4 tips on how to use this Learning guide:
Please consider your own actual situation to learn.
If you still want to learn about other courses outside the guide, go ahead!
This guide is for informational purposes only, and there is no guarantee that you will be able to enter Google work even after you have completed all of the courses.
This guide is not updated regularly. You can follow Google for Students +page on Google + for more information at any time.
The recommendation of a preparatory style
Description: A computer science introduction is the basic content of the introduction of coding.
Online resources: Udacity–intro to CS Course, Coursera–computer Science 101
Beginner Online Resources: Learn to Program:the Fundamentals, MIT Intro to programming in Java, Google ' s Python Class, coursera–introduction To Python, Python Open Source E-book
Intermediate Online resources: Udacity ' s Design of computer Programs, Coursera–learn to program:crafting quality Code, coursera–programming Lan Guages, Brown university–introduction to programming Languages
Tip: You can choose one or more of these languages--java Script, CSS, HTML, Ruby, PHP, C, Perl, Shell, Lisp, Scheme.
Online resources: w3school.com–html Tutorial, codeacademy.com
Tip: Learn how to track bugs, create tests, and breakpoints.
Online resources: Udacity–software testing Methods, Udacity–software debugging
Online resources: MIT Mathematics for Computer Science, coursera–introduction to Logic, coursera–linear and discrete optimization, Cou Rsera–probabilistic graphical Models, coursera–game theory
Tip: Learn the basic data types (stacks, queues, and backpacks), sorting algorithms (Quick sort, merge sort, heap sort), data structures (binary search tree, red black tree, hash list), large O notation.
Online resources: MIT Introduction to Algorithms, Coursera Introduction to algorithms part 1& Part 2, List of algorithms, List of Data Structures, book:the algorithm Design Manual
Online resources: UC Berkeley Computer Science 162
Online resources: Stanford university–introduction to robotics, Natural Language processing, machine learning
Online resources: Coursera–compilers
Online resources: coursera–cryptography, udacity–applied cryptography
Online resources:coursera–heterogeneous Parallel Programming
Online resources: coursera–heterogeneous Parallel Programming
Non-study advice
Tip: Create and maintain a Web site, build your own server, or build a robot.
Online resources: Apache List of Projects, Google Summer of Code, Google Developer Group
Handle a small part of a very large system (code base), read and understand existing code, documentation, and Debug.
Tip: GitHub can be used to read the source code and contribute to a project.
Online resources: Github, Kiln
Tip: This will help you improve your team's ability to work and learn new things from others.
Tip: You can practice algorithmic knowledge in the Codejam or ACM programming contests.
Online resources: Codejam, ACM ICPC
Tip: Helping others can deepen your understanding of the field.
Note: The internship application should be applied in advance before the commencement of the internship. In the United States, the internship is in the summer (May to September), the application will generally be several months in advance.
Online resources: Google.com/jobs
Google publishes Programmer's Guide