Coursera
4 weeks to complete at 10 hours a week
This specialization helps software engineers build practical machine learning capabilities that extend beyond model training into full production workflows. You'll learn to build, optimize, deploy, and monitor machine learning systems.
Basic programming experience and familiarity with software development concepts. Python and data structures knowledge is helpful but not required.
The program covers the full machine learning engineering lifecycle, including mapping business problems to ML tasks, training and optimizing models, designing reliable data pipelines, and deploying ML services in production environments. Hands-on projects reinforce each stage of the ML lifecycle.
Coursera is a leading online learning platform that partners with top universities and industry experts to deliver high-quality, career-relevant courses and programs. This specialization is designed and taught by industry professionals to provide practical, applied skills in machine learning engineering.
This specialization will equip you with the skills to integrate machine learning into production software systems, build and deploy scalable ML services, and maintain the reliability and performance of ML models in real-world applications. The skills learned are applicable to roles such as software engineer, machine learning engineer, and platform engineer.
