Master the most important programming language in Data Science.
Module Objectives:
This module helps you get familiar with programming in Python – the most important language in Data Science. You will understand how computers "think," how to write your first program, and the foundational programming logic to process data efficiently.
What You Will Achieve After This Module:
- Write your first Python program ("Hello World").
- Understand variables, data types, strings, numbers, and boolean.
- Know how to write conditions (if/else), loops (for/while), and functions.
- Master working with lists, dictionaries, and strings – the 3 most used data structures in Data Science.
- Know how to read input, print output, and solve logic problems similar to entry-level interviews.
Career Value:
- A solid Python foundation helps you process data quickly, cleanly, and accurately.
- Logic skills (if, loop, function) help you pass recruitment tests for Data Analyst/Business Analyst/Data Engineer positions.
- A stepping stone to learn Pandas, NumPy, and Machine Learning.
- Become a candidate who "knows programming" – a huge advantage in the job market.
1 — IF STATEMENT
You will learn how to make computers "make decisions":
- Conditions if / elif / else.
- Logical operators AND, OR, NOT.
- Practice exercises like checking odd/even numbers, grading scores, calculating bonuses, checking characters…
- This is the foundation for data classification, validation, and business logic processing.
2 — SEQUENCES
You will learn:
- Create lists, access elements, update values.
- pop(), append(), sorted(), slicing.
- Practice exercises similar to real data processing scenarios: analyze planet positions, swap positions, find late arrivals, calculate sums by position…
- Lists are an important structure when processing raw data before importing into Pandas.
3 — LOOPS
- Iterate through lists, conditional loops, break/continue.
- Exercises from simple to interview-level questions:
- Print patterns, Fibonacci, FizzBuzz
- Move zeros in a list (Google interview question)
- Loop skills help you process large amounts of data element by element.
4 — FUNCTION
- Write functions, parameters, return values.
- Nested functions, default values, local/global variables.
- Exercises: check prime numbers, split strings, calculate lists…
5 — DICTIONARY
The foundation for processing key-value data. You will learn how to:
- Create dictionaries, access values, update and delete keys.
- Analyze data by groups (tally, count, frequency).
- Prepare for Pandas (because Series and DataFrame are both based on dictionaries).
- This is a truly important skill when working with JSON data, APIs, and logs.
6 — STRING MANIPULATION
- Slice strings, replace characters, split words, join strings.
- Clean text – a core skill in NLP & Data Cleaning.
- Mini-exercises like reverse sentences, filter numeric characters, remove nth character…
- Strings are the most common data type in practice (names, emails, text, logs).
7 — REGEX
- Search & extract patterns in text.
- Validate emails, phone numbers, passwords.
- Clean and analyze text data at a more professional level.
- Regex is an extremely powerful "data troubleshooting" skill in Data Analytics.
8 — INTERMEDIATE PYTHON (OPTIONAL)
- List comprehension
- Generator
- Iterator
- Zip, enumerate
- Lambda
- Included as "advanced" content to give you an advantage in data processing and writing clean – fast – efficient code.
EXAM — PYTHON 101
- 10–20 multiple-choice questions on variables, data types, if/else, loops, functions.
- 3–5 coding challenges: logic processing, strings, calculations, lists/dictionaries.
- Understand foundational programming logic clearly.
- Confidently move on to advanced Python & Pandas modules.
- Have sufficient skills to complete your first mini-project on text processing.
So stay motivated, stay curious, and most importantly, keep practicing. The future belongs to those who can harness the power of programming, and with Python, you will be well on your way to becoming a professional data scientist.
Take your time, be patient, and don't hesitate to ask for help when needed.
Welcome to the Python module, and happy learning! 🐍