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IBM AI Engineering Professional Certificate
Coursera · IBM · Updated March 2026
Platform rating
4.6/5
AI Tutor Rating
8.6/10
Duration
4 months at 10 hours a week
Classes
35
Professional certificate covering ML algorithms, deep learning frameworks, and deployment workflows including Spark, Keras, PyTorch, and TensorFlow.
What you'll get
Build supervised and unsupervised ML models
Deploy ML pipelines with Apache Spark
Build deep learning models with Keras, PyTorch, and TensorFlow
Apply LLM and RAG techniques in projects
Fit
Best for
Developers
AI Engineers
Data Scientists
Technical Builders
Not ideal for
Complete beginners
Non-technical learners
Prerequisites & pricing
Prerequisites
Intermediate; recommended experience
Pricing
Subscription (Coursera)
Certification
Certificate
Growth Leverage: Completing the IBM AI Engineering Professional Certificate opens doors to roles such as Machine Learning Engineer, Data Scientist, and AI Specialist, and prepares candidates for valuable certifications like AWS Certified Machine Learning and Google Professional Machine Learning Engineer.
Skills Value: Employers pay a premium for skills in ML and deep learning, with salaries for AI Engineers often exceeding $120,000 annually, due to the demand for expertise in deploying scalable ML models and leveraging frameworks like TensorFlow and PyTorch to solve complex business problems.
AI Engineering
Deep Learning
PyTorch
TensorFlow