How to become a machine learning engineer

Woman's hand reaching out to touch an interface labeled Machine Learning

How to become a machine learning engineer

Read Time 6 minutes

Machine learning and AI tools are upending many sectors and displacing entrenched business practices. In May 2022—six months before ChatGPT made its public debut—IBM’s Global AI Adoption Index was already reporting that 35% were already using AI, and another 42% were exploring its application. Now is the time for individuals and organizations to lay the necessary groundwork to be sure they aren’t left behind.

According to a study by the auditing firm PwC, AI could add up to $15.7 trillion to the global economy by 2030. China and North America will account for almost 70% of the global economic impact ($10.7 trillion). Widely available tools built on machine learning models such as ChatGPT are already increasing office productivity. These tools are helping organizations consistently disseminate best practices to newer workers, while also assisting more seasoned staff in everything from creating initial drafts for data-heavy reports to uncovering trends and insights from vast stores of historical data. Meanwhile, AI and machine learning are creating completely new career paths in data analysis and software development.

The once obscure role of "machine learning engineer" is suddenly and increasingly in demand. In 2024 and beyond, organizations will rely on machine learning engineers to serve as linchpins, holding together their data scientists, administrators, AI engineers, and software engineering teams.

A better approach to machine learning-related certification

During the past 25 years, James "Doc" Muren has delivered information technology, cybersecurity, and artificial intelligence training at Fortune 500 companies, for the Department of Defense, and to financial sector employees. He is already seeing the enormous effect that machine learning is having on the workplace. Tools like ChatGPT are boosting productivity, while machine learning more broadly is unlocking new organizational possibilities and opportunities.

But these benefits are realized only if organizations can get the certified machine learning engineers, software engineers, and data scientists they need to harness machine learning. Doc Muren emphasizes the value of the certification process as a "learning journey." In a dynamic and fast-evolving domain like machine learning and AI, this is an especially important distinction.

"Certification is an extremely important component," Muren points out, as it firmly establishes that candidates have a specific baseline knowledge. "There will always be a lot of candidates [for any position] that have some specific certification. What did they learn as a part of that journey? What can they demonstrate? What can they put in their portfolio?"

In addition to a solid foundation in computer science and programming languages like Python, they also need to be ready to define problems in a way that can be tackled with machine learning, work with data sets, and evaluate various approaches before putting those models and algorithms into production. A certification program with hands-on components that replicate real-world scenarios helps ensure the sort of engaging learning journey that translates into certified professionals who can hit the ground running, even in a rapidly changing landscape like that of AI and machine learning.

The AI and machine learning journey with Pearson VUE

For decades, Pearson has focused on delivering educational and training resources that adapt with the times. With its self-paced Pearson CertPREP courseware, students can control the amount of content delivered per session and build that into certification as their learning journey dictates.

The IT Specialist Computational Thinking program is designed for professionals in both non-technical and technical roles. It focuses on critical thinking and decision-making skills, as well as critical foundational knowledge for IT specialists. This includes key elements of data science, software engineering methodologies, algorithm representation, and an introduction to natural language processing and machine learning algorithms.

The IT Specialist Artificial Intelligence courseware focuses entirely on machine learning. It’s designed for students who want to both become AI-enabled learners and develop best practices for designing, evaluating, deploying, and monitoring machine learning-based solutions in production. This includes extracting, preparing, and analyzing data sets, training and evaluating machine learning models, and more.

With CertPREP training labs, students and IT professionals get the hands-on practice addressing real-world scenarios, without the risk of disrupting your network or business. Labs are cloud-hosted for maximum flexibility and anytime/anywhere availability. Each thirty- to sixtyminute scenario is tailored to a meaningful challenge, with automated assessments and feedback.

Don’t wait for technology to get ahead of you; now is the time to explore comprehensive training solutions and guide the effect of machine learning and AI on your workplace. Contact us today to discuss your company’s needs and prepare the workforce for the future of your business.

Looking for IT training and learning solutions to upskill your existing team or attract new pros?

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