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There are 4 modules in this course
In this course, 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.
By the end of this course, you will be able to:
- Explain Python fundamentals, including core Python syntax, data types (integer, float, string), and variable assignment
- Define fundamental concepts like object, class, method, and attribute in object-oriented programming
- Recognize the uses and benefits of Jupyter Notebook for data work and as a Python environment
- Identify Python's relevance to data science and why it is an essential tool for data analysis
- Perform basic mathematical calculations in Python
- Use Python's inherent capabilities to explore data effectively with built-in functions and keywords
- Gain knowledge of how to manage and utilize Python packages and interpreter options
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.
What's included
2 videos1 reading1 assignment
Show info about module content
2 videos•Total 7 minutes
Hello, Python!•2 minutes
Introduction to Python•5 minutes
1 reading•Total 8 minutes
Helpful resources and tips•8 minutes
1 assignment•Total 6 minutes
Test your knowledge: Get started with Python•6 minutes
The power of Python
Module 2•1 hour to complete
Module details
Become familiar with the core concepts of object-oriented programming: object, class, method, and attribute. Learn about Jupyter Notebooks, an interactive environment for coding and data work.
What's included
3 videos3 readings1 assignment1 ungraded lab
Show info about module content
3 videos•Total 14 minutes
Discover more about Python•7 minutes
Jupyter Notebook•3 minutes
Object-oriented programming•5 minutes
3 readings•Total 24 minutes
Python versus other programming languages•8 minutes
How to use Jupyter Notebooks•8 minutes
More about object-oriented programming•8 minutes
1 assignment•Total 6 minutes
Test your knowledge: The power of Python•6 minutes
Grow with Google is an initiative that draws on Google's decades-long history of building products, platforms, and services that help people and businesses grow. We aim to help everyone – those who make up the workforce of today and the students who will drive the workforce of tomorrow – access the best of Google’s training and tools to grow their skills, careers, and businesses.
Organizations of all types and sizes have business processes that generate massive volumes of data. Every moment, all sorts of information gets created by computers, the internet, phones, texts, streaming video, photographs, sensors, and much more. In the global digital landscape, data is increasingly imprecise, chaotic, and unstructured. As the speed and variety of data increases exponentially, organizations are struggling to keep pace.
Data science is part of a field of study that uses raw data to create new ways of modeling and understanding the unknown. To gain insights, businesses rely on data professionals to acquire, organize, and interpret data, which helps inform internal projects and processes. Data scientists rely on a combination of critical skills, including statistics, scientific methods, data analysis, and artificial intelligence.
Do I need to take the course in a certain order?
We highly recommend taking the courses in the order presented, as the content builds on information from earlier courses. This is the first course in a series of six courses that make up the Google Data Analysis with Python Specialization.
What do data professionals do?
A data professional is a term used to describe any individual who works with data and/or has data skills. At a minimum, a data professional is capable of exploring, cleaning, selecting, analyzing, and visualizing data. They may also be comfortable with writing code and have some familiarity with the techniques used by statisticians and machine learning engineers, including building models, developing algorithmic thinking, and building machine learning models.
Data professionals are responsible for collecting, analyzing, and interpreting large amounts of data within a variety of different organizations. The role of a data professional is defined differently across companies. Generally speaking, data professionals possess technical and strategic capabilities that require more advanced analytical skills such as data manipulation, experimental design, predictive modeling, and machine learning. They perform a variety of tasks related to gathering, structuring, interpreting, monitoring, and reporting data in accessible formats, enabling stakeholders to understand and use data effectively. Ultimately, the work of data professionals helps organizations make informed, ethical decisions.
Why start a career in data science?
Large volumes of data — and the technology needed to manage and analyze it — are becoming increasingly accessible. Because of this, there has been a surge in career opportunities for people who can tell stories using data, such as senior data analysts and data scientists. These professionals collect, analyze, and interpret large amounts of data within a variety of different organizations. Their responsibilities require advanced analytical skills such as data manipulation, experimental design, predictive modeling, and machine learning.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.