Introduction

Introduction#

These lecture notes are prepared for IST-3420, Introduction to Data Science and Management at Missouri University of Science and Technology (MS&T). The course aims to provide you with a solid foundation in data science concepts and practices, supporting both your future studies and career development.

Major curriculum modules included in this course are:

  • Foundation Building: Establishes solid Python/Jupyter programming skills essential for data science work.

  • Data Manipulation Core: Covers NumPy and Pandas extensively, as these are the backbone tools for data scientists.

  • Visualization Skills: Develops both basic and advanced visualization capabilities for effective data communication.

  • Analysis Techniques: Introduces statistical thinking and hypothesis testing crucial for data-driven insights.

  • Machine Learning: Covers both supervised and unsupervised learning with practical implementations.

Some of the Python parts of these notes are based on Allen Downey’s book Thank Python , which is a great textbook for Python. For materials from other resources, the links are provided and/or proper citations referenced.

Code license: MIT License Text license: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International