This is the second of seven courses in the Google Advanced Data Analytics Certificate. The Python programming language is a powerful tool for data analysis. In this course, you鈥檒l 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.
Get Started with Python
Get Started with Python
This course is part of Google Advanced Data Analytics Professional Certificate
Instructor: Google Career Certificates
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4.8
(1,524 reviews)
Advanced level
Designed for those already in the industry
Flexible schedule
Approx. 24 hours
Learn at your own pace
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What you'll learn
Explain how Python is used by data professionals
Explore basic Python building blocks, including syntax and semantics
Understand loops, control statements, and string manipulation
Use data structures to store and organize data聽
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Assessments
3 quizzes, 17 assignments
Taught in English
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This course is part of the Google Advanced Data Analytics Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
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There are 5 modules in this course
You鈥檒l 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鈥檒l become familiar with the core concepts of object-oriented programming: object, class, method, and attribute. You鈥檒l learn about Jupyter Notebooks, an interactive environment for coding and data work. You鈥檒l investigate how to use variables and data types to store and organize your data; and, you'll begin practicing important coding skills.
What's included
12 videos7 readings4 assignments3 ungraded labs
Next, you鈥檒l discover how to call functions to perform useful actions on your data. You鈥檒l also learn how to write conditional statements to tell the computer how to make decisions based on your instructions. And you鈥檒l practice writing clean code that can be easily understood and reused by other data professionals.
What's included
8 videos4 readings3 assignments5 ungraded labs
You鈥檒l start off by exploring loops, which repeat a portion of code until a process is complete. You鈥檒l 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鈥檒l learn how to manipulate strings by indexing, slicing, and formatting them.
What's included
9 videos5 readings4 assignments7 ungraded labs
Now, you鈥檒l explore data structures in Python, which are methods of storing and organizing data in a computer. You鈥檒l focus on data structures that are among the most useful for data professionals: lists, tuples, dictionaries, sets, and arrays. You鈥檒l also discover how to categorize data using data loading, cleaning, and binning. Lastly, you鈥檒l learn about two of the most widely used and important Python tools for advanced data analysis: NumPy and pandas.
What's included
17 videos12 readings5 assignments9 ungraded labs
You will put everything you have learned about Python so far into practice with an end-of-course project. You鈥檒l complete an end-of-course project by using Python to inspect and organize a dataset provided in a realistic workplace scenario.
What's included
4 videos10 readings3 quizzes1 assignment6 ungraded labs
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Showing 3 of 1524
AA
5
Reviewed on Dec 9, 2024
Great intro to Python for someone with a very basic understanding of computer coding. Some challenges in the clarity of lab instructions, but overall very easy to follow along.
MG
5
Reviewed on Jun 22, 2023
I'm exited with this course, i learn python from scratch and pyhton libraries such as numpy and pandas are easy to learn. tutorial video are effictive, lab are so effictive, thanks a lot.
AM
5
Reviewed on Feb 12, 2024
The course was very well structured, covering all basic Python and pandas concepts, ending with comprehensive documentation and exploratory data analysis capstones.
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