Not Your Typical Bootcamp
This accelerator covers methods of statistical inference, machine learning, data visualization, data mining and big data, all of which are key for the daily work of a data scientist. During the course, students will apply methods in Python Scikit-learn library to perform typical data processing, e.g. classification, regression and clustering of data. Basic Python programming skills and working knowledge of data structures and algorithms is required, as is fundamentals of calculus and linear algebra, probability and statistics. The course includes 75 hours of instructor-led training and in-class hands-on work.
Click here for the Course Outline.
- Apply Methods in Python
- Perform classification, regression and clustering of data
- 7.5 Continuing Education Units/ 75 Professional Development Hours
Who Should Enroll
Anyone looking to jump start into a career in Data Analytics.
Prerequisites: Basic Python programming, Data structures and algorithms, Calculus and Linear algebra, Probability and Statistics, basic machine learning