Machine Learning

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Prepare for DP-100: Data Science on Microsoft Azure Exam (Coursera) Coursera
Microsoft

Prepare for DP-100: Data Science on Microsoft Azure Exam (Coursera)

Elevate your career in cloud computing by preparing for the DP-100: Data Science on Microsoft Azure Exam. This course is designed to equip you with the knowledge and skills needed to successfully pass the certification exam and demonstrate expertise in planning and deploying data science workloads on Azure. Whether you're a data scientist, analyst, or someone looking to specialize in cloud-based data solutions, this course will guide you through essential topics such as setting up an optimal working environment, running data experiments, training predictive models, and managing machine learning models in production.

Nov 9th 2026
5-12 Weeks
Advanced Bayesian Statistics Using R (edX) EdX
University of Canterbury,UCx

Advanced Bayesian Statistics Using R (edX)

Take your understanding of Bayesian inference to the next level with our Advanced Bayesian Data Analysis Using R course. This professional program builds on foundational knowledge to explore complex topics such as modeling latent variables, Bayesian model averaging, generalised linear models, and Markov Chain Monte Carlo (MCMC) methods. Utilize R for practical application and deepen your expertise in statistical analysis.

Self Paced
Self-Paced
Technologies and platforms for Artificial Intelligence (Coursera) Coursera
Politecnico di Milano

Technologies and platforms for Artificial Intelligence (Coursera)

Dive into this comprehensive course that covers essential hardware technologies for machine and deep learning. Learn about different families of machine and deep learning platforms, including libraries and frameworks, to enhance your skills in designing and developing smart applications and systems.

Nov 9th 2026
4 Weeks
MLOps for Scaling TinyML (edX) EdX
HarvardX,Harvard University

MLOps for Scaling TinyML (edX)

Embark on a journey into Machine Learning Operations (MLOps) with a focus on scaling Tiny Machine Learning (TinyML). Learn best practices for deploying, monitoring, and maintaining ML models that are small enough to run on resource-constrained devices. This course is designed for developers, data scientists, and engineers who want to leverage the potential of tiny machine learning in their applications.

Self Paced
Self-Paced