#### Python: Real-World Data Science

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#### Python: Real-World Data Science

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#### Overview of this book

The Python: Real-World Data Science course will take you on a journey to become an efficient data science practitioner by thoroughly understanding the key concepts of Python. This learning path is divided into four modules and each module are a mini course in their own right, and as you complete each one, you’ll have gained key skills and be ready for the material in the next module.
The course begins with getting your Python fundamentals nailed down. After getting familiar with Python core concepts, it’s time that you dive into the field of data science. In the second module, you'll learn how to perform data analysis using Python in a practical and example-driven way. The third module will teach you how to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis to more complex data types including text, images, and graphs. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. In the final module, we'll discuss the necessary details regarding machine learning concepts, offering intuitive yet informative explanations on how machine learning algorithms work, how to use them, and most importantly, how to avoid the common pitfalls.

Table of Contents (12 chapters)

Python: Real-World Data Science

Meet Your Course Guide

What's so cool about Data Science?

Course Structure

Course Journey

The Course Roadmap and Timeline

1. Course Module 1: Python Fundamentals

2. Course Module 2: Data Analysis

3. Course Module 3: Data Mining

4. Course Module 4: Machine Learning

Index

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