Embark on an exciting journey into the world of data analytics with Google データアナリティクス. This comprehensive 6-month program equips you with the fundamental skills required to thrive in the field of data analysis, without the need for prior experience or a degree.
Throughout the program, you will delve into essential concepts such as data analysis, data ecosystems, and analytical thinking. You'll develop proficiency in critical analysis skills, including data cleaning, analysis, and visualization, using tools such as spreadsheets, SQL, R programming, and Tableau. The curriculum is designed to provide a deep understanding of data analysis processes, preparing you for roles such as Junior or Associate Data Analyst, or database administrator.
One of the program's highlights is the opportunity to learn from Google employees who have initiated their careers in data analysis, providing invaluable insights and practical knowledge. Upon completion, you'll be well-prepared to pursue career opportunities, with a significant percentage of Google certified graduates reporting career advancement within 6 months of certification.
Don't miss this chance to establish a solid foundation in data analysis and embark on a fulfilling career in this rapidly growing field.
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Google データアナリティクス offers a comprehensive journey through 8 modules, teaching you the essential skills and knowledge required for a successful career in data analysis. From foundational concepts to practical applications, this program equips you with the expertise needed to excel in this high-demand field.
Get acquainted with the fundamental concepts of data analytics, including data ecosystems and the role of analytical thinking. Understand the relevance of spreadsheets, query languages, and data visualization tools in data analytics. Gain insights into the responsibilities of a data analyst.
Learn to apply analytical thinking to solve problems and understand the impact of data in decision-making processes. Acquire basic data analyst tasks using spreadsheet software and explore the important concepts related to structured thinking.
Understand the factors influencing decision-making in data collection, the differences between biased and unbiased data, and the elements and functions of databases. Gain insight into best practices for data organization.
Define data integrity and the risks associated with it, and apply basic SQL functions for cleaning string variables in a database. Learn to create basic SQL queries and validate data cleaning results.
Recognize the importance of organizing data before analysis, understand data transformation and formatting, and learn to perform basic calculations using functions in spreadsheet software. Gain insights into joining data from multiple database tables using SQL queries.
Explore the use of data visualization for sharing data and data analysis results. Understand the role of Tableau as a data visualization tool, and learn about the significance and attributes of data-driven stories. Delve into principles and practices for effective presentations.
Gain knowledge about the R programming language and its environment, including basic concepts such as functions, variables, data types, pipes, and vectors. Understand the option to create visualizations in R and grasp the basics of R Markdown and content emphasis.
Comprehend the significance of case studies and portfolios, and apply practical methods and steps aligned with the data analysis process to a given dataset. Discuss the utilization of case studies and portfolios in communication with hiring managers and prospective employers.
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