Jun 26, 2025 · Applied machine learning is the implementation of ML algorithms to produce resolutions for various tasks, such as predicting future outcomes and streamlining operations.

We will briefly study the underlying principles of diverse machine learning approaches such as anomaly detection, ensemble learning, deep learning with a neural network, etc.

Explore the processes used to develop real-world systems that involve signals, sensors and hardware, such as robots or mobile phones. Through lectures, tutorials and labs, you'll delve …

The Applied Machine Learning course teaches you a wide-ranging set of techniques of supervised and unsupervised machine learning approaches using Python as the programming language.

This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods.

Through a variety of lecture examples and programming projects, students will learn how to apply powerful machine learning techniques to new problems, run evaluations and interpret results, …

The MS in Applied Machine Learning focuses on the methods and techniques of creating models and algorithms that learn from, and make decisions or predictions, based on data.

Description: Machine learning has been essential to the success of many recent technologies, including autonomous vehicles, chatbots, robotics, search engines, genomics, automated …

Our curriculum is designed to equip students with the skills to design, deploy, and optimize machine learning solutions on platforms such as drones and embedded systems. By the time …

Course Description You will learn how to implement and apply machine learning algorithms. This course emphasizes practical skills, and focuses on teaching you a wide range of algorithms …