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Artificial Intelligence vs. Machine Learning: What’s the Difference?

Industry Advice Computing and IT

Artificial intelligence (AI) and machine learning (ML) have created a lot of buzz in the world, and for good reason. They’re helping organizations streamline processes and uncover data to make better business decisions. They’re advancing nearly every industry by helping them work smarter, and they’re becoming essential technologies for businesses to maintain a competitive edge.

These technologies are responsible for capabilities like:

  • Facial recognition features on smartphones
  • Personalized online shopping experiences
  • Virtual assistants in homes
  • Medical diagnosis of certain diseases

This exponential growth is posing problems for organizations. They report that their top challenges with these technologies include a lack of skills, difficulty understanding AI use cases, and concerns with data scope or quality.

AI and ML, which were once the topics of science fiction decades ago, are becoming commonplace in businesses today. And while these technologies are closely related, the differences between them are important.

Here’s a closer look into AI and ML, top careers and skills, and how you can break into this booming industry.

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Whether you have a technical or non-technical background, here’s what you need to know.


Artificial Intelligence vs. Machine Learning

What Is Artificial Intelligence?

With the increased popularity of AI writing and image generation tools, such as ChatGPT and Stable Diffusion, it’s easy to forget that AI encompasses a wide range of capabilities and applications.

As a broad term, artificial intelligence is the ability of a machine to act and think like a human. “On a basic level, artificial intelligence is where a machine seems human-like and can imitate human behavior,” says Bethany Edmunds, associate dean and lead faculty for Northeastern’s computer science master’s program.

These imitated behaviors can include:

  • Problem-solving
  • Learning
  • Planning
  • Analyzing data
  • Identifying patterns within data

AI replicates these behaviors using a variety of processes, including machine learning. While AI encompasses machine learning, however, they’re not the same.

What Is Machine Learning?

Machine learning is a type of artificial intelligence.

“Where artificial intelligence is the overall appearance of being smart, machine learning is where machines are taking in data and learning things about the world that would be difficult for humans to do,” Edmunds says. “ML can go beyond human intelligence.”

ML is primarily used to:

  • Process large quantities of data very quickly
  • Utilize algorithms that change and improve over time
  • Spot patterns and identify anomalies

For example, a manufacturing plant might collect data from machines and sensors on its network in quantities far beyond what any human is capable of processing. ML can process this data and identify problems that humans can address.

“Machine learning is a technique that allows machines to get information that humans can’t,” Edmunds explains. “We don’t really know how our vision or language systems work—it’s difficult to articulate in an easy way. For this reason, we’re relying on data and feeding it to computers so they can simulate what they think we’re doing. That’s what machine learning does.”

Working in Artificial Intelligence and Machine Learning

Skills Needed for AI and ML Positions

Because artificial intelligence is a catchall term for smart technologies, the necessary skill set is more theoretical than technical. Machine learning professionals, on the other hand, must have a high level of technical expertise.

Artificial Intelligence Skills

According to our analysis of job postings data related to AI, people pursuing a career in artificial intelligence must have a foundation in:

  • Computer science
  • Software engineering
  • Agile methodology
  • Java (programming language)
  • Software development
  • SQL (programming language)
  • Python (programming language)
  • JavaScript (programming language)
  • Amazon Web Services
  • Application Programming Interface (API)

Machine Learning Skills

According to our analysis of job postings data related to ML, people pursuing a career in machine learning must have a foundation in:

  • Data analysis
  • SQL (programming language)
  • Python (programming language)
  • Data science
  • Computer science
  • Tableau (business intelligence software)
  • R (programming language)
  • Machine Learning
  • Dashboard
  • Business intelligence

Artificial Intelligence and Machine Learning Jobs

Since the recent boom in AI, this thriving field has experienced even more job growth, providing ample opportunities for today’s professionals.

According to our analysis of job posting data, the number of jobs in artificial intelligence and machine learning is expected to grow 26.5 percent over the next ten years.

That same report also shows the most in-demand jobs that require artificial intelligence and machine learning skills.

1. Software Engineer

Software engineers create and develop digital applications or systems. While ML experience may or may not be a requirement for this career, depending on the company, its integration into software is becoming more prevalent as the technology advances.

Software engineers enable the implementation of AI into programs and are crucial for their technical functionality. They play a major role in enabling digital platforms to leverage ML and accomplish diverse tasks.

2. Software Developers

Software developers create digital applications or systems and are responsible for integrating AI or ML into different software. Additionally, they may modify existing applications and carry out testing duties. They use a variety of programming languages—such as HTML, C++, Java, and more—to write new code or debug existing code.

3. DevOps Engineers

DevOps engineers work with other team members such as developers, operations staff, or IT professionals. They’re responsible for ensuring the code deployment process goes smoothly by building development tools and testing code before it’s deployed. Familiarity with AI and ML and the development of relevant skills is increasingly important in these roles as AI becomes more commonplace in the software world.

4. Java Developers

Java developers are software developers who specialize in the programming language Java. As one of the most common programming languages in AI development and one of the top skills required in AI positions, Java plays a huge role in the AI and LM world. For this reason, there’s a high demand for software developers who specialize in this language. Java Developers should still obtain proficiency in other languages, however, since it’s difficult to predict when another language will arise and render older languages obsolete.

Learn More: 5 High-Paying Careers in Artificial Intelligence

How Much Do AI and ML Professionals Earn?

If you’re hoping to work with these systems professionally, you’ll likely also want to know your earning potential in the field. While compensation varies based on education, experience, and skills, our analysis of job posting data shows that these professionals earn a median salary of $120,744 annually.

Pursuing an Advanced Degree in Artificial Intelligence

Northeastern University offers two avenues for people looking to pursue an advanced degree in artificial intelligence: a Master of Science in Artificial Intelligence (MSAI) and a Master of Science in Computer Science (MSCS) with a specialization in artificial intelligence.

Master of Science in Artificial Intelligence

The MSAI does not require a computer science undergraduate degree and is geared toward people looking for a broader understanding of AI. “This is someone who needs to understand artificial intelligence, but isn’t necessarily trying to push the envelope of what’s trying to be done,” Edmunds says. “Instead, it’s about advancing how machines are being used and how they can be applied.”

In the MSAI program, students learn a comprehensive framework of theory and practice. It focuses on both the foundational knowledge needed to explore key contextual areas and the complex technical applications of AI systems.

This program incorporates a variety of relevant coursework pertaining to topics, such as:

  • Data science
  • Robotics
  • ML
  • And more

This enables students to pursue a holistic and interdisciplinary course of study while preparing for a position in research, operations, software or hardware development, or a doctoral degree.

“This program takes people from different backgrounds and gives them enough information to be able to talk with a team who’s responsible for the more technical artificial intelligence responsibilities,” Edmunds says. “They don’t need to know the nuts and bolts, but they’ll leave with enough to know the right questions to ask and make sure they’re being responsible with the technology.”

Master of Science in Computer Science

The MSCS with a specialization in artificial intelligence, on the other hand, is designed for people who are—or want to become—software engineers, computer science developers, or computer science researchers with a focus on creating new applications for algorithms, for example.

This program is designed for students with a background in computer science and includes courses on:

  • Robotic science and systems
  • Natural language processing
  • Machine learning
  • Special topics in artificial intelligence

“AI and ML are going to be how we solve some of the largest problems,” Edmunds explains. “We’re very focused on making sure that everyone can get access to those skills because that’s how we’re going to create a better world.”

To learn more about how a graduate degree can accelerate your career in artificial intelligence, explore our MS in AI and MS in Computer Science program pages, or download the free guide below.


Download Our Free Guide to Breaking into Computer Science