Get Started with Python By Google Course Syllabus

Overview: This course provides a comprehensive introduction to Python programming with a focus on applications in data analysis. Designed for data professionals and beginners with foundational analytical knowledge, it covers core Python concepts, data structures, functions, and essential libraries like NumPy and pandas. Through hands-on labs and interactive coding in Jupyter Notebooks, learners will gain practical skills applicable across industries. The course is self-paced, with approximately 28 hours of content, making it ideal for those preparing for roles in data science, analytics, and machine learning.

Module 1: Hello, Python!

Estimated time: 3 hours

• Introduction to Python and its applications in data analysis
• Understanding object-oriented programming concepts: objects, classes, methods, and attributes
• Working with variables and data types
• Utilizing Jupyter Notebooks for interactive coding

Module 2: Functions and Conditional Statements

Estimated time: 3 hours

• Defining and invoking functions to perform specific tasks
• Implementing conditional statements to control program execution
• Writing clean and reusable code

Module 3: Data Structures

Estimated time: 6 hours

• Exploring lists, tuples, dictionaries, and sets
• Organizing and managing data efficiently using appropriate structures
• Manipulating strings and working with structured data

Module 4: Control Structures

Estimated time: 4 hours

• Implementing loops (for and while) for repetitive tasks
• Using conditional logic to manage program flow
• Combining control structures for complex logic

Module 5: Working with Libraries

Estimated time: 8 hours

• Importing and utilizing Python libraries such as NumPy and pandas
• Performing data analysis tasks: loading, cleaning, and binning data
• Applying library functions to real-world datasets

Module 6: Final Project

Estimated time: 4 hours

• Analyze a real-world dataset using Python
• Apply data structures, functions, and control flow
• Generate insights using pandas and NumPy with a final report in Jupyter Notebook

Prerequisites

• Familiarity with basic analytical principles
• Basic computer literacy
• Recommended: Prior exposure to data handling or spreadsheet software

What You'll Be Able to Do After

• Understand how Python is used by data professionals across industries
• Write Python code using proper syntax, variables, and data types
• Use functions, conditionals, and loops to control program flow
• Manipulate data using core data structures like lists, dictionaries, and sets
• Apply Python libraries such as NumPy and pandas for real-world data analysis tasks