This repository is my data analyst journal to record and keep track of my learning process and insights from the Google Data Analytics Certificate and Google Advanced Data Analytics Certificate, including a timeline of learning below. This repository will keep updating until I finish the course and the documentation.
- ⭐ awesom-data-analysis
- Kaggle (My profile)
- Toward Data Science - Data community
- DAF - Data Analysis Framework
- DAB - Data Analysis Bible
- Bellabeat Case Study - Google Data Analytics Capstone Project [R]
- Bullrun Analysis Dashboard v1.0.0 - Dune dashboard crypto bullrun analysis (beta) [SQL (Trino fork)]
- CLV Business Analysis - Customer Lifetime Value (CLV) analysis for a retail business (Mock Data) [Python]
- Sales and Customer Dashboard - [Tableau] Mock-up data template building
- Olist EDA Practice - E-commerce Exploratory Data Analysis project [Python]
- Chinook Music Store — SQL Revenue Analysis - Sample dataset for EDA and query practices [SQL]
- Cafe Sales - Data cleaning training [Python]
- On-chain Tokenized Gold - Dune dashboard for XAUT, PAXG, and CGT [SQL (Trino fork)]
- Amazon Sales - E-commerce data analysis [Python]
- Crypto Leaderboard - Simple Crypto dashboard with Coingecko API [ETL, Polars]
- SQL Murder Mystery - A mystery game using SQL for beginners
- SQL Case Files - A SQL game for interactively practicing your SQL skills
- SQL Zoo - SQL tutorials and references with SQL Zoo
- DataLemur - Practice SQL Interview and Data Science Interview questions
| Day | Course | Progress |
|---|---|---|
| - | Google Data Analytics Certificate | - |
| 1 | Course 1: Foundations: Data, Data, Everywhere (Module 1, 2) | - Process of data analysis - Type of data - Data life cycle |
| 2 | Course 1: Foundations: Data, Data, Everywhere (Module 3, 4) | - Spreadsheets intro - SQL intro - R intro - Data visualization - Tableau intro - Data fairness |
| 3 | Course 2: Ask Questions to Make Data-driven Decisions (Module 1, 2) | - Effective questioning - SMART framework - Types of problem - Business and data analysis - Basic spreadsheets - Basic formula and operator |
| 4 | Course 2: Ask Questions to Make Data-driven Decisions (Module 3, 4) | - Softskills - Spreadsheets function/formula - Communication with stakeholders and team - Meetings and email etiquette |
| 5 | Course 3: Prepare data for exploration (Module 1, 2) | - Data ethics - Data source - Data collection considerations - Data structures |
| 6 | Course 3: Prepare data for exploration (Module 3) | - Databases - Metadata - CSV file - How data is generated - Extract data using spreadsheets and SQL |
| 7 | Course 3: Prepare data for exploration (Module 4) | - Organizing data - Folder structure - Access control - Data security |
| 8 | Course 4: Process Data from Dirty to Clean (Module 1, 2) | - Prepare and process data - Data integrity - Sample sizing - Data cleaning - Tools and technique |
| 9 | Course 4: Process Data from Dirty to Clean (Module 3, 4) | - Advanced data-cleaning functions - Data cleaning with BigQuery - Data verification - Documentation - Changelog, and version control system |
| 10 | Course 5: Analyze Data to Answer Questions (Module 1) | - Organizing data - Data formatting - SORT function - FILTER function |
| 11 | Course 5: Analyze Data to Answer Questions (Module 2) | - Data convert - Data validation - CONCAT and CONCATENATE |
| 12 | Course 5: Analyze Data to Answer Questions (Module 3) | - Aggregate functions - VLOOKUP - JOINs - COUNT - Subqueries |
| 13 | Course 5: Analyze Data to Answer Questions (Module 4) | - Formulas for basic calculations - Conditional formulas that use the IF function - SUMPRODUCT function - Pivot tables to organize calculations - Queries and calculations in SQL |
| 14 | Course 6: Share Data Through the Art of Visualization (Module 1, 2) | - Foundation of data visualization - Data viz decision tree - Design thinking - Basic Tableau - Data storytelling |
| 15 | Course 6: Share Data Through the Art of Visualization (Module 3, 4) | - Tableau dashboard - Effective data stories - Presentation - Q&A, Objections handling |
| 16 | Course 7: Data Analysis with R Programming (Module 1, 2) | - Introduction to R - RStudio & Positron IDE - Data structure - R packages (tidyverse) - Use pipes to nest code |
| 17 | Course 7: Data Analysis with R Programming (Module 3) | - Data frame - tibbles - Data import - R operator - R data cleaning - Bias function |
| 18 | Course 7: Data Analysis with R Programming (Module 4) | - ggplot2 - Adding label - Adding annotation - Aesthetics attributes - ggsave() |
| 19 | Course 7: Data Analysis with R Programming (Module 5) | - Documentation and reports - R Markdown - Exporting documentation - Structure of a markdown document |
| 20 | Course 8: Google Data Analytics Capstone | - Building portfolio - AI for data analytics - Bellabeat case study |
| 🎉 | Completed Google Data Analytics Certificate! | |
| - | - | |
| Google Advanced Data Analytics Certificate | ||
| 21 | Course 1: Foundation of Data Science (Module 1, 2, 3) | - Data science foundation - Critical data security and privacy principles - Data team structure - How data professionals use AI |
| 22 | Course 1: Foundation of Data Science (Module 4, EOP) | - PACE stages - Best communication practices - Project proposal - End-of-course project |
| 23 | Course 2: Get Started with Python (Module 1, 2) | - Introduction to Python - Jupyter Notebook - Object-oriented programming - Variables - Naming conventions - Data types - Function - Conditional statement - Operator - Clean code |
| 24 | Course 2: Get Started with Python (Module 3) | - While loops - For loops - Strings slicing |
| 25 | Course 2: Get Started with Python (Module 4, 5) | - Lists - Tuples - Dictionaries - Sets - Arrays - NumPy - pandas - Python for dataset management |
| 26 | Course 3: Go Beyond the Numbers: Translate Data into Insights (Module 1, 2) | - Exploratory Data Analysis (EDA) - Data sources - Data types - Data formats - How to use Python to uncover big picture understandings - Date and time transformations in Python |
| 27 | Course 3: Go Beyond the Numbers: Translate Data into Insights (Module 3, 4, 5) | - EDA practices - Missing data and outliers - Categorical and numerical data - Input validation - Workplace skills - Ethical considerations - Tableau advanced - End of course project |
| 28 | Course 4: The Power of Statistics (Module 1) | - Introduction to statistics - Descriptive statistics - Mean, median, mode - Calculate statistics with Python |
| 29 | Course 4: The Power of Statistics (Module 2, 3, 4, 5, 6) | - The principles of probability - Binomial - Poisson - Bayes' theorem - Normal distribution - Z-scores - SciPy stats - Sampling process - Sampling methods - Central limit theorem - Confidence intervals (CI) - Hypothesis testing - One-sample test - Two-sample test - End of course project |
| 30 | Course 5: Regression Analysis: Simplify Complex Data Relationships (Module 1) | - Introduction to linear regression - Logistic regression |
| 31 | Course 5: Regression Analysis: Simplify Complex Data Relationships (Module 2, 3) | - Simple linear regression - Uncertainty in regression analysis - Interpret regression results - Multiple linear regression - Model assumptions - Model construction - Model interpretation and evaluation |
| 32 | Course 5: Regression Analysis: Simplify Complex Data Relationships (Module 4, 5, 6) | - Advance hypothesis testing - Chi-square - ANOVA, ANCOVA, MANOVA, MANCOVA - Binomial logistic regression - Importance of the logit function - Maximum likelihood estimation - Construct logistic regression in Python using sci-kit learn - Evaluation metrics in sci-kit learn |
| 33 | Course 6: The Nuts and Bolts of Machine Learning (Module 1, 2, 3) | - Introduction to machine learning - Ethics in machine learning - Python for machine learning - Feature engineering - Naive Bayes - K-means algorithm - Inertia and silhouette score |
| 34 | Course 6: The Nuts and Bolts of Machine Learning (Module 4, 5) | - Tree-based modeling - Hyper-parameter tuning - Ensembling techniques - Bagging methods - Boosting methods |
| Course 7: Google Advanced Data Analytics Capstone | Project on hold | |
| 🎉 | Completed Advanced Google Data Analytics Certificate! |
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