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Data Institute Certificates
Certificate courses at the University of San Francisco's Data Institute provide a learning experience for those seeking to increase their breadth and depth of knowledge of data science tools and techniques.
Courses are taught by MS in Data Science faculty and expert practitioners from leading tech firms. We offer courses for analysts, managers, executives, and engineers looking to augment their skills, as well as introductory-level courses for students without a background in data science. To accommodate working adults, all certificate courses are scheduled in the evening.
Offered in Fall 2024
- Generative AI for Coders: This course explores the process of constructing generative AI models, you'll gain the skills and knowledge necessary to leverage these models and frameworks.
- Python for Data Analysis: Learn to write Python code to solve data-related problems, create and manipulate simple data structures, develop and test code, read and use programming language documentation, define Python functions and modules, and work with NumPy, pandas and Matplotlib.
- SQL For Data Analysis: Learn to use SQL to extract and transform data from a variety of sources across different applications and industries. After completing this certificate, you will be able to write, debug and optimize SQL queries as well as understand foundational database design concepts.
Additional Certificate Courses
- AI & Data Ethics: Explore urgent issues of data ethics, including bias and fairness, privacy and surveillance, and disinformation and manipulation, as well as foundations of ethics and connections with broader social trends and systems.
- Applied Machine Learning: Solve practical machine learning problems using a hands-on approach in application areas such as e-commerce, business intelligence, and bioinformatics. You'll also learn to clean data, apply machine learning techniques to solve practical problems, and analyze data in supervised scenarios with an end-to-end approach.
- Data Science for Marketing: In this course, participants will focus on generating and interpreting statistical and machine learning outputs for effective decision-making. Students will work with the Python open-source coding language to execute common data science procedures used in marketing, including correlation analysis, regression, analysis of variance, segmentation, forecasting, and conjoint analysis. Basic familiarity with Python is required for this course.
- Fundamentals of Deep Learning: Learn the practical details of deep learning applications with hands-on model building using Pytorch. You will work on problems ranging from computer vision, natural language processing, and recommendation systems.
- GeoPandas for Data Analysis: This course, taught by an industry expert, provides an in-depth exploration of GeoPandas, an open-source project that simplifies working with geospatial data in Python. Gain knowledge of Pandas, Python, basic plotting, and GIS fundamentals.
- Introduction to Machine Learning: Learn foundational issues in machine learning, such as cross-validation and the bias-variance trade-off, which are covered with a focus on the intuition behind their use. You'll also explore principal techniques including logistic regression, decision trees, classification, and clustering.
- Large Language Models for Coders: This course is crafted to equip participants with deep, practical insights derived from real-world applications of generative AI.
- Pandas and Numpy for Data Analysis: Master the foundations of Pandas and NumPy for Python and learn to use these packages to import, organize, and clean data from files, websites, and databases. Also learn to manage missing data and create data visualizations. Participants should have basic experience with either Python or SQL.