Welcome to my comprehensive portfolio documenting the completion of the Google Data Analytics Professional Certificate! It contains hands-on projects, labs, cheat sheets, and final assignments across 8 core courses, demonstrating proficiency in data analysis, visualization, SQL, R-Programing, and business intelligence tools.
- Certificate: IBM Data Science Professional Certificate
- Issued By: IBM via Coursera
- Duration: 7 comprehensive courses + Capstone Project
Professional Certificate - 8-course series
- Define and explain key concepts involved in data analytics including data, data analysis, and data ecosystems.
- Conduct an analytical thinking self assessment giving specific examples of the application of analytical thinking.
- Discuss the role of spreadsheets, query languages, and data visualization tools in data analytics.
- Describe the role of a data analyst with specific reference to jobs.
- Explain how the problem-solving road map applies to typical analysis scenarios.
- Discuss the use of data in the decision-making process.
- Demonstrate the use of spreadsheets to complete basic tasks of the data analyst including entering and organizing data.
- Describe the key ideas associated with structured thinking.
- Explain what factors to consider when making decisions about data collection.
- Discuss the difference between biased and unbiased data.
- Describe databases with references to their functions and components.
- Describe best practices for organizing data.
- Define different types of data integrity and identify risks to data integrity.
- Apply basic SQL functions to clean string variables in a database.
- Develop basic SQL queries for use on databases.
- Describe the process of verifying data cleaning results.
- Discuss the importance of organizing your data before analysis by using sorts and filters.
- Convert and format data.
- Apply the use of functions and syntax to create SQL queries to combine data from multiple database tables.
- Describe the use of functions to conduct basic calculations on data in spreadsheets.
- Describe the use of data visualizations to talk about data and the results of data analysis.
- Identify Tableau as a data visualization tool and understand its uses.
- Explain what data driven stories are including reference to their importance and their attributes.
- Explain principles and practices associated with effective presentations.
- Describe the R programming language and its programming environment.
- Explain the fundamental concepts associated with programming in R including functions, variables, data types, pipes, and vectors.
- Describe the options for generating visualizations in R.
- Demonstrate an understanding of the basic formatting in R Markdown to create structure and emphasize content.
- Differentiate between a capstone project, case study, and a portfolio.
- Identify the key features and attributes of a completed case study.
- Apply the practices and procedures associated with the data analysis process to a given set of data.
- Discuss the use of case studies/portfolios when communicating with recruiters and potential employers.
- Gain an immersive understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job
- Learn key analytical skills (data cleaning, analysis, & visualization) and tools (spreadsheets, SQL, R programming, Tableau)
- Understand how to clean and organize data for analysis, and complete analysis and calculations using spreadsheets, SQL and R programming
- Learn how to visualize and present data findings in dashboards, presentations and commonly used visualization platforms
- Data Analysis
- Creating case studies
- Data Visualization
- Data Cleansing
- Developing a portfolio
- Data Collection
- Spreadsheet
- Metadata
- SQL
- Data Ethics
- Data Aggregation
- Data Calculations
- R Markdown
- R Programming
- Rstudio
- Tableau Software
- Presentation
- Data Integrity
- Sample Size Determination
- Decision-Making
- Problem Solving
- Questioning
This portfolio represents my personal learning journey through the Google Data Analytics Professional Certificate. While this is primarily a showcase of my work, I welcome discussions, feedback, and collaborations on data analysis projects.
Sanketh Ks
- GitHub: @Sankethks27
- LinkedIn: Sanketh Ks
- Email: sankethks27@gmail.com
- Google for the comprehensive curriculum
- Coursera for the learning platform
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