About This Course
In today's data-driven economy, the ability to query, manipulate, and analyse structured data is among the most sought-after technical competencies in both the private and public sectors. Transact-SQL — Microsoft's proprietary extension of SQL used with SQL Server and Azure SQL Database — remains the backbone of enterprise data management across industries ranging from finance and healthcare to logistics and government. At the same time, Python has emerged as the world's most widely used programming language for data engineering, automation, and analytics, with a rich ecosystem of libraries that complement and extend traditional database work.
This 10-day Transact-SQL and Python Programming Training course, delivered by TrainingComplex, is designed to give participants a rigorous, practical grounding in both technologies. Rather than treating them in isolation, the programme builds an integrated skill set: participants learn to write sophisticated T-SQL queries against real relational databases, and then leverage Python to connect to those databases, automate repetitive data tasks, clean and transform datasets, and produce analytical outputs — all within a coherent, professional workflow.
The course is structured to be progressive. The first half establishes a strong foundation in T-SQL — from basic SELECT statements and filtering through joins, subqueries, stored procedures, and performance optimisation. The second half introduces Python fundamentals and then rapidly advances to pandas-based data manipulation, database connectivity using libraries such as pyodbc and SQLAlchemy, and practical scripting for business use cases. Capstone exercises in the final days bring both skill sets together in integrated projects that mirror real-world scenarios.
Whether you are a database administrator looking to expand into scripting, an analyst seeking to automate reporting, or a developer aiming to deepen your data querying expertise, this course provides the technical depth and hands-on practice needed to operate confidently at the intersection of SQL and Python in a professional environment.
Who Should Attend
- Database administrators and SQL developers seeking to add Python scripting capabilities
- Data analysts and business intelligence professionals who want to automate workflows and deepen query skills
- Software developers transitioning into data engineering or back-end data roles
- IT professionals responsible for reporting, ETL processes, or data pipeline maintenance
- Financial and operations analysts working with large structured datasets in SQL Server environments
- Monitoring and evaluation officers who manage relational databases and require scripted data extraction
- Recent graduates in computer science, information systems, or related disciplines entering data-focused roles
Learning Objectives
- Write complex Transact-SQL queries including multi-table joins, subqueries, CTEs, and window functions
- Create and manage SQL Server objects including tables, views, stored procedures, and triggers
- Apply T-SQL performance tuning techniques including indexing strategies and query execution plan analysis
- Demonstrate proficiency in core Python syntax, control flow, functions, and object-oriented programming fundamentals
- Use Python's pandas and NumPy libraries to ingest, clean, transform, and aggregate structured datasets
- Connect Python to SQL Server databases using pyodbc and SQLAlchemy to execute queries and load results programmatically
- Automate repetitive data extraction, transformation, and reporting tasks using Python scripts
- Build reusable, modular Python scripts following professional coding standards and documentation practices
- Handle errors, exceptions, and data quality issues in both T-SQL and Python environments
- Integrate T-SQL and Python in end-to-end data workflows that reflect realistic enterprise use cases
Course Modules
Module 1: Foundations of Relational Databases and the SQL Server Environment
- Relational database concepts: tables, keys, relationships, and normalisation
- Overview of Microsoft SQL Server architecture and key components
- Installing and navigating SQL Server Management Studio (SSMS)
- Understanding databases, schemas, and object naming conventions
- Connecting to a SQL Server instance and exploring sample databases
- Introduction to the T-SQL language and its role within SQL Server
Module 2: Core Transact-SQL Querying
- Writing SELECT statements: columns, aliases, and expressions
- Filtering data with WHERE clauses and logical operators
- Sorting results with ORDER BY and limiting output with TOP
- Working with NULL values and IS NULL conditions
- Using built-in scalar functions: string, numeric, and date functions
- Grouping and aggregating data with GROUP BY and HAVING
Module 3: Joins, Set Operations, and Multi-Table Queries
- Understanding INNER JOIN and retrieving matched rows across tables
- LEFT, RIGHT, and FULL OUTER JOINs and when to use each
- Self-joins for hierarchical and comparative queries
- CROSS JOINs and their appropriate use cases
- Combining result sets with UNION, INTERSECT, and EXCEPT
- Building and reading entity-relationship diagrams to plan multi-table queries
Module 4: Subqueries, CTEs, and Advanced Query Structures
- Writing correlated and non-correlated subqueries
- Using subqueries in SELECT, FROM, and WHERE clauses
- Introduction to Common Table Expressions (CTEs) and their syntax
- Recursive CTEs for hierarchical data traversal
- Derived tables vs CTEs: readability and performance considerations
- Practical exercises: solving multi-step business questions using CTEs
Module 5: Window Functions, Pivoting, and Analytical Queries
- Understanding the OVER clause and partitioning concepts
- Ranking functions: ROW_NUMBER, RANK, DENSE_RANK, and NTILE
- Aggregate window functions: running totals, moving averages
- LAG and LEAD functions for period-over-period comparisons
- Pivoting data with PIVOT and UNPIVOT operators
- Building analytical query solutions for sales, finance, and operational reporting
Module 6: T-SQL Data Manipulation, Objects, and Stored Procedures
- INSERT, UPDATE, DELETE, and MERGE statements for data modification
- Creating and altering tables, views, and indexes
- Designing and executing stored procedures with input and output parameters
- Using user-defined functions (scalar and table-valued)
- Introduction to triggers: AFTER and INSTEAD OF trigger types
- Transaction management with BEGIN, COMMIT, ROLLBACK, and savepoints
Module 7: T-SQL Performance Tuning and Query Optimisation
- Reading and interpreting execution plans in SSMS
- Understanding clustered and non-clustered indexes and their impact
- Identifying and resolving common performance bottlenecks
- Using database statistics and the Query Store
- Temporal tables and strategies for managing large datasets efficiently
- Best practices for writing efficient, scalable T-SQL code
Module 8: Python Programming Fundamentals
- Setting up the Python environment: installing Python and VS Code with extensions
- Core syntax: variables, data types, operators, and expressions
- Control flow: if/elif/else conditions and loop structures (for, while)
- Defining and calling functions with parameters and return values
- Working with lists, tuples, dictionaries, and sets
- Handling errors and exceptions with try/except blocks
Module 9: Data Manipulation with pandas and NumPy
- Introduction to NumPy arrays and vectorised operations
- Creating and exploring pandas DataFrames and Series
- Loading data from CSV, Excel, and JSON files into DataFrames
- Filtering, selecting, and transforming data using pandas methods
- Grouping, aggregating, and pivoting data with groupby and pivot_table
- Handling missing data, duplicates, and data type conversions
Module 10: Connecting Python to SQL Server Databases
- Overview of Python database connectivity libraries: pyodbc and SQLAlchemy
- Establishing connections to SQL Server from Python scripts
- Executing T-SQL SELECT queries from Python and reading results into DataFrames
- Running INSERT, UPDATE, and DELETE statements from Python
- Using parameterised queries to prevent SQL injection
- Managing transactions and connection pooling in Python database workflows
Module 11: Python Scripting for Automation and Reporting
- Designing modular, reusable Python scripts following PEP 8 standards
- Automating data extraction schedules using the schedule library
- Generating formatted Excel reports from database query results using openpyxl
- Sending automated email notifications with query summaries via smtplib
- Logging script activity and errors to files for auditability
- Version control basics: managing Python scripts with Git
Module 12: Integrating T-SQL and Python in End-to-End Data Workflows
- Architecting a complete extract-transform-load (ETL) pipeline using T-SQL and Python
- Using Python to call stored procedures and handle output parameters
- Orchestrating multi-step data workflows: sequencing SQL and Python tasks
- Data validation patterns: cross-checking SQL outputs with Python assertions
- Error handling strategies across the full pipeline stack
- Documenting and handing over integrated data solutions within a team
Module 13: Capstone Project: Designing and Delivering an Integrated Data Solution
- Capstone briefing: reviewing a realistic business data challenge and requirements
- Participants design their database schema and T-SQL query architecture
- Building the Python scripting layer to automate extraction and transformation
- Data quality checks, exception handling, and output generation
- Project presentations: each participant or pair demonstrates their solution
- Peer and instructor feedback, course review, and professional development planning
Requirements & Prerequisites
Participants should have a working familiarity with computers and basic spreadsheet tools such as Microsoft Excel. Some prior exposure to any programming or scripting language, or to database concepts such as tables and records, is helpful but not strictly required, as the course begins with foundational material. A willingness to engage with technical content and complete hands-on lab exercises daily is essential for full benefit.
Training Methodology
- Instructor-led live coding demonstrations using SQL Server Management Studio (SSMS) and Visual Studio Code, allowing participants to follow along in real time
- Guided lab sessions after each module where participants write and execute T-SQL and Python code against pre-loaded sample databases
- Case study walkthroughs based on realistic business scenarios drawn from finance, logistics, and public sector data environments
- Pair programming exercises that encourage peer learning and collaborative problem-solving on multi-step scripting challenges
- Query debugging workshops where participants diagnose and fix intentionally broken SQL and Python code to build troubleshooting skills
- Execution plan analysis exercises using SSMS tools to help participants understand and improve query performance
- Python scripting assignments that connect to SQL Server and produce formatted reports, building end-to-end workflow competency
- Daily review quizzes and discussion sessions to consolidate learning and address common misconceptions before advancing
- A structured capstone project in the final two days requiring participants to design, build, and present an integrated T-SQL and Python data solution
- Take-home reference cheat sheets and reusable script templates that participants can apply directly in their workplaces
Organisational Benefits
- Reduced dependency on manual data extraction and reporting through scripted automation
- Faster turnaround on data requests as staff can write and optimise their own queries
- Improved data quality through structured validation and transformation pipelines
- Stronger in-house capacity to maintain and extend SQL Server databases and reporting infrastructure
- Cost savings from replacing repetitive analyst tasks with reusable Python scripts
- Better integration between database systems and analytical tools used by the organisation
- Enhanced team credibility and technical capability when engaging with ICT, data engineering, and vendor teams
- A more agile data function capable of responding to evolving organisational information needs
Where Is Transact-SQL and Python Programming Training Offered?
This course runs in-person across: Nairobi, Johannesburg, Kigali, Addis Ababa, Abuja, Cape Town, Naivasha, Mombasa, Riyadh, Dubai, Nakuru, Lagos, Accra, Arusha, Pretoria, Dar es Salaam, Kisumu, Kampala, Zanzibar, plus Live Virtual (online) cohorts. Browse live dates for your city below.
Upcoming Schedules
| Location | Format | Dates | Price |
|---|
| Live Virtual |
Online |
28 Sept 2026 – 9 Oct 2026 |
KES 160,000 |
| Nairobi, Kenya |
In-Person |
5 Oct 2026 – 16 Oct 2026 |
KES 230,000 |
| Johannesburg, South Africa |
In-Person |
5 Oct 2026 – 16 Oct 2026 |
USD 7,000 |
| Kigali, Rwanda |
In-Person |
12 Oct 2026 – 23 Oct 2026 |
USD 3,800 |
| Addis Ababa, Ethiopia |
In-Person |
12 Oct 2026 – 23 Oct 2026 |
USD 4,800 |
| Live Virtual |
Online |
17 Oct 2026 – 6 Dec 2026 |
KES 160,000 |
| Abuja, Nigeria |
In-Person |
19 Oct 2026 – 30 Oct 2026 |
USD 5,600 |
| Cape Town, South Africa |
In-Person |
19 Oct 2026 – 28 Oct 2026 |
USD 7,600 |
| Naivasha, Kenya |
In-Person |
19 Oct 2026 – 30 Oct 2026 |
KES 230,000 |
| Mombasa, Kenya |
In-Person |
19 Oct 2026 – 28 Oct 2026 |
KES 240,000 |
| Riyadh, Saudi Arabia |
In-Person |
19 Oct 2026 – 28 Oct 2026 |
USD 9,000 |
| Dubai, United Arab Emirates |
In-Person |
19 Oct 2026 – 28 Oct 2026 |
USD 8,200 |
| Nakuru, Kenya |
In-Person |
19 Oct 2026 – 28 Oct 2026 |
KES 240,000 |
| Lagos, Nigeria |
In-Person |
19 Oct 2026 – 28 Oct 2026 |
USD 5,000 |
| Accra, Ghana |
In-Person |
26 Oct 2026 – 4 Nov 2026 |
USD 7,600 |
+238 more dates — view live schedule →
Frequently Asked Questions
Do I need prior SQL or programming experience to attend?
Some familiarity with computers and basic data concepts is helpful, but the course starts from foundational principles in both T-SQL and Python. Participants with no prior SQL or programming experience can follow along, though those with some background will progress more quickly through the early modules.
What software will participants need, and will it be provided?
Participants will use SQL Server Management Studio (SSMS), Visual Studio Code, Python, and related libraries. TrainingComplex provides pre-configured lab environments for in-person sessions, so delegates do not need to install anything in advance — though guidance for personal machine setup is shared before the course begins.
Will participants receive a certificate upon completion?
Yes, all participants who attend and complete the full 10-day programme receive a TrainingComplex Certificate of Completion in Transact-SQL and Python Programming, which can be shared on professional profiles and CVs.
Is this course aligned with any industry certification exams?
While this course is not a direct exam-prep programme, the T-SQL content covers material relevant to the Microsoft DP-900 and DP-300 certification paths, and the Python content builds skills applicable to data engineering and analytics certifications. Delegates seeking specific certifications are encouraged to discuss this with the trainer.
Can organisations send multiple staff members and receive group pricing?
Yes, TrainingComplex offers group enrolment discounts for organisations sending three or more participants to the same cohort. Please contact our training coordination team directly to discuss institutional invoicing and tailored in-house delivery options.
