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The course, thanks to which I learned the skills of communication with stakeholders, design of business analysis project documents, requirements gathering, creation of Pipelines and organization of ETL processes, design of dashboards.
The specialty that started my introduction to analytics helped me learn both the basic practical tools: Excel, Python, SQL, Power BI, as well as probability theory and mathematical statistics.
The courses in the specialization helped me to better structure my knowledge, deepen my understanding of the steps an analyst takes when working on his or her projects, as well as introduce me to tools that were new to me, such as Tableau and the R programming language.
Successfully passed the certification exam for Associate Data Analyst, consisting of 60 theoretical questions and problems on Python and SQL statistics, as well as practical work on data extraction and cleaning in PostgreSQL.
Discovered the skills needed for a career in data analysis. Learned foundational concepts used in data analysis and practice using basic software tools for data analytics and data visualization.
Technology specialization, where I learned more in-depth Python, structured my knowledge of ETL, BigData, and learned how to collect and label data. In the end, I completed a graduation project where I developed a service solving a business problem of a medical institution.
Foundational knowledge needed to be a successful Data Engineer. Develops an understanding of database schemas, design concepts and cloud tools, as well as the ability to manipulate and cleanse data.
A comprehensive course on systems analysis. I studied requirements analysis, system architecture design, modeling (UML, BPMN), and API design. This course provided deep insights into the software development lifecycle and the role of a systems analyst in bridge building between business requirements and technical solutions.