Data Science with Python

Description

Python is the working language of this course, and the aim is to analyse real data. Fourteen PDF lessons start with setting up Python and using Pandas and NumPy, then cover visualisation with Matplotlib and Seaborn and the core ideas of machine learning.

Later lessons build first predictive models, clean and prepare real-world datasets and evaluate model performance. Further topics include business applications, data-driven reports, more advanced algorithms, natural language processing basics and recommendation systems. A final project ties the steps into one workflow. Exercises appear in ten lessons. After reading, you should be able to follow a data analysis from raw file to written report.

Who it is for: beginners with some comfort in basic programming who want to analyse data with Python.

What’s included
14 PDF lessons · 134 pages · about 28,500 words
One ZIP download that is yours to keep — read on any device, no subscription or app needed.

Course programme

1. Getting Started with Python for Data Science
2. Data Analysis with Pandas and NumPy
3. Data Visualization with Matplotlib and Seaborn
4. Introduction to Machine Learning Concepts
5. Building Your First Predictive Models
6. Working with Real-World Datasets
7. Data Cleaning and Preprocessing Techniques
8. Model Evaluation and Performance Metrics
9. Business Applications of Data Science
10. Creating Data-Driven Business Reports
11. Advanced Machine Learning Algorithms
12. Natural Language Processing Basics
13. Building Recommendation Systems
14. Final Project: Complete Data Analysis Workflow