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Every programmer needs to know Python, including those looking to work in rapidly-growing fields such as machine learning and A.I. During this course, you’ll learn the fundamentals you need to take the next step in your career.
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In this course, you’ll learn to represent and store data using Python data types and variables, and use conditionals and loops to control the flow of your programs. You’ll harness the power of complex data structures like lists, sets, dictionaries and tuples to store collections of related data. You’ll define and document your own custom functions, write scripts and handle errors. You will also learn to use two powerful Python libraries — Numpy, a scientific computing package, and Pandas, a data manipulation package.
No Experience Required.
Gain an overview of what you’ll be learning and doing in the course and understand why you should learn programming with Python.
Learn to represent data using Python’s data types: integers, floats, booleans, strings, lists, tuples, sets, dictionaries, compound data structure. Perform computations and create logical statements using Python’s operators: Arithmetic, Assignment, Comparison, Logical, Membership, Identity. You'll also declare, assign, and reassign values using Python variables, modify values using built-in functions and methods, and practice whitespace and style guidelines.
Write conditional expressions using if statements and boolean expressions to add decision making to your Python programs, and learn how to use for and while loops along with useful built-in functions to iterate over and manipulate lists, sets and dictionaries. Condense for loops to create lists efficiently with list comprehensions, and use skip iterations in loops using break and continue.
Learn to define your own custom functions, create and reference variables using the appropriate scope, and add documentation to functions using docstrings. You'll also define lambda expressions to quickly create anonymous functions and use iterators and generators to create streams of data.
Learn to install Python 3 and set up your programming environment, and begin running and editing python scripts. You'll also identify and handle errors and exceptions in your code, open, read and write to files, and find and use modules in Python Standard Library and third-party libraries.
Create, access, modify, and sort multidimensional NumPy arrays (ndarrays), and use slicing, boolean indexing, and set operations to select or change subsets of an ndarray. Understand the difference between a view and a copy of ndarray, perform element-wise operations on ndarrays, and use broadcasting to perform operations on ndarrays of different sizes.
Learn to create, access and modify the main objects in Pandas, Series and DataFrames, perform arithmetic operations on Series and DataFrames, load data into a DataFrame, and deal with Not a Number (NaN) values.
You will use Python to answer interesting questions about bikeshare trip data collected from three US cities. You will write code to collect the data, compute descriptive statistics and create an interactive experience in the terminal that presents the answers to your questions.
With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.
On demand help. Receive instant help with your learning directly in the classroom. Stay on track and get unstuck.
Validate your understanding of concepts learned by checking the output and quality of your code in real-time.
Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.
We provide services customized for your needs at every step of your learning journey to ensure your success.
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Josh has been sharing his passion for data for nearly a decade at all levels of university, and as Lead Data Science Instructor at Galvanize. He's used data science for work ranging from cancer research to process automation.
Derek is the CEO of Mode Analytics. He developed an analytical foundation at Facebook and Yammer and is passionate about sharing it with future analysts. He authored SQL School and is a mentor at Insight Data Science.
Juno is the curriculum lead for the School of Data Science. She has been sharing her passion for data and teaching, building several courses at Udacity. As a data scientist, she built recommendation engines, computer vision and NLP models, and tools to analyze user behavior.
Richard is a Course Developer with a passion for teaching. He has a degree in computer science, and first worked for a nonprofit doing everything from front end web development, to backend programming, to database and server management.
Before joining Udacity, Karl was a Site Reliability Engineer (SRE) at Google for eight years, building automation and monitoring to keep the world's busiest web services online.
The fundamentals of Python that every programmer needs to know.
On average, successful students take 1 month to complete this program.
No. This Course accepts all applicants regardless of experience and specific background.
No prior experience is required, but it is recommended that students are comfortable with basic computer skills, such as managing files, using third-party online programs, and navigating the Internet through an online browser.
The Introduction to Python course is comprised of content and curriculum to support one project. We estimate that students can complete the program in 1 month.
The project will be reviewed by the Udacity reviewer network and platform. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.
Access to this course runs for the length of time specified in the payment card above. If you do not graduate within that time period, you will continue learning with month to month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our programs.
Please see the Udacity Program Terms of Use and FAQs for policies on enrollment in our programs.
For this program, you will need a desktop or laptop computer running recent versions of Windows, Mac OS X, or Linux, and an unmetered broadband Internet connection. There are no additional hardware or software requirements for this program, other than those outlined on Udacity's general Technology Requirements page.