11 courses with the subject DSAI, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
DSAI 101RAI FOR EVERYONE3
Artificial Intelligence is changing the world. It is changing jobs, creating them, and even replacing them (but less than you think). More than ever before, companies need employees who can use AI tools to solve problems creatively and responsibly. This non-technical AI crash course builds the foundational skills needed to do that and is designed to be valuable to anyone. Learn how to distinguish problems that AI is useful for, master prompt engineering to improve outputs, detect AI-generated output, analyze ethics and privacy, and stay up-to-date on one of the most transformative technologies of our lifetimes.
This course introduces students to core concepts and the current landscape of Data Science, Machine Learning, and Artificial Intelligence. Students explore how these fields intersect through a shared data lifecycle, including problem definition, data collection, preparation, analysis, and communication of results. Topics include types of data, sampling methods, web scraping, handling missing data, basic data storage, descriptive statistics, data visualization, dashboards, and ethical use of data. While a range of tools and technologies are discussed, this is not a programming course, and no prior programming experience is required.
An introduction to traditional methods of Data Science with an emphasis on the relevant mathematics, statistics and theory. Topics to include regression, clustering, discriminant analysis, naive Bayes, variable selection, decision trees, and time series.
This course takes a deep dive into machine learning models, natural language processing, and time series in Python. The following topics are covered: time series, regression, unsupervised learning, deep learning, feature engineering, and ethical implications. Students will use both unstructured and structured data to build machine learning models and use the models to create actionable and ethical predictions.
Artificial Intelligence decisions are often only as good as the person asking the question. In this course, youll learn how to ask the right ones and increase the productivity and innovation you can achieve with AI. Create better prompts, compare and contrast strengths and limitations, evaluate outcomes, and by the end of this course, understand and leverage the power of AI for decision-making across any discipline, opening up new career paths and personal growth.
Generative AI has introduced a new paradigm of AI: the co-creator. Top professionals and companies use AI to improve productivity and creativity every day, and in this course, youll learn the iterative prompting, search, and functional evaluation metrics powering these uses. By the end of this course, youll integrate AI tools into a variety of creative skill sets, and your own projects, building new avenues for creativity in your career.
An introduction to the established Data Science tool kit including clustering, the many faces of regression, random forests, and support vector machines. An optional introduction to neural nets and deep learning. An introduction to the presentation of Data Science results including proper visualization and storytelling. The course consists of three lecture hours and one two-hour laboratory per week.
This course is a technical approach to cutting-edge AI methods. Students will produce machine learning models to solve business problems, evaluate modern AI use cases (such as computer vision) and adapt Large Language Models (LLMs) for specific applications.
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.
Prescriptive AI teaches you the highest-value technical AI skills available. Youll 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, youll be able to frame problems and train models that make you a desirable hire in any industry.
This course explores the challenges and opportunities in the evolving field of Data Science by evaluating case studies across the entire data science pipeline. Classes are interspersed with student presentations and discussions around best practices, technical implementation, and ethical concerns. Based on the reviewed case studies, students will analyze the future of Data Science and their role within the field.
