Python Basics for Data Science

Build a strong Python programming foundation specifically designed for Data Science, Data Analysis, and Machine Learning applications.

Created by

Asogbon Samuel

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English

Last updated

Mon, 06-Apr-2026

Course description

This is the foundational module of the Data Science with Python – Zero to Hero program. Many students struggle in Data Science not because of complex algorithms, but because their Python basics are weak. This module solves that problem by teaching Python programming from absolute zero, but with a strong focus on how Python is actually used in real data science work.You will learn variables, data types, operators, control structures (if-else, loops), functions, list comprehensions, error handling, and file handling. All concepts are taught using practical data-related examples such as working with lists of customer data, analyzing sales numbers, cleaning messy text data, and preparing data for analysis.By the end of this module, you will have the confidence to write clean, efficient Python code and be fully prepared to move into data analysis libraries like NumPy and Pandas in the next module.

What will i learn?

  • Write clean, readable, and well-structured Python code Work confidently with different Python data structures (lists, dictionaries, etc.) Use control flow statements to solve logical problems Create reusable functions and modular code Handle errors gracefully in your programs Read from and write data to files Perform basic operations using NumPy arrays and Pandas Series Think programmatically a crucial skill for any data scientist

Requirements

  • Basic computer literacy (using keyboard, browser, and files)
  • A computer with stable internet connection
  • No prior programming or Python experience required

Frequently asked question

Yes. We start from absolute zero. No previous programming knowledge is needed. Everything is explained step-by-step with simple examples.

This module teaches Python the way data scientists actually use it from day one. All examples and exercises are related to data, analysis, and real-world data problems, so you don’t waste time learning things you won’t use later.

You will install Anaconda (which includes Python, Jupyter Notebook, and essential libraries). We will use Jupyter Notebook for all coding exercises because it is the most popular tool among data scientists.

Yes. By the end of Module 1, you will be comfortable enough with Python to start learning data analysis tools like Pandas and NumPy in Module 2.

Asogbon Samuel

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₦40000

₦45000

Lectures

0

Skill level

Intermediate

Expiry period

3 Months

Certificate

Yes
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