CDSP is designed for practitioners who are seeking to collect, wrangle, and explore datasets, plus apply statistical models and artificial intelligence algorithms to extract and communicate insights.
To ensure your success in this course, you should have at least a high-level understanding of fundamental data science concepts, including, but not limited to: types of data, data science roles, the overall data science lifecycle, and the benefits and challenges of data science. You should have also have experience with high-level programming languages like Python. Being comfortable using fundamental Python data science libraries like NumPy and pandas is highly recommended.
166 W. Main Street, Suite 204B
Mesa, AZ 85201
In this course, you will implement data science techniques in order to address business issues. You will: Use data science principles to address business issues, apply the extract, transform, and load (ETL) process to prepare datasets, use multiple techniques to analyze data and extract valuable insights, design a machine learning approach to address business issues, train, tune, and evaluate classification models, train, tune, and evaluate regression and forecasting models, train, tune, and evaluate clustering models, and finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance.
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):
If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.