Concepts of Physics is an adaptation based on modules from OpenStax College's textbook College Physics.

This text is intended for use in a one-semester physical science course that requires algebra but no trigonometry.

Not all physics topics are covered in this work. Of the nearly 300 original College Physics modules, only 100 were retained. For these selected modules, content was modified (as needed) to remove/replace any trigonometry-related topics, examples, homework, or figures. Occasionally, original content was edited (or replaced) to reflect the level, and coverage, of the course. Notation was modified in a few cases for consistency between modules. Explicit links between modules (and discussions related to non-retained modules) were removed. Finally, all direct links to PHeT plugin-based (Java or Flash) physics simulations were removed.

This second edition of Database Design book covers the concepts used in database systems and the database design process.

This book contains self-paced learning modules that were written as a tool to guide and teach you to master Inventor. No two students learn at the same pace, therefore, the modules were written as competency-based bite-size pieces to allow you to work at your own pace. They can be used in correspondence courses, online courses, instructor-lead classes or by individuals teaching themselves to use Inventor in their own home or office.

Introduction to Ecology is an open course remix of the OpenStax Biology open textbook. The remix includes a modular revision of parts of the text with supplemental questions added.

This course uses the basic principles of biology and earth science as a context for understanding environmental policies and resource management practices. Our planet is facing unprecedented environmental challenges, from oil spills to global climate change. In ENSC 1000, you will learn about the science behind these problems; preparing you to make an informed, invaluable contribution to Earth’s future. I hope that each of you is engaged by the material presented and participates fully in the search for, acquisition of, and sharing of information within our class.

This textbook, or really a “coursebook” for a college freshman-level class, has been updated for Spring 2014 and provides an introduction to programming and problem solving using both Matlab and Mathcad. We provide a balanced selection of introductory exercises and real-world problems (i.e. no “contrived” problems). We include many examples and screenshots to guide the reader. We assume no prior knowledge of Matlab or Mathcad.

"In this text, we will explore the fundamental physical, chemical, geological, and biological features and processes of the
oceans and review how humans have studied the oceans. We will discuss the range of resources that the oceans provide for us, and the pollution and other impacts that result from human use of the oceans and exploitation of their resources. We will also examine the direct and indirect effects of climate change, not just on human civilization and natural ecosystems but also on the fundamental chemistry of the global ocean that pose a long-term threat
of the extinction of many ocean species"--Introduction.

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.

Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.

With this handbook, you’ll learn how to use:

IPython and Jupyter: provide computational environments for data scientists using Python
NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python
Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python
Matplotlib: includes capabilities for a flexible range of data visualizations in Python
Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

New Edition! The goal of this book is to provide an Informatics-oriented introduction to programming. The primary difference between a computer science approach and the Informatics approach taken in this book is a greater focus on using Python to solve data analysis problems common in the world of Informatics.

In this online intro to design you’ll get exposed to a medley of design abilities, methods, and mindsets. You’ll watch videos and learn what design looks like in the real world, as well as discover ‘what design is’ by doing partner activities and discussions. In three hours you’ll learn over 20 concepts and tools that will help you apply human-centered design to your own work.