Get Started with Python
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Get Started with Python at Coursera Overview
Duration | 25 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Advanced |
Official Website | Explore Free Course  |
Credential | Certificate |
Get Started with Python at Coursera Highlights
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Coursera Labs Includes hands on learning projects. Learn more about Coursera Labs External Link
- Advanced Level
- Approx. 25 hours to complete
- English Subtitles: English
Get Started with Python at Coursera Course details
- 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’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 the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate.
- 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
Get Started with Python at Coursera Curriculum
Hello, Python!
Introduction to Course 2
Welcome to week 1
Adrian: My path to a data career
Introduction to Python
Discover more about Python
Jupyter Notebooks
Object-oriented programming
Hamza: How Python helped my data science career
Variables and data types
Create precise variable names
Data types and conversions
Wrap-up
Helpful resources and tips
Course 2 overview
Follow-along instructions: Hello, Python!
Python versus other programming languages
Create, upload, and edit Jupyter Notebooks
More about object-oriented programming
Explore Python syntax
Glossary terms from Week 1
Test your knowledge: Get started with the course
Test your knowledge: The power of Python
Test your knowledge: Using Python syntax
Weekly challenge 1
Functions and conditional statements
Welcome to week 2
Michelle: Approach problems with an analytical mindset
Define functions and returning values
Write clean code
Use comments to scaffold your code
Make comparisons using operators
Use if, elif, else statements to make decisions
Wrap-up
Follow-along instructions: Functions and conditional statements
Reference guide: Functions
Reference guide: Python operators
Reference guide: Conditional statements
Glossary terms from week 2
Test your knowledge: Functions
Test your knowledge: Conditional statements
Weekly challenge 2
Loops and strings
Welcome to week 3
Introduction to while loops
Introduction to for loops
Loops with multiple range() parameters
Work with strings
String slicing
Format strings
Wrap-up
Follow-along instructions: Loops and strings
Loops, break, and continue statements
For loops
String indexing and slicing
String formatting and regular expressions
Glossary terms from week 3
Test your knowledge: While loops
Test your knowledge: For loops
Test your knowledge: Strings
Weekly challenge 3
Data structures in Python
Welcome to week 4
Introduction to lists
Modify the contents of a list
Introduction to tuples
More with loops, lists, and tuples
Introduction to dictionaries
Dictionary methods
Introduction to sets
The power of packages
Introduction to NumPy
Basic array operations
Introduction to pandas
pandas basics
Boolean masking
Grouping and aggregation
Merging and joining data
Wrap-up
Follow-along instructions: Data structures in Python
Reference guide: Lists
Compare lists, strings, and tuples
Glossary terms from week 4
Test your knowledge: Lists and tuples
Test your knowledge: Dictionaries and sets
Test your knowledge: Arrays and vectors with NumPy
Test your knowledge: Dataframes with pandas
Weekly challenge 4
Course 2 end-of-course project
Welcome to week 5
Introduction to Course 2 portfolio project
End-of-course project wrap-up and tips for ongoing career success
Course wrap-up
Course 2 end-of-course portfolio project overview: Automatidata
Activity Exemplar: Create your Course 2 Automatidata project
Course 2 glossary
Get started on the next course
Activity: Create your Course 2 Automatidata project
Assess your Course 2 end-of-course project
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