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Python in practice from scratch – programming and automation

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Training process

Training needs analysis

If you have specific requirements regarding the training programme, we will carry out a training needs analysis for you. This will guide us on which aspects of the programme should receive greater emphasis, so that the training programme meets your specific needs.

What will you gain?

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Independent Python setup - You will set up your working environment and run your first scripts with confidence, so after the course you can immediately start building and testing your own solutions on your computer.

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Writing simple programs with ease - You will learn how to use data types, variables and operators to create clear, correct code, helping you avoid common beginner mistakes from the very first lines of a script.

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Automating logic in code - You will master conditionals and loops, so you can turn repetitive tasks, business rules and simple decision paths into Python code instead of doing the same steps manually.

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Working efficiently with data - You will use lists, dictionaries and tuples to organize data, find the elements you need and build simple filtering operations that are useful in everyday office or analytical work.

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Building your own functions - You will write functions with arguments and return values, making your code easier to structure, reuse and expand when you create your own automation scripts for practical tasks.

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Handling text and CSV files - You will learn to read and save TXT and CSV files and perform basic operations in pandas, making it easier for you to process data from reports, exports and simple source files.

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Catching errors more effectively - You will understand how try and except work and how to diagnose common beginner issues, so you can identify the cause of an error faster and fix your program with less frustration.

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Ready for your own mini projects - You will connect all the fundamentals in hands-on practice, so after the training you can build simple programs and automations that support your daily office or analytical tasks.

Training programme

1. Introduction to Python

  • what Python can be used for,
  • installation of the environment (Anaconda / Python + VSCode),
  • first lines of code, running scripts.

2. Data types and variables

  • numbers, text, logical value,
  • rules for naming variables,
  • type conversions.

3. Operators and expressions

  • arithmetic, comparison, logical,
  • order of operations,
  • simple conditions.

4. Conditional instructions

  • if, elif, else,
  • executing code depending on the condition.

5. Loops and iterations

  • for and while,
  • iteration over lists and strings,
  • breaking and skipping (break, continue).

6. Basic data structures

  • lists, dictionaries, tuples,
  • adding, removing, changing elements,
  • searching and filtering data.

7. Functions in Python

  • defining and calling functions,
  • arguments and return values,
  • examples of using functions for automation.

8. Working with files

  • reading and writing text files (.txt, .csv),
  • basics of working with files in pandas,
  • simple operations on data from files.

9. Error handling

  • try / except,
  • the most common beginner mistakes,
  • how to diagnose problems in code.

What are the prerequisites for participating in the training?

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Basic computer skills - You should be comfortable using your operating system, opening programs, saving files and moving through folders so you can work smoothly during the practical exercises.

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Keyboard and file handling - You should be able to type, copy and paste text, and create and open files, because these tasks will be needed when writing, editing and running Python scripts.

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Basic logical thinking - You should understand simple if-then relationships, compare values and perform basic arithmetic so you can follow conditions, expressions and loops more easily.

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Readiness to work with data - You should feel comfortable with simple text and numeric data and with working on files, because during the training you will read, modify and save data in practice.