Data Science diploma
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Become a job-ready data scientist from scratch

This structured diploma takes you from zero data experience to a portfolio of real projects — covering Python, SQL, statistics, and machine learning the way employers actually use them. No advanced math degree required. No hand-waving. Just rigorous, practical training built for career changers and ambitious professionals.

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Data Science diploma

I don't want you to finish this program able to talk about data science — I want you to be able to do it.— Renstay

What you'll learn

What you'll be able to do

  • Write clean, production-style Python code for data wrangling, analysis, and visualization using pandas, NumPy, and Matplotlib
  • Apply core statistical concepts — distributions, hypothesis testing, and regression — to draw defensible conclusions from real datasets
  • Build, train, and evaluate supervised and unsupervised machine learning models using scikit-learn
  • Design and execute a full data science project lifecycle: from problem framing and data collection through modelling and stakeholder-ready reporting
  • Query, join, and aggregate data confidently using SQL across relational databases
  • Assemble a portfolio of at least three capstone projects that demonstrate job-ready skills to employers

How it works

A school that adapts to you

This isn't a set of static videos. Every lesson is generated live and tuned to where you actually are.

We learn your level

A quick placement check tailors your starting point so you're never bored or lost.

Lessons adapt as you go

Each lesson is written for your pace and your goal, adjusting as your skills grow.

Your AI coach keeps you moving

Checkpoints, feedback, and gentle nudges turn progress into a real result.

The curriculum

What's inside your school

6 modules · 31 lessons

1

Data Foundations & the Data Science Workflow

Builds the mental models and tooling setup every data scientist needs before writing a single line of code.

  • 1.1What Data Scientists Actually DoIncluded
  • 1.2Setting Up Your Data Science EnvironmentIncluded
  • 1.3Types of Data & How to Think About ThemIncluded
  • 1.4Your First Exploratory Data AnalysisIncluded
2

Python for Data Science

Develops practical, production-style Python skills — from core syntax through pandas, NumPy, and Matplotlib — on real datasets.

  • 2.1Python Essentials for Data WorkIncluded
  • 2.2Data Wrangling with pandasIncluded
  • 2.3Numerical Computing with NumPyIncluded
  • 2.4Data Visualization with Matplotlib & SeabornIncluded
  • 2.5Writing Clean, Reusable Python CodeIncluded
3

SQL & Data Retrieval

Gives you confident, hands-on SQL skills to query, join, and aggregate data from relational databases.

  • 3.1Relational Databases & How SQL WorksIncluded
  • 3.2Querying & Filtering DataIncluded
  • 3.3Joining Tables & Combining DatasetsIncluded
  • 3.4Aggregation, Grouping & Window FunctionsIncluded
  • 3.5SQL in Python: Connecting Databases to Your WorkflowIncluded
4

Statistics for Data Science

Builds the statistical intuition and applied skills needed to draw defensible, evidence-based conclusions from data.

  • 4.1Descriptive Statistics & DistributionsIncluded
  • 4.2Probability EssentialsIncluded
  • 4.3Hypothesis Testing & p-ValuesIncluded
  • 4.4Correlation & Simple Linear RegressionIncluded
  • 4.5Multiple Regression & Model AssumptionsIncluded
5

Machine Learning

Covers the full supervised and unsupervised machine learning toolkit — from theory to evaluated, production-ready models using scikit-learn.

  • 5.1The Machine Learning Mindset: Bias, Variance & ValidationIncluded
  • 5.2Supervised Learning: ClassificationIncluded
  • 5.3Supervised Learning: Regression ModelsIncluded
  • 5.4Model Evaluation & Hyperparameter TuningIncluded
  • 5.5Unsupervised Learning: Clustering & Dimensionality ReductionIncluded
  • 5.6Introduction to Natural Language ProcessingIncluded
6

Capstone Projects & Career Readiness

Guides you through three end-to-end capstone projects and the professional skills needed to land your first data science role.

  • 6.1The Data Science Project LifecycleIncluded
  • 6.2Capstone 1: Exploratory & SQL Analytics ProjectIncluded
  • 6.3Capstone 2: Predictive Modelling ProjectIncluded
  • 6.4Capstone 3: Open-Ended Data Science ProjectIncluded
  • 6.5Communicating Results to StakeholdersIncluded
  • 6.6Building Your Portfolio, CV & Interview PreparationIncluded

Who it's for

Is this you?

Career changers

You're leaving a non-technical field and need a structured, credible path into data science that takes you seriously from day one.

Data analysts levelling up

You're comfortable with spreadsheets and dashboards but want the machine learning, Python, and statistical fluency to move into a data scientist role.

Recent graduates

Your degree gave you some quantitative grounding but not the hands-on, employer-ready skill set — this diploma fills that gap with real projects and a portfolio.

Self-taught coders

You can write Python but your statistics and machine learning knowledge has gaps — this program gives you the rigorous foundation to back up your coding ability.

Working professionals

You're employed and busy, but serious about upskilling — the program's structured, self-paced design lets you build toward a career move without quitting your job.

Business & domain experts

You understand the industry deeply and want to add data science skills so you can lead data-informed decisions rather than just interpret them.

Questions

Frequently asked

Your teacher

A note from your teacher

Renstay

Renstay

If you're reading this, there's a good chance you already know you want to work in data science — you just haven't found a path that takes you seriously.

Maybe you've tried a few online tutorials and ended up with a collection of disconnected notebooks but no clear picture of how it all fits together. Maybe you're an analyst who can build a great dashboard but feels out of your depth when the conversation turns to machine learning or statistical inference. Maybe you're switching careers entirely and the sheer volume of things people say you "need to learn" has made it hard to know where to start. I've seen all of these situations, and I built this program for exactly that moment.

The Data Science Diploma is structured the way I wish data science education had been structured when I was learning: start with the workflow and the mindset, build genuine fluency in Python and SQL as integrated tools, develop statistical thinking carefully enough that you can actually defend your conclusions, and then apply all of it to machine learning with the rigour it deserves. No skipping the hard parts. No hand-waving through the concepts that matter. And no ending the program with a certificate that isn't backed by real, demonstrable work.

What I care about most in this program is that you finish it able to do the job — not just talk about it. That's why the curriculum closes with three capstone projects, stakeholder communication, and practical interview preparation. A portfolio that shows your thinking is worth more than any credential on its own, and we build that portfolio together, deliberately, across every section of this program.

This isn't a shortcut. It's a straight line — clear, rigorous, and encouraging the whole way through. If you're ready to do the work, I'm ready to walk through it with you. Let's get started.

— Renstay

Start your journey today

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  • 6 modules, 31 lessons
  • AI-adaptive lessons tuned to your level
  • Quizzes & checkpoints to lock in progress
  • Your own AI learning coach
  • Learn on any device, at your pace
  • Full access for as long as you're subscribed