Introduction to Data Science and Programming (Python)

Who is it for?

• University students who are just starting to program (for example in business, economics or social-science programmes).
• Career changers and professionals who work with data and want to start with the basics of Python.
• Anyone who wants a structured, hands-on introduction at their own pace.

Prerequisites

None. You need a web browser and basic English reading skills (the materials are in English; the videos have English and Hungarian captions).

Modules and learning outcomes

1. Session 1 — Python, Google Colab and Your First Program (125 min)

   Understand what makes Python a high-level, interpreted, general-purpose language, know the tools a program needs (editor, interpreter, linker, loader, IDE), and write, run and debug your first programs in Google Colab with print(), strings, numbers, separators and escape characters.

   By the end you will be able to:

   • Explain why Python is called a high-level, general-purpose, interpreted and dynamically typed language.
   • Describe the role of the editor, the compiler/interpreter, the linker, the loader and an IDE, and why we use Google Colab.
   • Write and run a print() statement in a Colab code cell and read its output.
   • Predict the difference between "5" + "6" and 5 + 6, and print several values with commas, sep and end.
   • Use the escape characters \n and \t to control line breaks and columns.
   • Read a TypeError message, classify an error as syntax, semantic or runtime, and fix it — including restarting the session when an earlier mistake is still in memory.

2. Session 2 — Variables, Simple Data Types, Type Conversion and Operators (140 min)

   Create and name variables, work with int, float, bool and str values, print and format them, convert between types explicitly and implicitly, understand why input() always returns a string, and write small calculation programs with Python's arithmetic operators.

   By the end you will be able to:

   • Explain a variable as a named box in memory and follow Python's naming rules.
   • Create int, float, bool and str variables, check their type with type() and print their values.
   • Combine booleans with the logical operators and / or.
   • Use the constant naming convention and explain why Python has no true constants.
   • Distinguish explicit type conversion (int(), float(), str()) from implicit conversion done by the interpreter.
   • Explain why input() returns a string and convert user input before calculating with it.
   • Use + − * / // % ** and operator precedence to write small calculation programs.

3. Session 3 — Decisions in Python: Logical Operators and if / elif / else (127 min)

   Use truth tables, comparison, logical and assignment operators to write the true-or-false questions programs ask, then branch with if, if–else and elif. The examples are an age check, a login check and a camera-budget program. Test every branch.

   By the end you will be able to:

   • Read and apply the truth tables of and, or and not.
   • Use the comparison operators <, >, <=, >=, == and !=, and tell == (a question) apart from = (an assignment).
   • Evaluate expressions with brackets, arithmetic, comparison and logical operators using the precedence table.
   • Use the assignment operators +=, -=, *=, /=, %= and //= and predict the new value.
   • Write unary (if) and binary (if–else) selections, and give the user feedback in the else branch.
   • Write chained conditionals with elif, and recognise nested conditionals, match-case and the ternary operator.
   • Test every branch of a program, including boundary values.

4. Session 4 — Loops: for, range() and while (125 min)

   Automate repetition in Python: loop over a range with for, control start, stop and step, combine a loop with an if statement, write while loops with a working stop condition, recognise infinite loops and loops that never start, and control loops with break, continue and pass.

   By the end you will be able to:

   • Explain why loops are the first tool for automating repeated work.
   • Write a for loop over range(n) and over range(start, end, step), and predict exactly which numbers it produces.
   • Combine a for loop with an if statement, for example to print only the numbers divisible by 10.
   • Write a while loop whose condition eventually becomes False, and recognise an infinite loop.
   • Diagnose a while loop that never runs because its condition is False at the start.
   • Use break, continue and pass, and emulate a post-test loop.
   • Turn a structogram (prime check, cash denominations) into a working Python loop.

5. Session 6 — Basic Algorithms I: Decision, Summation, Counting, Search and Maximum (128 min)

   Six basic algorithms that answer the most common questions about a list — is there such an element, what is the sum or average, how many are there, which one is first, where is it, and which is the largest — first as pseudocode, then in Python with while and for loops.

   By the end you will be able to:

   • Read the pseudocode of a basic algorithm and translate it to Python, moving from 1-based positions to 0-based indexes.
   • Use the decision algorithm (a while loop with two conditions) to tell whether an element with property P exists.
   • Compute a sum with a running total and turn it into an average.
   • Count the elements with a property, and use N − count for the complement.
   • Find the first matching element with selection or linear search, and know when each is safe.
   • Find the largest element with maximum selection, and trace the algorithm step by step.

The Teringette learning framework

Every Teringette course follows the same proven arc, so you always know where you are and every step prepares you for the next:

1. Understand: Short video clips and concise concept explanations — only what you really need.
2. Step by step: Worked demonstrations that show how a professional solves a task.
3. Real decisions: Decision scenarios from real situations: what would you do, and what follows?
4. Practise: Code examples and practice tasks, with Python running right in your browser, nothing to install.
5. Check: Quizzes and automatically checked tasks with instant, explanatory feedback.
6. Consolidate: A checklist and a final assessment at the end of every module, with progress you can track.

About the author

Ádám Uzonyi — Programmer, educator, founder of Teringette

Ádám Uzonyi is a programmer and educator and the founder of Teringette. He teaches Python, Java and C++, runs AI training and builds custom AI-based software. He builds the Teringette Academy courses on his own Teringette learning framework, so that learning turns into real, usable skills rather than memorisation: from the concepts through step-by-step demonstrations and real decision situations to independent practice with instant feedback.

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Frequently asked questions

How much does the course cost and how long can I use it?

The course costs 19 900 Ft (Hungarian forints) as a one-off payment; the seller is VAT-exempt, so this is the total. Access lasts 12 months from payment, with no subscription and no automatic renewal.

How can I pay?

By card, Apple Pay or Google Pay on Stripe’s secure payment page, or by bank transfer. Buyers abroad can pay in their own currency. The invoice is sent by e-mail.

What language is the course in?

The texts and exercises are in English. The videos have English and Hungarian captions, and the interface is available in English and Hungarian.

Do I need to install anything?

No. The Python exercises run directly in your browser, tasks are checked instantly and your progress is saved. An up-to-date Chrome, Edge, Firefox or Safari is enough.

How long does it take?

The course has 5 modules, about 11 hours of study in total. You learn at your own pace and can continue where you left off.

Can I withdraw within 14 days?

This is digital content: when ordering you expressly ask for access to open immediately after payment and acknowledge that you thereby lose the 14-day right of withdrawal. If the material is faulty or does not work, your rights under the Terms remain.

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