Start from what you can already do
Most data science course lists rank programs as if every reader starts from zero. In practice the right program depends on three things you already know about yourself: whether you have written code before, whether you are comfortable with statistics, and how many hours a week you can protect for several months.
This guide sorts options into three starting points and keeps to what each provider publishes: course count, estimated time, stated prerequisites, the math involved and the projects you finish with. If you are choosing between the two most common beginner certificates, our IBM Data Science vs Google Data Analytics comparison covers that decision in more depth, and our DataCamp vs Coursera guide covers short daily practice versus a long structured program.
- Beginner: no programming yet, and you want a guided route that ends with machine learning basics.
- Analyst: you already use spreadsheets, SQL or a BI tool and want statistics, Python and modeling on top.
- Developer: you already write code and want data libraries and machine learning without re-learning programming basics.
Programs side by side
Hours are provider estimates. Coursera states time as months at 10 hours a week, so a learner with 5 hours a week should roughly double the calendar time. Educative states total hours, which is easier to plan against a weekly budget: 57 hours at 6 hours a week is about 10 weeks.
| Program | Best starting point | Stated prerequisites | Math level | Projects | Time and cost listed |
|---|---|---|---|---|---|
| IBM Data Science Professional Certificate (Coursera) | Beginner | No prior programming; high school math helpful | Calculus and linear algebra are an asset for the last few courses but not required | Labs plus projects such as SQL on census and crime data, housing price regression, a dashboard and a loan classification; Applied Data Science Capstone | 12 courses, about 4 months at 10 hours a week; included with Coursera Plus ($59 a month or $399 a year) |
| Google Data Analytics Professional Certificate (Coursera) | Beginner aiming at analyst roles | None required | Not stated on the program page | Hands-on labs and a capstone case study | 9 courses, about 6 months at 10 hours a week; $49 a month in the US and Canada after a 7-day trial, with most learners paying under $300 by Coursera's estimate |
| Google Advanced Data Analytics Professional Certificate (Coursera) | Analyst | Designed for Google Data Analytics graduates or people with equivalent experience | Descriptive statistics, probability, sampling, hypothesis testing, linear and logistic regression | Applied learning project throughout and a capstone | 7 courses, about 6 months at 10 hours a week; included with Coursera Plus |
| Educative: Become a Data Scientist skill path | Developer | None listed | Not stated on the path page | Modules on NumPy and pandas, scikit-learn, TensorFlow and Keras, and model pipelines | 5 modules, 287 lessons, about 57 hours; part of the Educative Unlimited subscription, price not shown on the pages we checked |
| Educative: Become a Machine Learning Engineer skill path | Beginner or developer who wants ML depth | None listed; FAQ says it starts with Python from scratch | Regression, classification, clustering, neural networks | Capstone projects including image colorization and road sign recognition | 7 modules, 180 lessons, about 105 hours; Educative Unlimited subscription |
Beginner: choose the route that reaches the work you want
If you have never programmed, IBM Data Science is the beginner program in this list that goes furthest toward data science proper. Coursera lists Python, SQL and R, with Jupyter, pandas, NumPy, Matplotlib, Seaborn and scikit-learn, and machine learning topics including regression, classification and clustering. The page says high school math is helpful and that calculus and linear algebra help in the last few courses without being required.
Google Data Analytics is the better fit if your near-term goal is an analyst job rather than modeling. Coursera lists spreadsheets, SQL and Tableau among its tools; it takes longer on Coursera's estimate (about 6 months versus 4), and ends with a capstone case study rather than machine learning. Google designed its advanced certificate, below, for graduates of this one, so it can serve as a first step.
Skip both if you want a few minutes of practice a day on your phone rather than a weekly study block; the short-lesson subscriptions covered in our DataCamp vs Coursera guide suit that pattern better.
Analyst: add statistics and modeling, not another beginner course
Analysts often waste months repeating spreadsheet and SQL basics. Google Advanced Data Analytics is listed as an advanced program designed for graduates of Google Data Analytics or people with equivalent analytics experience, so it skips that ground. Its third course covers descriptive statistics, probability distributions, sampling and hypothesis testing; the fourth covers linear and logistic regression; the fifth covers supervised and unsupervised learning, decision trees and random forests. Tools listed are Python in Jupyter Notebook and Tableau.
The trade-off is pace. Coursera estimates about 6 months at 10 hours a week for 7 courses. If you already code in Python at work, a developer-style path may get you to modeling faster; if your statistics are rusty, the structured sequence is the safer choice.
- Good fit: you write SQL weekly, know what a pivot table is doing, and want to run regressions and explain them to stakeholders.
- Poor fit: you have not yet worked with real datasets; start with a beginner certificate instead.
Developer: use a code-first path
Developers usually need the data libraries and the modeling workflow, not another introduction to loops. Educative's Become a Data Scientist path lists five modules, 287 lessons and about 57 hours: getting started with NumPy, pandas and Beautiful Soup, an introductory guide to machine learning, data science with scikit-learn, deep learning with TensorFlow and Keras, and building scalable model pipelines.
The path page does not list statistics as a topic, so plan to fill that gap separately if hypothesis testing and regression interpretation matter in your role. Educative's Become a Machine Learning Engineer path is longer (about 105 hours, 180 lessons) and starts from Python basics, which makes it heavier than a working developer needs but a reasonable single path for a motivated beginner.
Educative did not show a price on the pricing and Unlimited pages we checked. Its trial page advertises a 21-day free trial, and its pricing page says that if you cancel, access continues to the end of the paid period and it will not issue a refund. Check the price shown at checkout and plan to finish within the period you pay for.
Total cost: three worked examples
The annual Coursera Plus plan only saves money if you will keep studying for most of the year; Coursera lists a 14-day money-back guarantee on the annual plan and a 7-day free trial on the monthly plan. Coursera also notes financial aid is available on the IBM program page.
| Plan | How you pay | Estimated total |
|---|---|---|
| IBM Data Science in 4 months | Coursera Plus monthly at $59 | About $236 (4 x $59) |
| Google Data Analytics in 6 months | Program subscription at $49 a month (US and Canada) | About $294 (6 x $49), consistent with Coursera's under-$300 estimate |
| Google Data Analytics then Advanced Data Analytics over 12 months | Coursera Plus annual at $399 versus monthly at $59 | $399 annual versus $708 monthly (12 x $59) |
| Code-first practice alongside a certificate | DataCamp Premium listed at $14 a month billed annually | About $168 a year (12 x $14) if the listed rate holds; confirm the total at checkout |
Checklist before you pay
- Write down your starting point honestly: coding experience, statistics comfort and weekly hours.
- Open the syllabus and confirm the last two courses cover the work you want, such as modeling, dashboards or pipelines.
- Check the math stated on the program page and refresh it first if needed.
- Count months at your real weekly hours, then multiply by the monthly price.
- Confirm the program shows as included before relying on a Coursera Plus subscription.
- Plan one project on data you chose yourself after the capstone, so your portfolio is not identical to every other graduate's.
Questions before you decide
Which online data science course is best for a complete beginner?
For a beginner who wants to reach machine learning, IBM Data Science on Coursera requires no programming background, lists high school math as helpful, and runs 12 courses over about 4 months at 10 hours a week. Google Data Analytics suits beginners aiming at analyst roles instead.
How much math do I need for a data science certificate?
The IBM program says high school math is helpful and that calculus and linear algebra are an asset for the last few courses but not required. Google Advanced Data Analytics teaches statistics, probability, hypothesis testing and regression inside the program.
Is Google Advanced Data Analytics suitable if I have never done analytics?
Google describes it as an advanced program designed for graduates of the Google Data Analytics Certificate or people with equivalent data analytics experience, so beginners should start with a beginner program first.
What is a good data science course for software developers?
A code-first path avoids repeating programming basics. Educative's Become a Data Scientist path lists 5 modules and about 57 hours covering pandas, scikit-learn, TensorFlow and Keras and model pipelines; add statistics separately because the path does not list it.
Is Coursera Plus cheaper than paying for one data science certificate?
For one program finished in a few months, paying monthly is usually enough: IBM Data Science at about 4 months on Coursera Plus monthly is about $236. If you will study for most of a year across two programs, the $399 annual plan costs less than 12 months at $59.
Sources & verification
Product details and prices can change. Check the linked provider before buying.
- Coursera: IBM Data Science Professional Certificate Accessed 30 Oct 2026
- Coursera: Google Data Analytics Professional Certificate Accessed 30 Oct 2026
- Coursera: Google Advanced Data Analytics Professional Certificate Accessed 30 Oct 2026
- Coursera Plus pricing Accessed 30 Oct 2026
- Educative: Become a Data Scientist skill path Accessed 30 Oct 2026
- Educative: Become a Machine Learning Engineer skill path Accessed 30 Oct 2026
- Educative: pricing and cancellation terms Accessed 30 Oct 2026
- Educative: 21-day free trial page Accessed 30 Oct 2026
- DataCamp pricing Accessed 30 Oct 2026
Sources link directly to providers. Product buttons may use separately labeled affiliate links. Read our disclosure.