Data Science

This course provides a general overview of the common topics in the data science domain. Students are introduced to data collection, data engineering, machine learning algorithms and packages, data visualization techniques and related programming tools and frameworks.

Data collection, data engineering, machine learning algorithms and packages, data visualization, and related programming tools and frameworks. These topics are covered in DSC 105, but here they will be discussed in more depth, and projects will reflect real world challenges. In addition, data mining techniques and more advanced machine learning algorithms will be introduced. In some cases, the statistical concepts behind some of the algorithms will be discussed. Projects may involve text and image classification tasks, developing regression models, etc.

Generative AI is AI that can produce new content - answers, code, music, art, video, and more. Those who harness it are more productive, more in demand, and more highly paid. Those who don’t will be left behind. This lightly technical intro will teach you the foundational skills to level up your understanding of transformers, LLMs (Large Language Models), and more. By the end of this course, you will engineer better prompts and apply chain-of-thought techniques to generate AI solutions. (Same as CSC 271.)

AI jobs are exploding, but the pathways to discover and land them aren’t always clear. In this course, you’ll explore the wide - and growing - variety of career pathways your AI skills unlock. You’ll understand salaries, growth trends, target jobs, and the skills needed to land them. You’ll deepen an understanding of resume and interview skills, achievable goals, and careers that meet your needs for meaning, excitement, and a lucrative financial future. (Same as CSC 272.)

This course presents the art and science of turning data into readable graphics. We’ll explore the design and creation of data visualizations based on data available and tasks to be achieved. This process includes data modelling, data processing, mapping data attributes to graphical attributes, and strategic visual encoding. Students will evaluate the effectiveness of visualization designs and create their own data visualizations.

This course aims at providing mathematical explanations of the machine learning models discussed in DSC 105 and DSC 205. Topics include probability, probabilistic models, statistical concepts related to machine learning, and analysis of some of the popular machine learning models with the help of probability and statistics. Projects will reflect real world challenges and will aim at discovering how machine learning models work.

This course brings the predictive power of AI to your toolbox. You'll discover how to analyze, interpret, and forecast complex data using AI tools. Learn through hands-on activities and practice techniques like regression analysis and neural networks. You'll also explore how to fill in missing data and estimate your confidence in your predictions. By the end of this course, you'll have in-demand skills for your career and be ready to take on more advanced studies. (Same as CSC 373.)

This course will offer programming languages and techniques necessary to process and analyze data. Special emphasis will be on advanced use of Python and R languages to analyze datasets from a variety of disciplines and industries.

Students will apply their data science knowledge and technology to a real world scenario. Students can accomplish this by working with a local businesses, acquiring data from governmental entities, or through an internship. The capstone will conclude with a final deliverable report and presentation to the business, government, or internship entity.

Individual work on special topics in data science.

Prescriptive AI teaches you the highest-value technical AI skills available. You’ll use the advanced techniques of optimization, evolutionary computation, surrogate modeling, and agent building, helping you use AI for its true superpower: faster, better business decisions. Through real-world challenges and hands-on projects in decision-making, robotics, and more, you’ll be able to frame problems and train models that make you a desirable hire in any industry. (Same as CSC 474.)

Study of selected topics in data science.