MLOps is a set of strategies and techniques that allow data science teams to quickly and effectively create, deploy, and maintain ML models in production environments.

The initial launch of TensorFlow sparked a surge in Deep Learning architectures and solutions, due to its popularity as a framework for handling various artificial neural networks.

Data science has exploded as a practice in recent years, with open-source technologies such as Linux and Kubernetes playing a major role in driving innovation.

Learning MLOps can give you valuable skills to develop and maintain ML/AI models more efficiently and effectively, making you more attractive to employers looking for data professionals with experience in this discipline.

Linear Algebra is a vital cog in data scientists’ skill set that learners don't bother much about because they find maths intimidating.

Machine Learning Engineer is one of the most lucrative and dynamic career paths in Data Science and Ai.