67 data analysis
Data analysis data and API using data,,, visualization, up to perform practical work type analysis education with.
0. Purpose and ultimate goal
Data analysis education of objective learners Kaggle, Google Dataset Search, data.gov, data.gov.uk, EU Open Data Portal, Public Data Portal, GitHub data using data · · analysis and Python, SQL, pandas, Tableau, Power BI, Looker Studio with. data analysis and BI practical work education of using portfolio focused with operation.
Referenced professional training patterns
- Data analysis of Python · SQL · BI based practical work project
- Data visualization course of data,, report writing
- API · CSV · JSON data course of automation,, quality practice
- Portfolio type education of problem definition, analysis, presentation deck creation
Introductory · 1 Day
Introductory 1 day data analysis curriculum
Data spreadsheet with basic analysis result create.
| Category | Details | Practice methods |
|---|---|---|
| Objective 1 | Data of and quality understanding. | Kaggle, Google Dataset Search, data.gov, data.go.kr, OECD Data in by data search and file compare. CSV, XLSX, JSON, API,,,, data with. |
| Objective 2 | Basic analysis perform. | Excel or Google Sheets in filter, sorting, pivot table, with data. ,,,, using data table writing. |
| Objective 3 | Analysis report create. | Chart, chart,, map visualization using core table visualization. PowerPoint or Canva with analysis, data,, 1 report create. |
| Platforms | Excel 365, Google Sheets, Kaggle, Google Dataset Search, data.gov, data.go.kr, Canva, PowerPoint |
|---|---|
| Instructor profile | Data, spreadsheet analysis, basic · visualization education 2years or more |
| Target learners | Data analysis introductory, · college student,, job seeker, data activity |
| Duration | 4-6 hours |
| Materials | , internet, Google account, spreadsheet tools, data |
| Deliverables | Data table, basic analysistable, 1 data analysis report |
| Assessment method | Data 25%, 25%, analysis 25%, report 15%, participation 10% |
Beginner · 3 Days
Beginner 3 days data analysis curriculum
Python and BI tools using data and visualization.
| Category | Details | Practice methods |
|---|---|---|
| Objective 1 | Python based data. | Google Colab or Jupyter Notebook in pandas read_csv, read_excel, read_json with data. Data,,,,, pandas info, describe, isna with. |
| Objective 2 | Analysis data create. | Pandas dropna, fillna, groupby, pivot_table, merge using analysis to data. SQL SELECT, WHERE, GROUP BY, JOIN of SQLite or DuckDB with practice using table based analysis. |
| Objective 3 | Visualization and create. | Matplotlib, Plotly, Tableau Public, Power BI tools using comparison · · chart creation. Looker Studio or Power BI with KPI, filter, table, chart create. |
| Platforms | Python, pandas, Google Colab, Jupyter Notebook, SQLite/DuckDB, Tableau Public, Power BI, Looker Studio |
|---|---|
| Instructor profile | Python data analysis, SQL basic, BI, data visualization education 3years or more |
| Target learners | College student, job seeker, data, marketing · education operation practitioner |
| Duration | 12-18 hours |
| Materials | , Google account, Python/Colab, BI tools account, data |
| Deliverables | Data, analysis, visualization chart, |
| Assessment method | Python practice 25%, 25%, analysis 20%, visualization 20%, presentation 10% |
Beginner · 1 Week
Beginner 1 week data analysis curriculum
Problem of and data using analysis project perform.
| Category | Details | Practice methods |
|---|---|---|
| Objective 1 | Analysis and table design. | , education,,,, Category using analysis and writing. KPI, table,, filter, comparison, objective table with organize. |
| Objective 2 | Data analysis perform. | ,,,, table based on CSV · API data. Pandas merge, concat, groupby and Power Query comparison and analysis result create. |
| Objective 3 | Focused result complete. | Tableau Public or Power BI in type and type Category using creation. Data,, plan using portfolio presentation deck. |
| Platforms | Kaggle, data.gov, EU Open Data Portal, Python, pandas, Power Query, Tableau Public, Power BI, PowerPoint |
|---|---|
| Instructor profile | Data project, Python · BI practice, data 3years or more |
| Target learners | Data portfolio, team, startupteam, education · project |
| Duration | 20-30 hours |
| Materials | , Python/BI, data 2, presentation deck |
| Deliverables | Analysis, data, BI, presentation deck |
| Assessment method | Problem definition 20%, data 25%, analysis 25%, report 20%, presentation 10% |
Intermediate · 4 Weeks
Intermediate 4 weeks data analysis curriculum
Automation and · analysis practical work analysis project complete.
| Category | Details | Practice methods |
|---|---|---|
| Objective 1 | Data. | Requests, BeautifulSoup, API authentication,,, with saving procedure design. GitHub Actions or Windows through automation create. |
| Objective 2 | Advanced analysis perform. | Pandas, seaborn matplotlib/Plotly, scipy using relationship,,, analysis. GeoPandas, Folium, QGIS with table · based data map. |
| Objective 3 | Analysis result operation format with. | Streamlit or Power BI Service using filter operation analysis create. Notion or Google Docs to data,, procedure, · copyright table documentation. |
| Platforms | Python, requests, pandas, Plotly, GeoPandas/Folium/QGIS, Streamlit, Power BI Service, GitHub, Notion |
|---|---|
| Instructor profile | API, Python analysis, · analysis, experience 4years or more |
| Target learners | Data analysis practitioner,, · project PM, portfolio advanced learners |
| Duration | 40-60 hours |
| Materials | , Python development, GitHub account, API, BI account, project document |
| Deliverables | Automation, analysis, map ·, operation document |
| Assessment method | 25%, analysis 30%, 20%, documentation 15%, presentation 10% |
Advanced · 8 Weeks
Advanced 8 weeks data analysis curriculum
Data, report, materials up to project perform.
| Category | Details | Practice methods |
|---|---|---|
| Objective 1 | Data analysis. | , scenario, data, or education use design. ERD, data with, table, analysis with, MVP writing. |
| Objective 2 | Analysis. | Python ETL, PostgreSQL/SQLite, FastAPI or Streamlit, BI connect end-to-end analysis create. ,, local community analysis and result. |
| Objective 3 | Portfolio and educationmaterials complete. | GitHub README, presentation deck,, analysis report · portfolio. Introductory practice data, step-by-step,, assessment rubric, instructor operation manual creation. |
| Platforms | Python, pandas, SQLAlchemy, PostgreSQL/SQLite, FastAPI/Streamlit, GitHub, Power BI/Tableau/Looker Studio, Notion |
|---|---|
| Instructor profile | Data, ETL · DB · prototype, BI, educationmaterials development 5years or more |
| Target learners | Data analysis instructor course, data, startupteam, advanced portfolio |
| Duration | 80-120 hours |
| Materials | , Python/DB, GitHub account, data, BI account, presentation deck tools |
| Deliverables | Data, ETL, DB, / MVP, educationmaterials |
| Assessment method | 20%, 30%, analysisquality 20%, educationmaterials 15%, presentation 15% |