{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Getting started on Using Jupyter Notebooks and Python\n", "\n", "## Learning Objectives\n", "The goal of this notebook is to learn how to use Python for solving chemical engineering problems. We assume that you are familiar with content from APSC 160 (or any other introductory programming courses if you are a transfer student), but have no prior experience with Python.\n", "\n", "By the end of this section, you should be able to:\n", "\n", "1. Understand how to use Jupyter notebooks\n", "2. Write simple Markdown and Python code\n", "\n", "## Introduction and Motivation\n", "\n", "Welcome to **CHBE 241: Material and Energy Balances**!\n", "\n", "In this course, we will use Jupyter notebooks to illustrate how to apply modern, open-source software tools for chemical engineering applications. We will be using Python, a free, open-source and powerful computing environment. It is one of the most popular languages in the data science community alongside R, which you will learn in STAT 241.\n", "\n", "Coding is one of the most useful, transfereable skills that you can learn in the 21st century. According to the [U.S. Department of Labor](https://www.bls.gov/ooh/architecture-and-engineering/chemical-engineers.htm), the chemical engineering industry is projected to grow 2% between 2014-2024. Over the same period, the software industry is projected to grow by a staggering 17%. Software, automation and data science will serve an increasingly important role in the field of chemical engineering. For example, researchers in the [DAIS Lab](http://dais.chbe.ubc.ca/) here in CHBE are investigating applications of machine learning techniques to design better controllers for industrial processes.\n", "\n", "The goal of using Python in this course is to provide you with a gentle introduction to the language of modern software development and equip you with the necessary foundations to pursue further explore this area if you are interested in learning more.\n", "