SQL: the path from scratch
to PRO in the world of
business analytics

You'll learn a key data science tool, learn how to solve analytical problems, prepare for technical interviews, and expand your career opportunities.
Enroll Now
Why do you need SQL?
SQL is a language that allows you to interact efficiently with databases, which is especially important in areas such as commerce, finance and telecommunications. It helps to quickly analyze data, identify sales trends and segment customers, which in turn allows you to personalize your marketing strategies.
Who is this course suitable for?
Analyst
You'll be able to dive into ambitious projects and solve even the most intricate problems. We'll teach you the art of writing complex SQL queries and share the secrets of working with a variety of databases to make you a master of analytics.
Marketer
You'll discover the world of user behavior through the data you extract from the database. Learn how to get the information you need on your own, without the need for developers, and make fact-based decisions.
Product Manager
You'll be able to make strategic product decisions based on solid data. We'll show you how to extract and analyze information from the database, turning it into valuable insights for your business.
How to take the course
Immersion in theory
Study anywhere, anytime - our educational platform is always at your fingertips! Every week, new modules with exciting video lessons open up new horizons of knowledge for you.
Practice with the SQL trainer!
Practise on the SQL trainer! Problems and exercises await you. Immerse yourself in practice and become a SQL master with every new assignment!
Preparing for an interview
Practice your problem-solving skills during an interview so you can confidently demonstrate your abilities to employers and stand out from other candidates!
Course experts
Nicola Kreiser
Head of Development and Data Science, Satyhome,
Daniel Kramer
Data Platform Engineer, Exness
Eric Gronsky
Backend developer .net & SQL, VDcom company
Marina Tsvetkova
Data Analyst at GlowByte Consulting
On the course you will learn
  • SQL and relational database basics: basic concepts and concepts, SQL syntax
  • Form SQL queries to databases, retrieve required data sets
  • Combine data from multiple tables into a single data dump
  • Aggregate/aggregate and merge data
  • Make key calculations using functions
  • Make changes to data tables (up to and including changing the structure of existing tables or creating new ones).
  • Learn MySQL Workbench program for working with the database
Course program
Introduction
3 lessons
  • Author's introduction
  • Addition
  • How will we learn
Basic concepts of relational databases
15 lessons
  • Why do I need all this?
  • Relational Databases and DBMSs
  • Table (array)
  • Row: record, field, object, tuple
  • Column: attribute, characteristic, attribute, variable
  • Data (values)
  • Array awareness
  • Basic basic data types
  • Limitations\Checking data (values)
  • Notion of the level of granularity (granularity) of the data\array
  • The paradigm of “working with the whole column”
  • Modeling: links between several tables
  • Types of links
  • Section Summary
  • Understanding the basics
General concept and introduction to SQL
7 lessons
  • What is SQL
  • SQL as an ETL toolkit
  • Command Groups in SQL
  • How to use SQL
  • Choosing a toolkit for SQL training
  • Preparing the workplace: installing the selected tools
  • Results
Getting to know MuSKL Workbench: wassis for a pussy start
17 lessons
  • MySQL Workbench interface parsing
  • Getting acquainted with the interface
  • Databases and their structure
  • Familiarizing yourself with a database using one of the databases as an example
  • Exporting and Importing a database
  • Importing a training database
  • Importing another training database
  • SQL scripts for uploading data
  • Try a simple query
  • SQL script writing helpers
  • Simple query with hints
  • Editing the uploaded data (and making edits to the database if necessary!).
  • Editing strings
  • Exporting unloaded data to external files (and importing them into the database).
  • Downloading tables to Excel (our favorite native)
  • Importing a couple more training databases
  • Section totals
Downloading data from a specific table: simple SELECT queries
13 lessons
  • Introduction to SELECT queries
  • Basic SQL construct for SELECT for all occasions
  • Simple data selection from a table: SELECT FORM
  • Features of unloading
  • Selects only non-repeating values (no duplicates): DISTINCT
  • Uniqueness selection
  • Sorting rows by extracted columns ORDER BY + ASC, DESC + LIMIT
  • Sorting an upload
  • Renaming columns in query: AS
  • Aliasing
  • How can a beginner (and not only) not get confused in SQL code afterwards? Using comments
  • Commenter
  • Section summary
Filtering strings in SELECT: conditions for selecting/filtering strings WHERE
20 lessons
  • What is culling\ string filtering and why it is needed
  • String filtering by condition: WHERE
  • Trying string selection
  • Mathematical selection
  • Selection of strings in the range of values: BETWEEN...AND...
  • Range
  • Selection of strings by belonging to a list\set of values: IN
  • List set
  • Selection of strings by incomplete/partial matching (similar to the example): LIKE
  • Similarity
  • Filtering/selection of unknown values: IS NULL
  • Search for empty and unknown values
  • Multiple (several) selection conditions: AND and OR operators
  • Many different conditions
  • Complex conditions: combinations of operators in each other.
  • Attachments
  • Reverse: NOT operator
  • Unload a completely different thing
  • Section summary
Calculations in queries
35 lessons
  • Why do we need calculations in queries?
  • Calculated columns
  • Simple math operations
  • Math
  • Mathematical functions
  • Functional math
  • Logical functions
  • Simple logic
  • Cases
  • Conditions with calculations
  • Substitution instead of NULL
  • COALESCE
  • COALESCE in calculations
  • Text functions
  • Merging the full name
  • Character slicing
  • Pulling a value from the MIDDLE of a cell value
  • Let's play with registers
  • Functions for working with dates
  • Dates of acts and not only
  • Features of column calculation in the presence of unknown values: NULL
  • Measures\ Aggregates (scalar\one value summarizing all values in a column\s)
  • Quantity: COUNT and COUNT(DISTINCT)
  • Quantity as a single number
  • “School” measures: SUM and AVG
  • Summing and averaging
  • Some statistics: MIN and MAX, and for “gourmets” STDDEV
  • MINIMAX
  • Text aggregation
  • Text Aggregation
  • To be or not to be? Measures for string selection conditions (filtering) in WHERE!?
  • Can we use Math, Logical and Dat functions when calculating measures?
  • So what about aggregation functions to calculate a column?
  • Systematizing knowledge of the last 3 lectures
  • Section summary
Basics of window calculations for new columns
17 lessons
  • What is WINDOW?
  • Trying pure OVER()
  • “Slicing windows in PARTITION BY array
  • One window, two windows....
  • Sorted windows: sorting rows in a window via ORDER BY
  • Sorting...
  • Aggregation functions (SUM,AVG,COUNT,MIN,MAX) for window calculations
  • Behavior of aggregates in sorted windows (partition along with order)
  • Tests: reinforcing the concept of WINDOW
  • Introduction to non-aggregate special functions
  • Non-aggregation special functions that exist only with OVER: ranks/ratings
  • Age rankings for M and W
  • Rankings
  • Non-aggregation special features that exist only with OVER: line-by-line bias
  • Familiarizing ourselves with offset functions
  • Let's play backand...
  • Section summary
Changes in array granularity: grouping/generalization and its filtering
10 lessons
  • Memories of granularity\detailing.
  • Filtering and Aggregation (measure) as tools to reduce the granularity of an array
  • Changing granularity/detailing through grouping: GROUP BY
  • Practicing grouping
  • Important points to understand when working with GROUP BY
  • Filtering grouped data: HAVING
  • Aggregation filtering
  • Nuances for a deeper understanding of how HAVING works
  • GROUP BY, HAVING and WHERE: nuances to round out the section
  • Section summary
Unloading data from several tables into one table: assembly/join, Join and Union
20 lessons
  • What if the columns to upload are contained in different tables?
  • Memories of keys\ row identifiers and more
  • Implicit table join by filtering rows: using identifiers in WHERE
  • Joining, but implicitly
  • Joining three tables
  • Recollections of the different types of relationships between tables
  • How to see and read table relationships in MySQL Workbench
  • Seeing the relationships on the model
  • Internal join: join tables with row loss [INNER] JOIN...ON
  • Playing with the model when joining 3 tables
  • Synchronize model with database
  • External join of 2 tables: LEFT\RIGHT [OUTER] JOIN...ON
  • Trying external JOINs
  • Creating an identifier “in flight”
  • Remember JOINs well: comparing internal and external table joins
  • Joining tables to add rows: UNION
  • Joining table rows
  • Rows from different tables
  • Self-join with UNION
  • Results of building a set of tables
The concept and basics of request formation
12 lessons
  • The concept of subqueries
  • Results returned by subqueries
  • Column calculation (after basic SELECT)
  • Column from another table without JOIN
  • Calculating tables (for FROM and JOIN)
  • Subquery table
  • Selecting/filtering rows (for WHERE and HAVING)
  • (Sub)query filtering
  • List generation (for IN operator arguments in WHERE and HAVING)
  • Retrieving lists
  • Comparisons with a set of values: ALL and SOME\ANY operators
  • Summary of subqueries
Complex requests
6 lessons
  • What is a “complex request”?
  • Learning how to read a complex query
  • Reading SQL script
  • Learning how to write your own complex queries
  • Writing a complex query ourselves
  • Section results
Basics of making changes to data contained in a database: DML
12 lessons
  • What is DML
  • DML in the Workbench user interface
  • Make edits through the interface
  • Adding new data: INSERT INTO
  • Mastering INSERT INTO
  • Modifying existing data: UPDATE
  • Trying UPDATE data update
  • Deleting data: DELETE
  • Deleting from tables
  • SELECT in DML
  • Trying SELECT in UPDATE and DELETE
  • Section Summary
Basics of object formation in Databases: DDL
19 lessons
  • What is DDL and objects
  • Visual DDL in the MySQL Workbench user interface
  • Own database with tables in the user interface
  • Creating and deleting database and tables: CREATE and DROP
  • Creating and deleting
  • Data Types in SQL
  • Dealing with types
  • Simple constraints: UNIQUE, PRIMARY KEY, AUTO-INCREMENT, NULL\NOT NULL, DEFAULT
  • Let's restrict things a bit...
  • Restrictions with data validation: CHECK
  • Checking data by condition
  • FOREIGN KEY constraint with customizing actions ON DELETE, ON UPDATE
  • Trying out foreign key constraints
  • 1 question Another way to create constraints for data management: triggers
  • Our first trigger
  • Modifying tables, columns and their constraints: ALTER, ADD, MODIFY,RENAME, TRUNCATE
  • Changes to tables, columns and constraints
  • Changes to primary and foreign keys
  • Section summary
Basic understanding of the data process
7 lessons
  • The process of working with data
  • Modeling: creating tables and relationships between them
  • ETL: extracting, transforming (cleaning, preparing, calculating) and loading data
  • Data Visualization and Analysis
  • SQL in notebooks (Jupiter, Google Colab, Apach Zeppelin...): connecting and using it.
  • Not directories alone: AI assistants (using CHAT GPT as an example)
  • Section summary
Bonus
3 lessons
  • The whole course in one slide
  • Tutorial
  • Bonus lecture

After completing the course you
will receive a certificate

The Bureau of Labor Statistics projects that data scientist jobs will increase 35% by 2032, giving you access to a hot new field.
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Reviews
Helena
The course has a lot of practical assignments for independent work, which help to build skills. The assignments are not too difficult, but sometimes you need additional study. The speaker is great at teaching the course and the tutor is just great! :) I am very satisfied!
Nik
This course was a real eye-opener for me, just top notch. The combination of humor, knowledge and presentation of the material is amazing, as well as the willingness to answer any questions and be patient. That kind of involvement is really appreciated nowadays. All in all, the course left me with extremely positive impressions!
Michael
Absolutely a good fit. Although the course is positioned as for business users, it was suitable for jun. I tried to do a couple of SQL quizzes - and successfully coped with the skills I learned in the course.
We answer your questions
I've never worked with SQL. Can I do it?
Of course! You will succeed even without special knowledge - just pay more attention to practice and read additional literature. The rest will be helped by practicing experts who will accompany you throughout the course.
What is your refund policy for courses?
We try to be flexible to your needs. Therefore, we take circumstances into account and refund all or part of the tuition fees when contractually agreed.
How long will it take me to complete the course?
It depends on you. Some people complete it in 2 months of intensive work. Some need more time. You learn at your own pace at any time of day or night.
Where to go to work with SQL knowledge?
SQL is needed in the work of analysts and marketers, software testers and programmers, data scientists and ML specialists - everyone who works with big data.