Google Data Analytics Professional Certificate

Identify reliable data sources, use APIs and web scraping basics, and organize datasets for consistency.

Master VLOOKUP, INDEX-MATCH, IF statements, and text functions to manipulate and prepare data in Excel and Google Sheets.

Detect missing data, apply imputation techniques, and document your cleaning process for reproducibility.

Use built-in tools to deduplicate records, normalize text, and ensure consistent formatting across datasets.

Create data validation rules, perform consistency checks, and verify cross-field relationships to maintain quality.

Summarize and reshape data using pivot tables, calculated fields, and grouping to uncover quick insights.

Write your first SQL queries to retrieve, filter, and sort data from relational databases.

Use COUNT, SUM, AVG, and GROUP BY to aggregate data and generate summary statistics directly in SQL.

Master INNER, LEFT, RIGHT, and FULL OUTER joins to combine multiple tables and expand your analysis scope.

Simplify complex queries with subqueries and Common Table Expressions (CTEs) for better readability and performance.

Set up R and RStudio, navigate the interface, and run your first scripts for basic calculations and data exploration.

Understand R’s core data types and structures, and practice creating and manipulating them for analysis.

Load CSV, Excel, and SQL data into R, and export results to shareable formats like CSV and PDF.

Use dplyr verbs, filter, select, mutate, arrange, and summarize, to clean and transform datasets efficiently.

Chain operations with pipes (%>%), perform grouped summaries, and write readable, efficient R code.

Calculate measures of central tendency, spread, and distribution shape using base R and dplyr.

Create compelling plots, scatterplots, histograms, bar charts, and customize themes for professional presentations.

Apply t-tests, chi-square tests, and confidence intervals to validate assumptions and draw conclusions from data.

Import data into Tableau, understand dimensions and measures, and navigate the workspace for effective analysis.

Create and customize common chart types to communicate trends, comparisons, and proportions clearly.

Design scatter plots for correlation analysis and heat maps for geographic or matrix-based insights.

Build interactive dashboards with filters, parameters, and actions to let stakeholders explore data dynamically.

Write calculated fields for custom metrics and use table calculations for running totals, percent of total, and more.

Structure a data story, choose the right visuals, and design presentations that drive action and clarity.

Apply design principles to make dashboards visually appealing, accessible, and easy to interpret for all audiences.

Publish dashboards to Tableau Public or Server, embed them in reports, and share insights with stakeholders.

Build a complete sales performance dashboard from scratch, incorporating multiple data sources and interactive elements.

Explore how AI tools can automate data cleaning, generate insights, and enhance predictive capabilities in your workflow.

Use AI-powered tools to detect anomalies, suggest transformations, and streamline repetitive cleaning tasks.

Leverage AI to identify patterns, correlations, and outliers in your data, accelerating initial analysis phases.

Ask questions in plain language and get automated summaries, charts, and insights using modern AI platforms.

Apply simple AI models for forecasting and classification, and interpret results to support business decisions.

Choose a real-world scenario, define SMART questions, and outline your analysis plan for the capstone.

Gather and clean your dataset, document your process, and validate data quality for the capstone analysis.

Perform statistical analysis in R, create compelling Tableau dashboards, and uncover key insights for your scenario.

Synthesize findings into a clear narrative, prepare a presentation, and recommend actionable next steps.

Practice delivering your analysis with confidence, handle questions, and communicate technical details clearly.

Highlight your certificate, projects, and technical skills to attract recruiters and land entry-level interviews.

Use LinkedIn effectively, prepare for technical interviews, and leverage Google’s career resources for job search success.

Explore next steps like Python for data analysis, machine learning, and specialized certifications to advance your career.