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12 monthsBeginner friendly

Build models that predict, classify and power AI.

Learn the programming, maths and statistics behind data science, then move into machine learning, AI and prompt engineering with real projects.

Who this program is for

Career changers with a numbers background

From finance, engineering, science, teaching maths or research who want to move into data science and AI.

Data analysts ready to level up

Analysts who know Excel, SQL or Power BI and want to build predictive models and machine learning systems.

Developers moving into AI

Programmers who want the statistics, modelling and machine learning skills behind modern AI products.

What you will learn

  • Write Python to load, clean, transform and explore data.

  • Apply the maths behind data science: linear algebra, calculus and probability, explained for practical use.

  • Use statistics to test hypotheses, measure uncertainty and draw sound conclusions.

  • Build and evaluate models for prediction and classification.

  • Train and tune machine learning models with libraries such as scikit-learn.

  • Understand how neural networks and modern AI models work, and when to use them.

  • Use prompt engineering to get reliable results from large language models in data workflows.

  • Communicate model results, limits and risks clearly to non-technical audiences.

What you will build

Fellows finish with five portfolio pieces they can show employers.

Project 01

Clean and explore a real dataset in Python and present the key patterns you find.

Skills shown

  • Python
  • pandas
  • Data visualisation

Skills you'll learn

  • Python programming
  • Data wrangling
  • Linear algebra
  • Calculus
  • Probability
  • Statistics
  • Hypothesis testing
  • Regression and classification
  • Machine learning
  • Deep learning concepts
  • Model evaluation
  • Prompt engineering
  • Communicating results
  • Python
  • Jupyter Notebook
  • pandas
  • NumPy
  • Matplotlib
  • scikit-learn
  • SQL
  • Git
  • Large language models

Program outline

  • 8

    courses

  • 5

    projects

  • 12

    months

  1. 01

    Programming & Tools

    Python, Jupyter, Git and the core tools used in data science work.

  2. 02

    Maths & Statistics

    Descriptive and inferential statistics, probability and hypothesis testing.

  3. 03

    Analysis and Modelling

    Exploratory analysis, regression and classification models, and model evaluation.

  4. 04

    Mathematical Foundations

    Linear algebra and calculus needed to understand how models learn.

  5. 05

    Programming & Data Foundations

    Data structures, data cleaning and working with databases in Python and SQL.

  6. 06

    Core Artificial Intelligence & Machine Learning

    Supervised and unsupervised learning, neural networks and model tuning.

  7. 07

    Advanced Topics and Specialisation

    Choose a focus area such as natural language processing, computer vision or time series.

  8. 08

    Prompt Engineering

    Designing prompts and workflows that get reliable results from large language models.

Certification pathway

The program prepares fellows for these industry certifications. Exams are taken with the certifying body, and exam fees are paid separately.

In data science, employers weigh a portfolio of real models and analyses more heavily than certifications. The five projects are designed to provide that portfolio.

Prerequisites and requirements

  • Prior experience

    No coding experience is needed. Comfort with secondary-school maths helps, as the program builds on it quickly.

  • Language

    Good written and spoken English.

  • Equipment

    A laptop or desktop computer with at least 8 GB of memory and a reliable internet connection. A phone or tablet alone is not enough for the tools used.

How learning works at FairChild

  • Fully online and self-paced

    Study from anywhere, on your own schedule, through the FairChild learning portal.

  • Learn by doing

    Every course ends with practical work, and the projects build a portfolio employers can review.

  • Choose your pace

    Finish in 6 months on the accelerated track or spread the work over 12 months.

  • Join the fellows community

    Connect with other FairChild fellows working through the same courses.

  • Add mentorship and career support

    Pair the program with Guided Mentorship & Career Development, or join through the FairChild Fellowship, for interview preparation and career coaching.

Career outcomes

Graduates are prepared to apply for roles such as:

  • Junior Data Scientist

  • Machine Learning Engineer (junior)

  • AI Analyst

  • Data Analyst

  • Business Intelligence Analyst

  • Prompt Engineer

Only The Best Brains Teach at FairChild Institute

Our mentors aren't just teachers. They're practitioners solving real problems with data every day.

CRM Platform & Projects

Oluwaseyi Allison

I work in CRM every day. I teach project delivery from the field, not the textbook.

Data Analytics & Business Intelligence

Malik Pelumi Bello

Data and BI are my world. I teach you to make numbers tell a story.

Business analysis

Baba Nureni-Yusuf

BA is where I made my name. I teach the craft and the interview game.

Agile and Scrum Mastery

Babajide Onabajo

Agile is how I run teams. I teach Scrum without the jargon.

Salesforce Service Cloud with Projects

Debo Fafore

I build on Service Cloud. I teach solutions that survive go-live.

Salesforce Essentials

Samson Bavo

Salesforce got me in the door. I teach the essentials that still do.

Salesforce Sales Cloud

Sophie Mokah

I live in Sales Cloud. I teach setups that help teams sell.

Data Analytics & Business Intelligence

Qahhar Okenla

BI is my thing. I teach dashboards people actually open.

Salesforce Experience Cloud

Ogenna Odebatu

Experience Cloud is my space. I teach portals built for real users.

Triple Play Course B - Salesforce Flow Automation Implementations

Niloy Debnath

Flow is what I do. I teach automations that work on day one.

Triple Play Course A - 8+ Salesforce Project Implementation

Oladipo Ojo

8+ projects in. I teach Salesforce how it's done on the job.

Triple Play Course C - Salesforce Admin Platforms Implementations

Olanrewaju Badiru (Ola B)

Admin platforms are my lane. I teach configs built for production.

CRM Platform & Projects

Oluwaseyi Allison

I work in CRM every day. I teach project delivery from the field, not the textbook.

Data Analytics & Business Intelligence

Malik Pelumi Bello

Data and BI are my world. I teach you to make numbers tell a story.

Business analysis

Baba Nureni-Yusuf

BA is where I made my name. I teach the craft and the interview game.

Agile and Scrum Mastery

Babajide Onabajo

Agile is how I run teams. I teach Scrum without the jargon.

Salesforce Service Cloud with Projects

Debo Fafore

I build on Service Cloud. I teach solutions that survive go-live.

Salesforce Essentials

Samson Bavo

Salesforce got me in the door. I teach the essentials that still do.

Salesforce Sales Cloud

Sophie Mokah

I live in Sales Cloud. I teach setups that help teams sell.

Data Analytics & Business Intelligence

Qahhar Okenla

BI is my thing. I teach dashboards people actually open.

Salesforce Experience Cloud

Ogenna Odebatu

Experience Cloud is my space. I teach portals built for real users.

Triple Play Course B - Salesforce Flow Automation Implementations

Niloy Debnath

Flow is what I do. I teach automations that work on day one.

Triple Play Course A - 8+ Salesforce Project Implementation

Oladipo Ojo

8+ projects in. I teach Salesforce how it's done on the job.

Triple Play Course C - Salesforce Admin Platforms Implementations

Olanrewaju Badiru (Ola B)

Admin platforms are my lane. I teach configs built for production.

CRM Platform & Projects

Oluwaseyi Allison

I work in CRM every day. I teach project delivery from the field, not the textbook.

Data Analytics & Business Intelligence

Malik Pelumi Bello

Data and BI are my world. I teach you to make numbers tell a story.

Business analysis

Baba Nureni-Yusuf

BA is where I made my name. I teach the craft and the interview game.

Agile and Scrum Mastery

Babajide Onabajo

Agile is how I run teams. I teach Scrum without the jargon.

Salesforce Service Cloud with Projects

Debo Fafore

I build on Service Cloud. I teach solutions that survive go-live.

Salesforce Essentials

Samson Bavo

Salesforce got me in the door. I teach the essentials that still do.

Salesforce Sales Cloud

Sophie Mokah

I live in Sales Cloud. I teach setups that help teams sell.

Data Analytics & Business Intelligence

Qahhar Okenla

BI is my thing. I teach dashboards people actually open.

Salesforce Experience Cloud

Ogenna Odebatu

Experience Cloud is my space. I teach portals built for real users.

Triple Play Course B - Salesforce Flow Automation Implementations

Niloy Debnath

Flow is what I do. I teach automations that work on day one.

Triple Play Course A - 8+ Salesforce Project Implementation

Oladipo Ojo

8+ projects in. I teach Salesforce how it's done on the job.

Triple Play Course C - Salesforce Admin Platforms Implementations

Olanrewaju Badiru (Ola B)

Admin platforms are my lane. I teach configs built for production.

FAQ

No. Every program starts with the basics and builds up step by step.

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