Applied Data Science

Applied Data Science teaches you how to turn raw data into meaningful insights and intelligent systems. You will learn how to clean, visualize, and work with diverse data types. Explore machine learning algorithms, image processing, and neural networks that power technologies like self-driving cars and AI language models. You will develop practical skills to analyze data, build predictive models, and understand the challenges behind robotics and intelligent machines.

Opening up Applied Data Science courses

In Applied Data Science, everyone can enter any of the 100 and 200-level courses. If you want to take one of the 300-level courses, you need to first complete the Mathematical Methods gateway.

Courses in Applied Data Science

Gateway

Mathematical Methods

Introduces linear algebra (vectors, matrices, eigenvalues) and calculus (limits, differentiation, integration) to construct and solve equations. Provides problem‑solving skills applicable across disciplines.

100-level

Introduction to Data Science

Data science is the science of extracting meaningful information from data. In this course, you develop foundational abilities in data visualization as well as data cleaning and manipulation. Next to traditional data coming in the form of tables, we explore non-traditional data types such as spatial data and text data. The course includes much hands-on work with example data sets coming from sciences, social sciences, and arts and humanities.

200-level

Machine Learning

Machine learning deals with extracting patterns from data and making predictions. In this course, we focus on core techniques and algorithms ranging from simple linear regression to advanced tree-based methods. In the theoretical part of the course, we discuss the strengths and weaknesses. of the different methods. In the practical part of the course, students apply machine learning methods to real data from fields such as medicine, physics, or economics.

200-level

Image Processing & Computer Vision

The course covers the processing of image data to turn images into better images and the analysis of image data to gain high-level understanding of the content of images. Students also learn about feature and object detection and tracking. Image processing and computer vision are highly relevant to the medical domain, self-driving vehicles, interactive gaming, robotics, crowd and traffic management, and many other application areas.

300-level

Neural Networks & Deep Learning

Neural networks have enabled major advances in areas such as computer vision, large language models, and generative AI. This course focuses on the underlying theory as well as practical implementations. We start by building and training our own basic neural networks from scratch. We then move on to more complex neural networks for applications such as computer vision. Finally, we discuss recent developments in large language models (such as ChatGPT) and image generation models (such as DALL-E).

300-level

Robotics

This course focuses on crucial computational problems in robotics. Among the topics that we address are forward and inverse kinematics, which deal with controlling a robotic arm in such a way that it can accomplish a given task. We also consider the problem of modelling and planning the motion of an autonomous robot in an environment with obstacles, as well as local collision avoidance. Finally, the course focuses on modelling and planning of various forms of robotic grasping and manipulation.

Also consider these options:

Data Science & Intelligent Systems

The other fields within the Data Science & Intelligent Systems cluster.

Data Science & Intelligent Systems

Explore Business!

To transform numbers into impact and insights into opportunity.

Business

Explore Philosophy!

To think critically about what data means and how it’s used.

Philosophy

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The UCR Program Builder is designed to help you easily plan your academic program. Step by step, the tool guides you through selecting courses, building a balanced curriculum, and meeting UCR’s academic requirements.

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Applied Data Science

Applied Data Science

Opening up Applied Data Science courses

Courses in Applied Data Science

Courses in Applied Data Science

Mathematical Methods

Mathematical Methods

Introduction to Data Science

Introduction to Data Science

Machine Learning

Machine Learning

Image Processing & Computer Vision

Image Processing & Computer Vision

Neural Networks & Deep Learning

Neural Networks & Deep Learning

Robotics

Robotics

Also consider these options:

Also consider these options:

Data Science & Intelligent Systems

Data Science & Intelligent Systems

Explore Business!

Explore Business!

Explore Philosophy!

Explore Philosophy!