Overview

This course is the seventh course in the Google Data Analytics Certificate. The Python programming language is a powerful tool for data analysis. In this course, you’ll learn the basic concepts of Python programming and how data professionals use Python on the job. You'll explore concepts such as object-oriented programming, variables, data types, functions, conditional statements, loops, and data structures. Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you enhance your data analytics skills to prepare for your career. Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary. By the end of this course, you will: -Define what a programming language is and why Python is used by data scientists -Create Python scripts to display data and perform operations -Control the flow of programs using conditions and functions -Utilize different types of loops when performing repeated operations -Identify data types such as integers, floats, strings, and booleans -Manipulate data structures such as , lists, tuples, dictionaries, and sets -Import and use Python libraries such as NumPy and pandas

Syllabus

Hello, Python!

You’ll discover the main features and benefits of the Python programming language, and how Python can help power your data analysis. Python is an object-oriented programming language based on objects that contain data and useful code. You’ll become familiar with the core concepts of object-oriented programming: object, class, method, and attribute. You’ll learn about Jupyter Notebooks, an interactive environment for coding and data work. You’ll investigate how to use variables and data types to store and organize your data; and, you'll begin practicing important coding skills.

Functions and conditional statements

Next, you’ll discover how to call functions to perform useful actions on your data. You’ll also learn how to write conditional statements to tell the computer how to make decisions based on your instructions. And you’ll practice writing clean code that can be easily understood and reused by other data professionals.

Loops and strings

You’ll start off by exploring loops, which repeat a portion of code until a process is complete. You’ll learn how to work with different kinds of iterative or repeating code, such as for loops and while loops. Then, you'll explore strings, which are sequences of characters like letters or punctuation marks. You’ll learn how to manipulate strings by indexing, slicing, and formatting them.

Data structures in Python

Now, you’ll explore data structures in Python, which are methods of storing and organizing data in a computer. You’ll focus on data structures that are among the most useful for data professionals: lists, tuples, dictionaries, sets, and arrays. You’ll also discover how to categorize data using data loading, cleaning, and binning. Lastly, you’ll learn about two of the most widely used and important Python tools for advanced data analysis: NumPy and pandas.