Course Summary
This course teaches you how to analyze data using Python. You'll learn to use data analysis libraries to manipulate, analyze, and visualize complex datasets.Key Learning Points
- Learn to use Python libraries for data analysis
- Manipulate and clean datasets
- Visualize data using various techniques
Job Positions & Salaries of people who have taken this course might have
- USA: $60,000 - $120,000
- India: ₹400,000 - ₹1,000,000
- Spain: €20,000 - €40,000
- USA: $60,000 - $120,000
- India: ₹400,000 - ₹1,000,000
- Spain: €20,000 - €40,000
- USA: $65,000 - $120,000
- India: ₹400,000 - ₹1,500,000
- Spain: €25,000 - €45,000
- USA: $60,000 - $120,000
- India: ₹400,000 - ₹1,000,000
- Spain: €20,000 - €40,000
- USA: $65,000 - $120,000
- India: ₹400,000 - ₹1,500,000
- Spain: €25,000 - €45,000
- USA: $80,000 - $150,000
- India: ₹500,000 - ₹2,500,000
- Spain: €30,000 - €60,000
Related Topics for further study
Learning Outcomes
- Use Python libraries for data analysis and visualization
- Manipulate and clean datasets
- Apply data analysis techniques to solve real-world problems
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of Python programming
- Familiarity with data structures and algorithms
Course Difficulty Level
IntermediateCourse Format
- Online self-paced
- Video lectures
- Assignments and quizzes
Similar Courses
- Applied Data Science with Python
- Python Data Science Handbook
Related Education Paths
Related Books
Description
This is the fifth course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. In this course, you’ll explore the “analyze” phase of the data analysis process. You’ll take what you’ve learned to this point and apply it to your analysis to make sense of the data you’ve collected. You’ll learn how to organize and format your data using spreadsheets and SQL to help you look at and think about your data in different ways. You’ll also find out how to perform complex calculations on your data to complete business objectives. You’ll learn how to use formulas, functions, and SQL queries as you conduct your analysis. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.
Knowledge
- Discuss the importance of organizing your data before analysis with references to sorts and filters
- Demonstrate an understanding of what is involved in the conversion and formatting of data
- Apply the use of functions and syntax to create SQL queries for combining data from multiple database tables
- Describe the use of functions to conduct basic calculations on data in spreadsheets
Outline
- Organizing data to begin analysis
- Introduction to getting organized
- The analysis process
- Ayanna: Sticking with it
- Always a need to organize
- More on sorting and filtering
- Sorting datasets
- The SORT function
- Emma: Journey to a meaningful career
- Sorting queries in SQL
- Course syllabus
- Learning Log: Process and organize your data
- Keeping data organized with sorting and filters
- Optional: Upload the movie dataset to BigQuery
- Sorting and filtering in Sheets and Excel
- Optional Refresher: Using BigQuery
- Glossary: Terms and definitions
- Test your knowledge on understanding data analysis
- Test your knowledge on organizing data
- Test your knowledge on sorting in spreadsheets
- Hands-On Activity: SQL sorting queries
- Hands-On Activity: Analyze weather data in BigQuery
- Test your knowledge on sorting in SQL
- Weekly challenge 1
- Formatting and adjusting data
- Getting started with data formatting
- From one type to another
- Data validation
- Conditional formatting
- Merging and multiple sources
- Strings in spreadsheets
- What to do when you get stuck
- Layla: All about the analyze phase
- Running into challenges? Not to worry!
- When to use which tool
- Converting data in spreadsheets
- Transforming data in SQL
- Optional: Prepare to use the bike sharing dataset in BigQuery
- Manipulating strings in SQL
- Learning Log: A data analysis checklist
- Advanced spreadsheet tips and tricks
- Glossary: Terms and definitions
- Hands-On Activity: Combine multiple pieces of data
- Test your knowledge on converting and formatting data
- Test your knowledge on combining multiple datasets
- Self-Reflection: Stack Overflow
- Weekly challenge 2
- Aggregating data for analysis
- Aggregate data for analysis
- Preparing for VLOOKUP
- VLOOKUP in action
- Identifying common VLOOKUP errors
- Understanding JOINS
- COUNT and COUNT DISTINCT
- Queries within queries
- Using subqueries to aggregate data
- Justin: Where data analysis takes you
- VLOOKUP core concepts
- Optional: Upload the employee dataset to BigQuery
- Secret identities: The importance of aliases
- Using JOINs effectively
- Optional: Upload the warehouse dataset to BigQuery
- SQL functions and subqueries: A functional friendship
- Glossary: Terms and definitions
- Hands-On Activity: Using VLOOKUP
- Test your knowledge on VLOOKUP
- Hands-On Activity: Queries for JOINS
- Test your knowledge on using JOINS to aggregate data
- Test your knowledge on working with subqueries
- Weekly challenge 3
- Performing data calculations
- Data calculations
- Common calculation formulas
- Functions and conditions
- Composite functions
- Start working with pivot tables
- Pivot tables continued
- Queries and calculations
- Embedding simple calculations in SQL
- Calculations with other statements
- Check and recheck
- Temporary tables
- Multiple table variations
- Congratulations!
- Functions with multiple conditions
- Elements of a pivot table
- Using pivot tables in analysis
- Optional: Upload the avocado dataset to BigQuery
- Types of data validation
- Learning Log: Finish your data analysis checklist
- Working with temporary tables
- Your intermediate guide to SQL
- Glossary: Terms and definitions
- Coming up next...
- Hands-On Activity: Working with conditions
- Test your knowledge on data calculations
- Hands-On Activity: Explore movie data with pivot tables
- Test your knowledge on using pivot tables
- Hands-On Activity: Calculations in SQL
- Test your knowledge on SQL calculations
- Hands-On Activity: From spreadsheets to BigQuery
- Test your knowledge on data validation
- Hands-On Activity: Create temporary tables
- Test your knowledge on using SQL with temporary tables
- Weekly challenge 4
- Course challenge
Summary of User Reviews
Key Aspect Users Liked About This Course
The course provides practical training on data analysis using Python.Pros from User Reviews
- Well-structured course content
- Hands-on practice exercises
- Experienced and knowledgeable instructors
- Excellent support from the community
- Useful assignments and quizzes
Cons from User Reviews
- Some sections are too advanced for beginners
- Some technical issues with the platform
- Not enough guidance on how to apply the concepts to real-world problems
- Some lectures are too long and repetitive
- The pace may be too slow for advanced users
Google Career CertificatesTop Instructor
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