Who should attend
Aspiring data engineers, ETL testers, analysts and professionals automating data processing tasks.
Prerequisites
Basic computer usage. No prior programming is required for the introductory pathway.
Learning outcomes
- Write readable Python scripts using core language constructs.
- Read, write and transform common data files.
- Work with APIs and relational databases.
- Clean, validate and transform datasets using Python libraries.
- Build reusable scripts with logging, configuration and exception handling.
- Create a small repeatable data ingestion/transformation workflow.
Detailed curriculum
8 modules01Python setup and programming foundations
- Installing Python, virtual environments and IDE setup
- Variables, data types, operators and type conversion
- Input/output, conditions and loops
- Functions, parameters, return values and scope
- Readable code, naming, comments and basic debugging
02Core data structures and programming
- Strings and string methods
- Lists, tuples, sets and dictionaries
- Comprehensions and nested structures
- Iteration, enumerate, zip and sorting
- Modules, packages and importing
03Files, formats and exception handling
- File paths and context managers
- Reading/writing text and CSV files
- JSON parsing and serialization
- Working with Excel files where included in the selected toolset
- Exceptions, validation and safe file handling
04Functions, OOP and reusable code
- Function design and reusable utilities
- Classes, objects, methods and constructors
- Encapsulation and inheritance fundamentals
- Dataclasses and type hints overview
- Unit-testing small functions and code organisation
05Data manipulation with libraries
- NumPy arrays and vectorised operations overview
- Pandas Series and DataFrames
- Reading CSV, Excel, JSON and database extracts
- Filtering, sorting, grouping, merging and reshaping
- Missing values, duplicates, type conversion and date handling
06APIs and database connectivity
- HTTP basics and calling REST APIs with requests
- Query parameters, headers, pagination and authentication concepts
- Parsing JSON responses and handling API errors
- Connecting to a relational database using a suitable driver/SQLAlchemy
- Parameterized SQL and safe database operations
07Data pipeline engineering practices
- Extract-transform-load script structure
- Configuration files and environment variables
- Logging, retries, checkpoints and idempotency
- Data validation and reconciliation checks
- Scheduling concepts and command-line execution
08Project, testing and deployment basics
- Writing unit tests with pytest or unittest
- Debugging and profiling basics
- Git fundamentals and requirements management
- Packaging dependencies and running scripts in a clean environment
- Documenting and demonstrating a mini data pipeline
How you will practise
Learn through instructor-led sessions using realistic, live applications. Then apply each concept through guided assignments on a separate hands-on practice application, with feedback to help you build practical skills and confidence.
Practical exercises and labs
- Clean and standardise a messy CSV dataset with Pandas.
- Call a paginated API and store selected fields in a database.
- Build duplicate, null and range validation checks.
- Create a reusable ETL script with logs and exception handling.
Capstone project
Create a Python pipeline that extracts data from CSV/API sources, cleans and validates it with Pandas, loads a relational target, logs each run and supports safe re-execution.
Tools and technologies
Python 3, VS Code/Jupyter, pip/venv, Pandas, requests, SQLAlchemy or a selected database driver, pytest and Git.
Assessment approach
- Module-wise knowledge checks or short practical tasks.
- Hands-on exercise review using an agreed checklist or rubric.
- Final project demonstration and explanation of design decisions, test evidence or outputs, as applicable.
- Completion criteria, attendance requirements and any certificate conditions must be separately approved and published by TrainingRite.
Schedule and fees
Upcoming batch schedules are shared by our TrainingRite team. Please submit an enquiry and our team will contact you by email or phone with the latest schedule. TrainingRite does not publish course fees or discounts on the website. Our counselling team will share the applicable course fee and other details with you by email or phone after you submit an enquiry.
Frequently asked questions
Who should join this course?
Aspiring data engineers, ETL testers, analysts and professionals automating data processing tasks.
Do I need prior experience?
Basic computer usage. No prior programming is required for the introductory pathway.
Is the training online?
TrainingRite programmes are delivered online.
Will I get hands-on practice?
Sessions are instructor-led and use realistic applications. You then apply each concept through guided assignments on a separate practice application.
How can I enquire about fees and the next batch?
Fees and batch schedules are not published on the website. Submit the enquiry form on this page and our counselling team will share them with you by email or phone.