Software Engineering for Data Analysis
The course covers the development of data processing systems and machine learning.
- How to bring the developed model into production?
- What should I do to work together on high-tech software?
- How not to lose previously achieved research results?
As a result of mastering the course, students acquire the skills of industrial development of machine learning algorithms, conducting repeatable experiments, using big data, testing and project execution processes in the field of machine learning.
- Structuring data processing programs (CODE).
- Writing reliable code (CODE).
- System design and data storage in machine learning (DATA) systems.
- Processes and types of work in the Data Analysis Project (PROC).
- Ensuring repeatability of results (PROC).
- Testing of high-tech software (TEST).
Practical tasks during the course + course project.
The final grade for the course is formed from the success of completing tasks during the semester - 10% for each task, and confirmation on an oral survey of ownership of each of the topics of the course (CODE, TEST, DATA, PROC) - 40% of the grade.