Kubernetes is an open-source platform for automating the deployment, scaling, and management of containerized applications. It helps ensure high availability, scalability, and efficient resource usage by orchestrating containers across clusters. Kubernetes is widely used to streamline DevOps workflows and modern cloud-native development.

Machine Learning (ML) is a branch of artificial intelligence that enables systems to learn from data and improve over time without being explicitly programmed. Core concepts include supervised and unsupervised learning, algorithms like decision trees and neural networks, and model evaluation techniques. ML is widely used in fields like finance, healthcare, and recommendation systems.

Deep learning is a subset of machine learning that uses neural networks with many layers to model complex patterns in data. It excels in tasks like image recognition, natural language processing, and speech analysis. Deep learning enables systems to automatically learn features from large datasets with minimal human intervention.

Data Science with Python involves using libraries like Pandas, NumPy, Matplotlib, and Scikit-learn to analyze, visualize, and model data. Python’s simplicity and rich ecosystem make it a powerful tool for data cleaning, statistical analysis, machine learning, and building data-driven applications.