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Instructor-led SQL and Python labs for small teams.

Database training for analysis teams

Databases and SQL for Data Science with Python

A practical course for analysts, researchers, and technical teams who need to query relational databases, move result sets into Python, and explain the data choices behind a model or report.

Course tools
DBeaver, SQL, Python, pandas
Delivery
Private team workshop or scheduled cohort
Price path
Quoted by phone after cohort size and format are known
Call (403) 995-0220 Prepare a quote call

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Choose the closest starting point

The course adjusts examples and pacing around the work your team already does with data.

Recommended emphasis: Query reading, joins, grouping, window logic, and exporting clean result sets into pandas.

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The syllabus is written as one query run

Each clause represents a course movement, from database connection through tested analysis output.

  1. Drivers, connections, schemas, tables, keys, and safe exploration in DBeaver.

  2. Projection, filters, joins, aggregations, common table expressions, and naming discipline.

  3. Null handling, date logic, sampling, duplicate checks, and query review habits.

  4. Loading result sets, pandas transformations, repeatable notebooks, and export-ready outputs.

A laptop displaying a data analysis workspace

JOIN sql_result TO python_frame

Practice the handoff from database query to Python analysis

Participants work through one complete path: inspect the data, write the SQL, load the result into Python, validate columns, and prepare an analysis-ready dataset.

Retention sample

  • Join customer, subscription, and activity tables.
  • Build a feature set with recency and account age.
  • Move the result into pandas for cohort analysis.
query_name = "retention_features"
frame = pandas.read_sql(sql_text, connection)
frame.groupby("plan_tier")["churn_flag"].mean()

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Prepare the right quote conversation

Use this quick selector before calling. It does not send data anywhere; it simply creates a clear call note for the course discussion.

Quote request: 6 attendees, private team room, two-day SQL and Python workshop with DBeaver labs.
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Workshop rhythm

Database orientation

Connections, schema reading, table relationships, and a shared query naming approach.

SQL for analysis

Joins, aggregates, common table expressions, window functions, and review techniques.

Python handoff

Loading SQL results into pandas, checking shape and types, and preparing an analysis output.

A workstation set up for Python and SQL practice

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Course operator and contact

Training is provided through the DBeaver SQL Ops course desk for teams using SQL databases, DBeaver, and Python in analysis work.

201 Southridge Dr
Okotoks, Alberta T1S 2E1
Canada
(403) 995-0220

Private team pricing and available dates are confirmed by phone. No payment is collected on this static site.

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