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 program is designed to provide you with the foundational knowledge and practical skills required for a successful career in data analysis. Throughout the 8 modules, you will delve into the key concepts of data analysis, learn essential analytical skills and master tools such as spreadsheets, SQL, R programming, and Tableau for data visualization.
As you progress through the course, you will gain a deep understanding of data cleaning, analysis, and visualization techniques, enabling you to confidently tackle real-world data challenges. Whether you aspire to become a junior or associate data analyst or pursue a career as a database administrator, this program will prepare you for in-demand roles in the field of data analytics. By the end of the program, you will be equipped with the expertise to make data-driven decisions, extract insights, and present compelling visualizations, setting the stage for a successful career in this dynamic industry.
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The Google データアナリティクス course comprises 8 modules that will provide you with a comprehensive understanding of data analysis, from foundational concepts to advanced tools and techniques. By mastering these modules, you'll be well-prepared to embark on a successful career in data analytics.
Explore the foundational concepts of data analytics, including the role of data, data analysis, and the data ecosystem. Gain insights into the responsibilities of a data analyst and understand the roles of spreadsheets, query languages, and data visualization tools in data analytics.
Learn to apply analytical thinking to solve problems and make data-driven decisions. Acquire essential skills such as using spreadsheets for data input and organization, and develop a structured approach to problem-solving.
Understand the process of preparing data for exploration, including making informed decisions when collecting data and recognizing the differences between biased and unbiased data. Gain knowledge of database functions and best practices for data organization.
Define data integrity and the risks associated with it. Apply basic SQL functions for cleaning string variables in a database, create basic SQL queries, and validate data cleaning processes.
Recognize the importance of organizing data before analysis, understand data transformation and formatting, and learn SQL query functions and syntax for combining data from multiple database tables. Gain proficiency in using spreadsheet functions for basic calculations.
Explore the use of data visualization tools to share data and analysis results. Understand the role of Tableau as a data visualization tool and learn the principles and practical methods for effective presentations.
Delve into the programming language R and its environment, including basic concepts such as functions, variables, data types, pipes, vectors, and creating visualizations in R. Understand the basics of R Markdown and emphasize content creation.
Gain a comprehensive understanding of case studies, portfolios, and their relevance. Apply practical methods and procedures aligned with the data analysis process to a given data set, and discuss the utilization of case studies and portfolios in communication with potential employers.
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