Introduction to Data Science

Description

Data science combines programming, statistics, and clear communication, and these PDF lessons introduce each part. The first lesson explains the basics, and the second covers Python fundamentals for data analysis.

Next come collecting and cleaning data, exploratory analysis to find patterns, visualization techniques, and an introduction to statistics. A later lesson builds a first machine learning model, and the last one shows how to assemble your work into a portfolio. Exercises and tables are included, and you would run any code on your own computer using Python. By the end, you should understand the main steps of a small data project and have ideas for portfolio pieces of your own.

Who it is for: beginners curious about data work who are willing to learn some Python.

What’s included
8 PDF lessons · 64 pages · about 16,000 words
One ZIP download that is yours to keep — read on any device, no subscription or app needed.

Course programme

1. Getting Started with Data Science: Understanding the Basics
2. Python Fundamentals for Data Analysis: Your First Steps
3. Data Collection and Cleaning: Working with Real Datasets
4. Exploratory Data Analysis: Finding Patterns and Insights
5. Data Visualization Techniques: Creating Clear and Compelling Charts
6. Introduction to Statistics for Data Science
7. Your First Machine Learning Model: Practical Application
8. Building Your Data Science Portfolio: Real Projects