professionals can work in areas such as manufacturing, health care and transportation.
Software engineers design, develop and maintain computer software using their analysis and computer science skills. They work closely with developers to explain the software functionalities so they can write code for the program. These professionals make recommendations for software upgrades and perform regular maintenance to keep the software working correctly. Many software engineers specialise in machine learning, where they create software that enables computers to identify patterns in data to make decisions and automate processes. They often work in the technology or research industries.