Position: Machine Learning Engineer
Category: Data Science
English level: upper
Years of experience: 1

1) Graduated from Karpov's Data Analyst courses. During the course I learned:
- Properly handle data
- Use Python for data analysis (pandas, numpy, matplotlib, seaborn)
- Compose queries in ClickHouse and PostgreSQL
- Based on the results of A / B testing, draw conclusions about the best version of the product
- Basic concepts of probability theory, conducting statistical tests
2) Completed a course on the basics of Python on Stepic
3) Graduated from the OOP Python course on Stepic
4) Graduated from the Deep Learning Specialization from Deeplearning.ai on Coursera
I started my career teaching mathematics. I prepared applicants for admission to universities.
After graduating I stayed to work at my university in the teaching and methodological department.
During quarantine, I simultaneously worked as a business analyst in the "E- Prosecutor" project for the Azerbaijani prosecutor's office. My tasks were:
1) Interaction with the client and obtaining information about the project from him
2) Analysis of the project workflow
3) Development of the project structure
4) Preparation and writing of a technical document of the developed program
5) Designing project modules
6) Testing the developed program

Further, I became interested in the field of machine learning. To develop in this area, I take various courses on educational platforms such as Stepic, Coursera, as well as on various Youtube channels.
I like machine learning because I can apply my mathematical knowledge in parallel with programming. I'm interested in what's "under the hood" of machine learning algorithms, as it will help me to apply models intelligently to solve future problems.
Python is a good tool for this. Therefore, I focused on studying this particular programming language: on the study of data structures and algorithms, as well as on object-oriented programming.