Subjects / Python Fundamentals

The foundations of
Python Fundamentals.

A practical introduction to Python for finance and consulting professionals. Seven courses and projects in a single Python Basics track, from first principles through functions, conditionality and loops, NumPy, Pandas and MatPlotLib for analysis, data preparation and connecting to live data via APIs.

Analyst working at a laptop in a modern office, learning Python fundamentals for finance data analysis
Curriculum
7 courses & projects
Total Learning
~15.5 hours
Level
Beginner to Intermediate
Credits
14.5 CPE/CPD
1M+ learners trained 4.7/5 average G2 rating 80% course completion rate
Trusted by finance and consulting teams at
Why Python?

The first programming language
finance and consulting analysts learn.

Python has quietly become the second tool every finance and consulting analyst is expected to know after Excel. Readable syntax, a huge data ecosystem, and a clear on‑ramp from spreadsheet thinking to programming. This subject takes a complete beginner from first principles through to live data pipelines.

See the learning outcomes

Beginner to applied in seven items

Open a Python notebook for the first time in week one. Connect to live API data and clean it for analysis by the end. No prior coding experience required to start.

Two workplace projects, not just lectures

Workplace cases on vineyard frost prediction with a live weather API and ingredient data cleaning for a meal kit company. Skills practised on the kind of problems Python actually shows up to solve.

The data ecosystem, in detail

NumPy for advanced calculations, Pandas for reading and manipulating datasets, MatPlotLib for visualisation. The three libraries every Python analyst leans on, taught with finance and consulting datasets.

Credentials that stand up

Every milestone is independently accredited by CPD, CPE and NASBA, so what learners earn here counts towards continuing professional development.

Learning Outcomes

What learners will be able to do
by the end of the program.

Every outcome is mapped to a specific lesson and assessed through scenario‑based exercises. Learners walk away with practical Python skills they can apply on the next analysis, data pipeline or research task.

Read and write Python with confidence

Get the foundations: variables, types, syntax and the principles behind why Python looks the way it does. The basis of every script that follows.

Python Basics

Use functions, conditionals and loops

The control flow that turns short scripts into useful tools. Functions for reusability, conditionals for decision logic, loops for repetition at scale.

Python Basics

Analyse data with NumPy, Pandas and MatPlotLib

The three libraries every analyst reaches for. NumPy for advanced calculations, Pandas for manipulating tabular data, MatPlotLib for visualising the result.

Python Basics

Prepare data the analysis can trust

Unions, joins and aggregation, plus cleaning techniques for nulls, duplicates, false types and the messy reality of real datasets.

Python Basics

Connect to live data and APIs

Pull csv files hosted online, scrape web‑page tables, and connect to live APIs. Move beyond static spreadsheets to data that updates itself.

Python Basics

Apply Python to real workplace projects

Build a frost‑risk predictor for a winemaker using a live weather API. Clean nutritional data from multiple ingredient suppliers for a meal kit company. Skills used the same week they're learned.

Workplace Projects
The Curriculum

Seven courses and projects,
in the order learners take them.

Python Fundamentals is a single track called Python Basics. Seven items, designed to be taken in order. Roughly 15 hours end to end, with two workplace projects at the close.

Python Basics · 1 of 7Beginner

Python Fundamentals

Get a grasp of the basics of Python. The principles behind the language, what Python is, why it's so popular, and how to start writing code that runs.

2.5 hours 2.0 CPE/CPD
Python Basics · 2 of 7Intermediate

Functions, Conditionality and Loops

The control flow that takes short scripts into real tools. Functions for reusability, conditional statements for decision logic, and loops for repetition at scale.

3 hours 2.5 CPE/CPD
Python Basics · 3 of 7Intermediate

Storing, Transforming and Visualizing Data

The three libraries every Python analyst leans on. NumPy for advanced calculations, Pandas for reading and manipulating datasets, MatPlotLib for visualising the result.

3 hours 2.5 CPE/CPD
Python Basics · 4 of 7Intermediate

Data Preparation

Unions, joins and aggregation, plus cleaning techniques for nulls, duplicates, false data types and the messy reality of real datasets. The unglamorous work that makes everything downstream possible.

2.5 hours 3.0 CPE/CPD
Python Basics · 5 of 7Intermediate

Connecting to Live Data

Use Python to connect to live data sources. Download csv files hosted online, pull web‑page tables into Python, and connect to data exposed through APIs.

1.5 hours 1.5 CPE/CPD
Python Basics · 6 of 7IntermediateProject

Predict frost risk in vineyards using live data

A workplace project. Help a winemaker automate frost‑risk prediction by using Python to connect to live weather data, removing the manual step that currently delays the alert.

1.5 hours 1.5 CPE/CPD
Python Basics · 7 of 7IntermediateProject

Clean nutritional data from ingredient suppliers

A workplace project. Help a homemade meal kit company unify nutritional data from multiple online suppliers, then apply data cleaning best practices to produce a trustworthy, error‑free dataset.

1.5 hours 1.5 CPE/CPD
7
Courses & Projects
~15.5h
Total Learning
14.5
CPE / CPD Credits
100%
Self‑paced

Python Fundamentals leads naturally into Machine Learning in Python. Together they sit inside Kubicle's wider library, alongside subjects on Excel, Power BI, Tableau, SQL, Alteryx, AI and financial modelling.

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The Kubicle Learning Experience

Why learners actually finish
and apply what they learn.

Kubicle is engineered around a single goal: practical skills that get used. Every design choice, from lesson length to assessment style, is made to keep finance and consulting professionals engaged and to translate watch time into measurable outcomes at their desk.

Bite‑sized lessons

Most lessons run 5–10 minutes. Designed to fit between meetings, not block out a Tuesday afternoon. The result: 80% completion vs. a 7% industry benchmark.

Real workplace projects

Learners build a portfolio of project work, not a list of completion certificates. Skills practised on the kind of data they'll see on a real engagement.

Independently accredited

CPD, CPE and NASBA accreditation means credits count toward continuing professional development. Certificates are shareable on LinkedIn the moment they're earned.

Modular and stackable

Every course slots into a wider learning path. Pair Python Fundamentals with Machine Learning in Python, SQL or Data Literacy as the team's needs grow.

Manager‑level visibility

Engagement and skill‑gain dashboards from day one. Leaders see exactly where capability is building and where it isn't, by team and by role.

Always current

Modules are refreshed continuously to reflect new tools, regulation and the rise of generative AI. You never pay for material that's gone stale.

Credibility

Why finance and consulting leaders
choose Kubicle, with confidence.

The numbers, the accreditations and the customer outcomes are all on the table, so L&D, Early Careers and Practice Leads can build the business case fast.

Learners trained
1,000,000+
G2 average rating
4.7/5
Course completion
80% · 11x industry
Years in the market
10+ years
Accreditations
CPD · CPE · NASBA
Security
ISO 27001 · GDPR
Independently Accredited

Credentials that count toward CPD.

Every course awards CPE / CPD credits via NASBA‑recognised accreditation, so time spent here counts on a CV and on the team's compliance log.

CPD, CPE, NASBA accreditation logos
Outcomes, Not Hours Watched

Skills learners apply
the same week they learn them.

These aren't aspirational numbers. They are the measured outcomes Kubicle clients report after a typical rollout, with manager‑level dashboards from day one so practice and L&D leaders can see exactly where capability is building.

The Headline

An hour back, every week.

More than 60% of Kubicle learners report saving between 30 minutes and 2 hours every week thanks to sharper data skills. Time redirected to higher-value work, and a measurable productivity dividend at the team level.

60%+
save 30 mins–2 hours every week
Skills That Stick

Used every single day.

45% of Kubicle learners apply newly‑acquired skills daily, the difference between training that's watched and training that's worked.

45%
apply newly‑learned skills daily in their roles
Sharper Communication

Stronger numbers, stronger narratives.

75%+ of learners report measurable gains in both data analysis and the communication skills needed to make insights land with stakeholders.

75%+
gain stronger analysis and communication skills
What Our Partners Say
TotalEnergies
Kubicle was easy to set up and our learners were quickly engaged. It's effectively closed our skill gap, especially in tools like Excel and data processing, and the real-time progress tracking and certifications are why we'll keep using it.

Validated Reviewer
TotalEnergies

Frequently Asked

Answers for the questions we hear most.

Still have a question? Send an enquiry and one of our learning advisors will walk you through it within a business day.

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Who is this subject designed for? +

Finance and consulting analysts, associates and managers who want to add Python to their toolkit. The seven items are sequenced from a complete beginner through to live data pipelines, with no prior coding experience required to start.

How much time does it take? +

Roughly 15.5 hours of content across 7 courses and projects, worth 14.5 CPE/CPD credits. Most learners complete the full subject in three to five weeks of casual study.

Do I need a coding background? +

No. Course 1 starts from first principles, including what Python is, why it's used, and how to write code that runs. Designed for finance and consulting professionals, not software developers.

Does this cover NumPy, Pandas and MatPlotLib? +

Yes. Storing, Transforming and Visualizing Data is a dedicated course on all three: NumPy for advanced calculations, Pandas for reading and manipulating datasets, and MatPlotLib for visualising the result.

What happens after Python Fundamentals? +

The natural next step is Machine Learning in Python, which builds on this subject to cover regression, decision trees, k‑means clustering, feature engineering and advanced classification. Both subjects sit inside Kubicle's wider data and AI library.

Are the credentials accredited? +

Yes. Kubicle credentials are independently accredited by CPD, CPE and NASBA. Every course and project awards CPE/CPD credits that learners can apply toward continuing professional development. Certificates are shareable on LinkedIn the moment they're issued.

Will it integrate with our LMS and SSO? +

Yes. Kubicle offers off‑the‑shelf integrations with leading LMS providers and the engineering team will build a custom integration for any other system you run. SSO is supported across the board, and a Reporting API exposes engagement and completion data to your dashboards.

How is Kubicle secured? +

Kubicle is ISO 27001 certified, GDPR‑compliant, and undergoes regular third‑party penetration testing. Granular roles, SSO and audit logging are built in.

Make an Enquiry

Give your team the Python skills they don't have today.

Send a short enquiry and a learning advisor will come back within one business day with a tailored recommendation: a curriculum mapped to your team's roles, a sample pathway through Python (and any related subjects), and a quote you can take to budget. Built for teams of 5 to 100, deployable in days.

Tailored curriculum recommendation for your team Sample learner pathway by role Volume-based quote, no obligation Reply within one business day
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