Relational databases
Offline
SQL and data analysis: relational DBMS and Python integration
5.0
(1)
Reviews
5
Students
30 hours
Duration
About the Course
The course is aimed at studying the principles of operation of relational databases and mastering the SQL language for creating, managing and analytical data processing. Database design, normalization, transactions, complex SQL queries (JOIN, SubQuery, CTE), as well as integration of Python (Pandas, NumPy, Matplotlib) data for analysis and visualization are considered.
Curriculum
3 modules
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1 Databases and their types. The structure of a relational database.
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2 Creating and deleting databases and tables. Types of data in tables. Restrictions on columns.
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3 Data manipulation. INSERT, UPDATE, and DELETE operators.
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4 Types and structure of SQL queries. SELECT, WHERE, DISTINCT, TOP, IS NULL. The BETWEEN, IN, and LIKE operators.
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5 Sorting and grouping. Arithmetic and logical operations, aggregate functions.
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1 Multi-tabular queries. JOIN, INNER JOIN, OUTER JOIN.
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2 Subqueries: single-line and single-column subqueries. Multi-line and single-column subqueries.
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3 Multi-column subqueries. Correlated subqueries.
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4 Generalized Tabular Expressions (CTE). The WITH operator.
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5 Combining requests. The UNION operator.
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1 Conditional logic: the CASE statement and the IF function.
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2 Stored procedures and functions.
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3 Importing SQL data into Python and getting to know NumPy arrays. The Pandas library.
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4 An introduction to SQL data visualization. Matplotlib basics and the Figure object.
Student Requirements
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Basic knowledge of programming.
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Understanding algorithms and data structures.
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Experience working with databases is not required.
Course Experts
Student Reviews
5.0
(1)
T
Tannur.fx
16 Mar 2026
"9"