AI Certifications

Google's foundational certificate for using AI tools in the workplace. Covers responsible AI use, prompt writing, and AI-assisted workflows. No coding required. Shareable on LinkedIn.

Proves you can build and train neural networks using TensorFlow and Keras. Exam is 5 hours — build 4 models during the test. Highly respected in the ML industry.

AWS's specialist certification for ML practitioners who build and deploy models on the AWS cloud. Covers SageMaker, data engineering, modeling, and deployment. Strong career ROI.

AWS's new foundational AI certification (launched 2024). Validates understanding of AI/ML concepts, generative AI, and AWS AI services. No hands-on ML experience required.

Design and implement AI solutions using Azure Cognitive Services, Azure Machine Learning, and Azure OpenAI Service. Practical focus on building AI applications in the cloud.

Foundational certification covering AI and ML concepts on Azure. Ideal for non-technical roles looking to validate AI knowledge. No programming required. Often a precursor to AI-102.

6-course series covering ML fundamentals, deep learning with Keras, PyTorch, and TensorFlow, plus computer vision and NLP. Comes with an IBM-issued digital badge and Coursera certificate.

Validates advanced skills in building, scaling, and deploying ML solutions on Databricks and Apache Spark. Highly valued in enterprise data science roles. Requires solid ML engineering experience.

Andrew Ng's updated 3-course ML specialization — the modern successor to the legendary Stanford ML course. Industry-standard credential, recognized globally. 1M+ enrolled.