Clean an open dataset
Download a file from a public open-data portal, fix types, duplicates and missing values with pandas, and document each choice.
All pathsDiscover Coursera PlusAfter step 2 After step 3 After step 4 After step 5
Data & AI · 01Beginner
Data Analyst
Beginners or career changers heading into business data analysis.
Clean data with pandas, describe and test it statistically, build clear visualisations and bring AI into an analysis workflow.
368hours of coursework
37weeks at 10 h
5steps
19courses
3universities
Target skills
Data VisualizationData PresentationPython ProgrammingData ProcessingData CleansingWeb ScrapingStatistical AnalysisMatplotlibStatistical VisualizationExploratory Data AnalysisData-Driven Decision-MakingRestful API
Skill labels as listed on Coursera.
Target jobs
- Data analyst
- BI analyst
- Statistical research officer
Progression
- 1University of MichiganBeginnerPython, SQL, SQLite
Stated prerequisites: No prerequisites; designed as an on-ramp to programming
Show the 5 courses
Course Level Length Rating (reviews) Programming for Everybody (Getting Started with Python) Beginner 17 h 4.8 (233,775) Python Data Structures Beginner 20 h 4.9 (97,365) Using Python to Access Web Data Beginner 19 h 4.8 (44,591) Using Databases with Python Beginner 14 h 4.8 (21,659) Capstone: Retrieving, Processing, and Visualizing Data with Python Beginner 9 h 4.7 (14,483) - 2University of Colorado BoulderBeginnerPython, pandas, NumPy, Seaborn
Stated prerequisites: Python fundamentals and statistics
Show the 5 courses
Course Level Length Rating (reviews) Fundamental Tools of Data Wrangling Beginner 27 h 4.3 (22) Data Collection and Integration Intermediate 28 h 4.5 (16) Data Understanding and Visualization Intermediate 25 h — Data Processing and Manipulation Intermediate 29 h — Data Wrangling with Python Project Intermediate 26 h — - 3University of MichiganBeginnerPython, Jupyter, Matplotlib, NumPy, pandas, Seaborn, Statsmodels
Stated prerequisites: High school algebra; basic Python recommended
Show the 3 courses
Course Level Length Rating (reviews) Understanding and Visualizing Data with Python Beginner 20 h 4.7 (2,741) Inferential Statistical Analysis with Python Intermediate 22 h 4.6 (938) Fitting Statistical Models to Data with Python Intermediate 15 h 4.4 (718) - 4Johns Hopkins UniversityIntermediateTableau, ParaView
Show the 3 courses
Course Level Length Rating (reviews) Foundations of Data Visualization Intermediate 24 h 4.7 (10) Advanced Techniques in Data Visualization Intermediate 28 h — Specialized Data Visualization Approaches Intermediate 31 h — - 5University of MichiganBeginnerGenerative AI tools, GitHub
Stated prerequisites: Basic familiarity with computers and internet search
Show the 3 courses
Course Level Length Rating (reviews) AI-Powered Data Analysis: A Practical Introduction Beginner 5 h 4.5 (30) Systems Thinking for AI & Automation Beginner 4 h — Rethink How You Decide with AI Beginner 5 h —
With Coursera Plus
This path takes 368 hours, about 9 months at 10 hours a week. A Coursera Plus subscription gives access to most of its courses during that time.
Projects to build
A/B test
Compare two versions of a web page from public or simulated data: hypothesis test, confidence interval and a quantified recommendation.
KPI report
Design 4 to 6 clear charts on one topic (transport, energy, sales) and write a one-page analysis.
AI-assisted analysis
Run an analysis with an AI assistant, then check and correct every result by hand, logging the errors found.
Free textbooks
Python for EverybodyCharles R. SeveranceFree, CC BY 4.0
Python for Data Analysis, 3rd ed.Wes McKinneyOpen access online
Think Stats, 3rd ed.Allen B. DowneyFree, non-commercial Creative Commons licence
OpenIntro StatisticsD. Diez, M. Çetinkaya-Rundel, C. BarrFree PDF