Courses / Live bootcamps
Data Analyst with AI Bootcamp
SQL, dashboards and AI-assisted analysis that answer a manager's question with evidence.
Data Analyst with AI Bootcamp is a 12-week live online bootcamp, taught on Zoom by one instructor at about 15 hours a week, with 6 deployed projects and a one-to-one every week. The founding price is A$319, down from A$690. Live sessions run on weekday evenings from 5:30 PM Sri Lanka and India time, with full-day sessions at weekends.
Founding cohort: A$319A$690
Founding cohort, one payment. Founding students keep their founding price on any second programme.
10 spots open now
0 held · 10 open
First cohort. Spot holders hear the start date first.
By week 12, you will have shipped
Weeks 1 to 2
Answered in SQL
Weeks 3 to 4
Exploration
Weeks 5 to 6
The dashboard
Weeks 7 to 8
The experiment
Weeks 9 to 10
End to end
Weeks 11 to 12
Employer brief
- weeks, live on Zoom
- 12
- hours a week
- 15
- deployed projects
- 6
- minutes 1-1, every week
- 30
Who it is for, and what you receive.
People who live in spreadsheets, or want to, and are changing career into data analysis. No code or SQL needed to start; you finish writing both with an AI pair and checking its work.
Before you start
Comfortable with spreadsheets; no code or SQL needed.
Skills
- SQL
- spreadsheets
- Power BI
- data cleaning
- statistics
- pandas
- AI-assisted analysis
- data storytelling
A week, about 15 hours
- Live on Zoom
- 4h
- Set reading and exercises
- 6h
- The project
- 5h
- 1
Six deployed projects
Each graded by Nova against a published rubric and signed off by the instructor at the gate.
- 2
The twelve-week plan
Every week has its theme, its topics and what you build, published before you apply and taught live by your instructor.
- 3
Live on Zoom every week
A 90-minute live code review, a 60-minute squad lab, 60 minutes of office hours, and a 30-minute 1-1 with your instructor.
- 4
Your hiring plan
Opened in week 1 and reviewed in every 1-1: target roles, the gap map, the proof list, weekly actions, an interview log, the outcome.
- 5
The record
Every grade and every project with its repository at square1ai.com/u/{handle}, and the recording of your viva, verifiable by any employer.
- 6
The certificate
A credential ID that resolves at square1ai.com/verify to the real completion.
- 7
The hiring sprint
Weeks 11 and 12: CV and portfolio from graded work, applications, mock interviews scored against the role, demo day.
- 8
Nova for twelve weeks
A tutor with every submission of yours in its memory, at 2am as well as in class.
Twelve weeks in six parts.
Each part teaches for a week, then you build and deploy a project, then a gate checks it before the next part opens. The project and its gate are the part's entry on your record.
Live time each week on Zoom: a 90-minute class where the instructor reviews real submissions, a 60-minute squad lab, 60 minutes of office hours, and your own 30-minute 1-1. Nothing is lectured live; the recorded lessons do that.
Spreadsheets to SQL
Part 1 · Weeks 1 to 2
A fictional cafe chain exports its sales into a database and wants ten questions answered: best sellers, busiest hours, store differences and more. You clean the data and answer each question in SQL.
- PostgreSQL
- Microsoft Copilot
- ChatGPT
Key skills- Asking the question before the data
- Spreadsheets done properly
- SQL from SELECT to joins
Week 1
Spreadsheets to SQL
Asking the question before the data. Spreadsheets done properly. SQL: SELECT, WHERE, ORDER BY.
You build: Ten questions answered in a spreadsheet
Week 2
Project 1: answered in SQL
Joins and grouping. Checking your answer.
You build: A cleaned dataset and ten business questions answered in SQL
Project 1 · the gate at week 2
Answered in SQL
A cleaned dataset and ten answered business questions in SQL, published
You hand in
- Cleaned dataset
- Ten SQL queries
- A one-page answer sheet
The gate
Every answer matches the withheld answer key.
Cleaning and exploring
Part 2 · Weeks 3 to 4
Pick a real public dataset from a government or open data portal, clean it with an AI assistant at your side, and find three things worth telling a manager. Every step the AI suggested is checked and logged.
- Jupyter
- PostgreSQL
- Microsoft Copilot
Key skills- Messy data and how to fix it
- Exploratory analysis with AI as a pair
- Checking what the AI wrote
Week 3
Cleaning and exploring
Missing values, duplicates and types. Exploratory analysis with AI as a pair. Checking what the AI wrote.
You build: A cleaning log
Week 4
Project 2: exploration
A public dataset. Reproducible steps.
You build: An exploratory analysis with a cleaning log, published
Project 2 · the gate at week 4
Exploration
An exploratory analysis of a real public dataset with a cleaning log, published
You hand in
- Cleaning log
- Exploratory notebook or workbook
- Three findings with charts
The gate
Every cleaning step is logged and reproducible.
Dashboards
Part 3 · Weeks 5 to 6
Build a sales dashboard for the cafe chain's area manager in Power BI or Looker Studio. A test user who has never seen it must answer five questions from it without your help.
- PostgreSQL
- Microsoft Copilot
- ChatGPT
Key skills- Charts that answer one question each
- Power BI and Looker Studio
- Measures and filters
Week 5
Dashboards
Charts that answer one question each. Power BI and Looker Studio. Measures and filters.
You build: A first dashboard; squads form
Week 6
Project 3: the dashboard
User testing. Fixing what confused them.
You build: A dashboard a manager can use alone, deployed
Project 3 · the gate at week 6
The dashboard
A dashboard a manager can use without you in the room, deployed
You hand in
- Published dashboard
- Measure definitions
- User test notes and fixes
The gate
A test user answers five questions from it unaided.
Statistics that matter
Part 4 · Weeks 7 to 8
An online shop tested two checkout pages. Analyse the results, decide whether the difference is real, and recommend what to do, including what the data cannot tell you.
- Jupyter
- PostgreSQL
- Microsoft Copilot
Key skills- Averages, spread and outliers
- A/B tests and significance
- Correlation, causation and forecasting basics
Week 7
Statistics that matter
Averages, spread and outliers. A/B tests and significance. Correlation, causation and forecasting basics.
You build: An A/B test analysis
Week 8
Project 4: the experiment
The recommendation. Saying what the data cannot tell you.
You build: An A/B test analysis with a recommendation, published
Project 4 · the gate at week 8
The experiment
An A/B test analysis with a recommendation, published
You hand in
- Analysis workbook or notebook
- Significance check
- Written recommendation
The gate
The conclusion survives the instructor's challenge.
AI-assisted analysis
Part 5 · Weeks 9 to 10
Take a raw dataset from question to recorded presentation: clean it, analyse it with Python and an AI pair, build the charts and present a recommendation in ten minutes.
- Python
- pandas
- Jupyter
Key skills- Python and pandas with an AI pair
- Natural-language questions over data
- Verifying AI answers against the source
Week 9
AI-assisted analysis
Python and pandas with an AI pair. Natural-language questions over data. Verifying AI answers against the source.
You build: An analysis notebook
Week 10
Project 5 and the viva
Raw data to presentation. Defending a number to the raw rows.
You build: An end-to-end analysis with a recorded presentation; the viva
Project 5 · the gate at week 10
End to end
The capstone: an end-to-end analysis from raw data to a recorded presentation
You hand in
- Analysis repository
- Slides
- Recorded presentation
The gate
The viva: defend a number from the slide back to the raw rows.
Employer brief and hiring sprint
Part 6 · Weeks 11 to 12
A fictional charity that reports donations by hand each month gives your squad a scoped reporting problem. You deliver a cleaned dataset, a dashboard and a short findings report within the fortnight. If no partner brief is available, the instructor sets an equivalent one.
- PostgreSQL
- Microsoft Copilot
- ChatGPT
Key skills- A partner's analysis problem
- Demo day
- CV, portfolio, applications, mock interviews
Week 11
Employer brief
A real problem from a hiring partner, in squads. A partner's reporting or analysis problem. Working to someone else's definition of done.
You build: The employer brief in progress
Week 12
Hiring sprint
CV and portfolio built from graded work. Applications and follow-ups in the hiring plan. Mock interviews scored against the role. Demo day.
You build: Project 6 delivered; demo day
Project 6 · the gate at week 12
Employer brief
The employer brief shipped, and demo day
You hand in
- Scoped plan agreed with the owner
- Cleaned data and dashboard
- Findings report
- Demo day presentation
The gate
The brief's owner accepts the result.
What you can do by week 12.
Six published analyses and dashboards that show you can take a business question to an answer a manager acts on, using SQL, Power BI and AI assistants you have learned to check.
- 1
Turn a vague business question into a question data can answer.
- 2
Write SQL from SELECT to joins, grouping and window functions.
- 3
Clean messy data with a log anyone can rerun.
- 4
Build dashboards in Power BI or Looker Studio that a manager can use alone.
- 5
Run and read an A/B test and know when a difference is real.
- 6
Use Python and AI assistants for analysis, and verify every AI answer against the source.
- 7
Present a finding and defend each number back to the raw rows.
Roles this prepares you for
- Data analyst
- Business analyst
- Reporting analyst
- BI analyst (junior)
No placement rate is shown, because there are no graduates to count yet. The roles above are what the projects are built for.
Your record at week 12.
Every exercise and project is graded by Nova against a rubric you can read, and every grade is kept on one page an employer can open and run. This is what the programme writes to it.
- Graded, line by line
- Nova reads every submission against the brief and the rubric and returns a score, what you did well and what to fix.
- Six gates
- A block does not open until the previous project passes its gate. You always know where you are and what is next.
- A weekly 1-1
- Thirty minutes with your instructor, who has already read your code before the call.
- One page an employer can run
- Every grade, project and the viva recording at /verify. An employer opens it, runs the code and watches you defend it.
Record, Data Analyst with AI Bootcamp
Example
- Week 2Graded, gate signed
Answered in SQL
Every answer matches the withheld answer key
- Week 4Graded, gate signed
Exploration
Every cleaning step is logged and reproducible
- Week 6Graded, gate signed
The dashboard
A test user answers five questions from it unaided
- Week 8Graded, gate signed
The experiment
The conclusion survives the instructor's challenge
- Week 10Graded, gate signed
End to end
A viva: defend a number from the slide back to the raw rows
- Week 12Graded, gate signed
Employer brief
The brief's owner accepts the result
- Weeks 1 to 12Kept
Twelve 1-1 notes
What your instructor saw in your work each week, and what you agreed to do next.
- Week 12Kept
Your hiring plan and its outcome
Target roles, the gap map, applications, interviews and where you landed.
The entries, not the grades: those are yours to earn. The page lives at /verify and an employer needs no account to open it.
8 entries, twelve weeks. 10 spots are open.
Reserve my spotHow we help you find a job.
The last block is not curriculum. It is the hiring sprint, and the proof you built in the ten weeks before it.
- 1
Your hiring plan, from week 1
Six parts you and your instructor keep: target roles, the gap map from real postings, the proof to send, weekly actions, an interview log, the outcome. Read before every 1-1.
- 2
The hiring sprint
Weeks 11 and 12: CV, portfolio, applications, mock interviews, and demo day in front of hiring partners.
- 3
A record an employer can run
Your six deployed projects and the recorded viva on /verify. An employer opens it, runs the code and watches you defend it.
- 4
The career agent
Paste a real job posting at /career and it maps the role to your graded work and what to do next.
- 5
The roles directory
Every role we prepare people for, what it pays and what it asks, at /roles.
Questions people ask.
About Data Analyst with AI Bootcamp, answered from the plan on this page.
Related programmes
- Data Science Bootcamp · 12-week live bootcamp
- Analytics Engineer Bootcamp · 12-week live bootcamp
- Data Engineering with AI Bootcamp · 12-week live bootcamp
How long is the Data Analyst with AI Bootcamp?
12 weeks at about 15 hours a week. The weeks run as six two-week blocks; each block ends in a project you deploy and a gate you must pass before the next block opens.
Is the Data Analyst with AI Bootcamp live or self-paced?
Live. It is taught on Zoom by one instructor, with a 30-minute one-to-one every week. Nova, Square 1's AI tutor, grades every exercise and project between sessions against a rubric you can read.
When are the live sessions for the Data Analyst with AI Bootcamp?
Live sessions run on weekday evenings from 5:30 PM Sri Lanka and India time, with full-day sessions at weekends. That is 5:00 PM in Pakistan, 5:45 PM in Nepal and 6:00 PM in Bangladesh, so the sessions fit around a working day.
How much does the Data Analyst with AI Bootcamp cost?
A$319 for the founding cohort, paid once; the standard price is A$690. It is the same price in every country. Founding students keep their founding price on any second programme.
Who is the Data Analyst with AI Bootcamp for?
People who live in spreadsheets, or want to, and are changing career into data analysis. No code or SQL needed to start; you finish writing both with an AI pair and checking its work. Before you start: Comfortable with spreadsheets; no code or SQL needed.
What will I build in the Data Analyst with AI Bootcamp?
6 deployed projects: Answered in SQL, Exploration, The dashboard, The experiment, End to end and Employer brief. Each is graded against a published rubric and kept on a record an employer can open at /verify.
What skills does the Data Analyst with AI Bootcamp teach?
SQL, spreadsheets, Power BI, data cleaning, statistics, pandas, AI-assisted analysis and data storytelling. It prepares you for roles such as Data analyst, Business analyst, Reporting analyst and BI analyst (junior).
Does the Data Analyst with AI Bootcamp guarantee a job?
No. No placement rate is published because the first cohorts have not graduated. What you leave with is six deployed projects, a recorded defence of your code and a hiring plan worked through with your instructor, including a two-week hiring sprint at the end.
How do I join the Data Analyst with AI Bootcamp?
Reserve one of the ten spots on this page with your email. Spot holders hear the start date first, and nothing is charged before you confirm. The price on this page is in Australian dollars and is the same in every country.
10 spots. Hold one of them.
10 spots, one instructor, 12 weeks, six things you ship. Spot holders hear the start date first, and nothing is charged before you confirm.
- Six published analyses and dashboards
- A recorded viva
- Your record on /verify
About a minute. No account, no card, and nothing is charged until you confirm.