cd ~/programs/data-analytics
Data Analytics
Learn to turn messy data into a decision someone can act on.
SQL first, then Python, statistics and dashboards: the working analyst's toolkit, taught through messy real-world datasets instead of clean textbook ones.
- 14 wks full-time
- 24 wks part-time
- from $7,900
- live online
time --honest
The hours, honestly
Both tracks cover the same units with the same instructors. Pick the one you can keep up for the whole program, not the one you hope to keep up.
~40 hrs / week
Full-time, 14 weeks
- Live sessions
- Mon to Fri, 11am to 5pm Eastern (8am to 2pm Pacific), with breaks
- Live hours
- 30 a week
- Project work
- About 10 hours a week, on your own time
- Working?
- Not compatible with a job. Plan your money for the full program plus a job search.
~16 hrs / week
Part-time, 24 weeks
- Live sessions
- Tue and Thu, 7pm to 10pm, plus Saturday 10am to 3pm (Eastern or Pacific cohorts)
- Live hours
- 11 a week
- Project work
- About 5 hours a week, on your own time
- Working?
- Built around a full-time job. Expect tired evenings, especially in checkpoint weeks.
cat syllabus --phases
What you'll learn, phase by phase
-
foundations · week 1
- The analyst's mindset and spreadsheets
-
sql · weeks 2 to 3
- SQL fluency
- Dirty data and window functions
-
python · weeks 4 to 5
- Python for analysts
- pandas in practice
-
statistics · weeks 6 to 7
- Statistics I: describing data
- Statistics II: testing claims
-
communication · weeks 8 to 9
- Visualization and data storytelling
- BI dashboards and metrics
-
modeling · week 10
- Intro to modeling
-
infrastructure · week 11
- Data infrastructure for analysts
-
capstone · weeks 12 to 13
- Capstone definition and sourcing
- Capstone build and review
-
careers · week 14
- Demo day and career sprint
What you'll work in
- SQL (PostgreSQL)
- Python & pandas
- Jupyter notebooks
- Statistics & A/B testing
- BI dashboards
- dbt-style transforms
- Spreadsheet modeling
The capstone
An end-to-end analysis of a real public dataset: sourced, cleaned, modeled, charted and defended as a written memo plus a live dashboard.
Before day 1
Comfort with spreadsheets helps. No code required; the free 12-hour prep course covers setup and SQL basics.
Marcus Webb
Lead Instructor, Data Analytics
SQL-first pragmatist. Every dataset in his course is genuinely messy, because clean data is a textbook fiction, and every analysis ends in a memo someone could actually act on.
Meet all instructorsgrep data-analytics outcomes-2025.csv
example figuresWhere 2025 grads ended up
Roles that graduates of this program were hired into:
- Data analyst
- Business intelligence analyst
- Operations analyst
- Marketing or product analyst
- 25th pct
- $54,000
- Median
- $62,000
- 75th pct
- $73,500
reported by 46 grads employed in-field. base pay before tax.
northpath pricing --program data-analytics
What it costs, every plan in full
A $250 seat deposit reserves your cohort on any plan and counts toward these totals. It is not on top of them.
Pay upfront
$7,900
total you pay
One payment before day 1. $500 less than the $8,400 list price.
Monthly installments
$8,550
total you pay
6 payments of $1,425, first at enrollment. No interest; the $150 plan fee is inside the total.
Deferred tuition
$11,880
total you pay
$0 during the program, then 36 payments of $330 starting 3 months after graduation. $3,980 more than upfront, owed whether or not you're hired.
Deferred tuition, every term
- The printed total is a hard cap. It never rises with your salary, and there is no interest on top.
- 36 equal monthly payments, starting 3 months after graduation.
- You owe the payments whether or not you get a job. That is the trade for paying nothing up front.
- Pay it off early at any time with no fee. You pay only what is left of the printed total.
- Hardship pause: up to 6 months in total if you lose income. The total does not change.
For this program the cap is $11,880. We don't offer income-share agreements; here's how one compares.
Refunds, in plain words
- Weeks 1 and 2
- Leave for a full refund, deposit included. No questions asked. A deferred plan is cancelled and you owe nothing.
- Weeks 3 to 6
- You get back the share of tuition for the weeks you won't attend. On a deferred plan, you owe only the share for the weeks you did attend. Or pause once and rejoin a later cohort at no charge.
- After week 6
- Tuition is committed and there is no refund. On a deferred plan, the full printed total is owed. We say this in full-size type because it's the clause that matters.
Example: you pay $7,900 upfront for the 14-week full-time track and leave after week 4. You get back 10 of 14 weeks: $5,643.
Is it a fit?
// a good fit if
- You already live in spreadsheets and want the next set of tools
- You enjoy asking why a number moved, not just reporting it
- You can write a clear paragraph, because analysts are paid to explain
// probably not a fit if
- You want to build machine learning models; this is an analyst program
- You dislike writing; every analysis ends in a memo
- You expect a data scientist's salary from an entry-level analyst role
Upcoming cohorts
- Nov 16, 2026 full-time
- Dec 1, 2026 part-time
- Feb 1, 2027 full-time
rolling admissions. no "3 seats left" theatre.
Apply to Data AnalyticsQuestions about Data Analytics
Do I need to be good at math?
You need arithmetic and comfort with percentages. Statistics is taught from scratch in weeks 6 and 7, with worked examples before any formulas.
Which tools do employers actually ask for?
SQL first, by a wide margin, then a spreadsheet tool, then a BI dashboard tool. Python is a strong plus. That's why the program is ordered the way it is.
Are the datasets real?
Yes. Every case study uses a public dataset with real gaps, duplicates and odd values, because cleaning data is most of the job.
More answers on the FAQ page, including refunds, schedules and payment plans.
northpath --apply
Start with a conversation.
Applying to Data Analytics takes about 20 minutes and commits you to nothing. A person replies within 2 business days, and you can audit one live session before you decide.