Machine learning (ML), artificial intelligence (AI), and machine learning (ML), are two terms that have generated a lot of buzz within the technology industry. They help organizations improve their processes and find the right data to make better business decisions. They are advancing almost every industry by making them more efficient and helping businesses stay competitive.
These technologies allow for features such as facial recognition on smartphones, personalized online shopping experiences and virtual assistants at home. They also enable the diagnosis and treatment of diseases.
These technologies and the professionals who are skilled in them are in high demand. Gartner’s research shows that the average number AI projects at an organization will more than triple in the next two-years.
Organizations are facing problems due to this rapid growth. According to them, the top issues with these technologies are a lack in skills, difficulty understanding AI use case scenarios, and concerns about data quality or scope.
AI and ML are now commonplace in business today. These technologies were once subjects of science fiction decades back. These technologies are closely related but there are significant differences. This article will provide a detailed look at AI and ML, the top jobs and skills and how to get into this lucrative industry.
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What is Artificial Intelligence?
According to Bethany Edmunds (associate dean and chief faculty of Northeastern’s computer science master’s program), artificial intelligence is not well defined, which leads to confusion between it, and machine learning.
Artificial intelligence is basically a system that appears smart. This definition is not very accurate, however, as it’s almost like saying something is healthy. She explains, “What does that actually mean?” Artificial intelligence, at its most basic level, is a machine that appears human-like and can mimic human behavior.
These behaviors include problem solving, learning, planning, and other skills. They are achieved by analyzing data and identifying patterns in it to reproduce those behaviors.
What is Machine Learning?
Edmunds explains that machine learning is a form of artificial intelligence. She explains that machine learning, which is a type of artificial intelligence, is the appearance of being intelligent. Machine learning is when machines take in data and learn things about the world that are difficult for humans. “ML can be more than human intelligence.”
ML is used to quickly process large amounts of data using algorithms that evolve over time and become better at what they are supposed to do. A manufacturing plant may collect data from sensors and machines on its network in amounts far greater than any human can process. The ML can then be used to identify patterns and anomalies that may indicate a problem humans can address.
She explains that machine learning allows machines to access information that humans cannot. We don’t know much about our vision and language systems. It’s hard to explain in an easy way. We rely on data to simulate what we think we are doing. Machine learning is exactly what this does.
Artificial Intelligence vs. Machine Learning – Skills Requirements
Artificial intelligence is a generic term that refers to smart technologies. Therefore, the required skill set is more technical than theoretical. However, machine learning professionals must possess high levels of technical expertise.
Artificial Intelligence Skills
A foundation is required for anyone who wants to pursue a career as an artificial intelligence professional.
- Algorithms and techniques for analysing them
- Machine learning and how to use techniques to draw inferences out of data
- Ethical concerns when developing AI technologies that are responsible
- Data science
- Robotics
- Java programming
- Programming design
- Data mining
- Problem-solving
Machine Learning
A foundation in:
- Mathematics applied
- Neural network architectures
- Physics
- Data modeling and evaluation
- Natural language processing
- Programming languages
- Probability and statistics
- Algorithms
Artificial Intelligence vs. Machine Learning Jobs
Gartner estimates that there will be 58 millions new jobs in artificial Intelligence by 2022, according to “The Future of Jobs 2018”, a report from the World Economic Forum. According to Indeed, the following jobs require machine learning and artificial intelligence.
1. $142,859 for a machine learning engineer
Advanced programmers are responsible for creating AI systems that learn from data. These professionals must have excellent data management skills and the ability for complex modeling on dynamic data.
2. Deep learning engineer: $75.676
These computer scientists are computer scientists who use deep-learning platforms to create programming systems that replicate brain functions. It is essential to have experience in developing neural networks.
3. Senior data scientist: $134 346
Senior data scientists use the data of the business to improve business capabilities through advanced statistical procedures. These highly qualified computer scientists and mathematicians are responsible for data collection and analysis. These individuals may also use machine learning and experimental frameworks to help build a foundation for advanced analytics. They also oversee junior data scientists and drive the company towards a data-driven culture.
4. Computer vision engineer: $126,400
Computer vision engineers determine how to program a computer to understand digital images and videos better. This vision is a technique that trains computer systems to understand visual images.
Studying for an advanced degree in artificial intelligence
Two options are available at Northeastern University for those who want to pursue an advanced degree of artificial intelligence: a Master of Science, Artificial Intelligence (MSAI), and a Master of Science, Computer Science (MSCS), with a specialization on artificial intelligence.
Edmunds states that the MSAI doesn’t require a bachelor’s degree in computer science and is designed for people who want to gain a deeper understanding of AI. She says, “This person needs to understand artificial Intelligence but isn’t necessarily trying push the envelope of how it can be done.” It’s not about how machines can be used, but how they can be applied.
The MSAI program teaches students a broad framework of theory as well as practical application. It covers both the fundamental knowledge required to examine key context areas as well as the technical applications of AI systems.
The program combines data science, robotics and ML. Students can pursue an integrated and interconnected course of study, while also preparing for a job in research, operations or software development or a doctoral degree.
Edmunds states that the program brings together people from diverse backgrounds to give them enough information to speak with someone who is responsible for technical aspects of artificial intelligence. They don’t have to be experts in the technical aspects of artificial intelligence, but they will leave knowing enough to ask the right questions and ensure they are being responsible with technology.
The MSCS with an emphasis in artificial intelligence is for those who want to be, or are interested in becoming, a computer scientist, software developer or researcher whose focus is on developing new algorithms.
This program is for students who have a background in computer sciences. It includes courses in robotic science and systems as well as natural language processing and special topics in artificial Intelligence.
“AI and ML will be the way we solve some of our biggest problems.” Because that’s how we will create a better world, we are very focused on making sure everyone has access to these skills.
