Course
Data Science
Continuing Education

Get Started with Python

31 Hours

Estimated learning time

Self-Paced

Progress at your own speed

Popular course

A popular course among students

About the Course

Description

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

This Course is part of a program

You can only buy it along with program.

Sections

Schedule

Asynchronous

Delivery method

Online

Deliverables

  • 0 Credits

    Academic Excellence

    Earn necessary number of credit hours for completing this content

  • Hone Important Skills

    Total Upgrade

    Such as Numpy, Python Programming, Data Analysis, Computer Programming, Analysis