Data Science
The Data Science Skills Bootcamp combines fundamental data principles with practical applications in machine learning and data processing. It is designed to help you build practical skills in data science, while developing strong foundations in data literacy, responsible data handling, and applied machine learning.
Course Overview
- 1 day a week, 14 weeks
- Online Delivery
- Fully Funded (subject to eligibility)
- No prior experience required
- BCS Foundation Award in Data Visualisation (BCS)
- Career Support
Across this programme, you will explore how organisations use data to support evidence-based decisions, how to store and protect data responsibly, and how to communicate insights clearly. You will then build on core cloud and data concepts through a vendor pathway, subject to prior experience and attainment, before developing hands-on skills in Azure Machine Learning. You will complete a capstone project that brings your learning together into an end-to-end analytics and machine learning workflow, supported by structured employability workshops to help you progress into work, further learning, self-employment, or a career change.
By the end, you will have a clearer understanding of how data science projects are structured, how models are trained and deployed, and how to present your skills with confidence to employers.
Why Choose an Data Science Bootcamp?
Employers increasingly need people who can work with data to generate insight, support planning, and build solutions that scale. Data science is not only about models and code, it’s also about understanding the business problem, preparing data, evaluating outcomes, and communicating results clearly.
This Data Science Skills Bootcamp gives you a structured route from foundations through to applied machine learning. You will start with onboarding and a digital skills diagnostic, then build core data literacy through the BCS data visualisation pathway. From there, you will progress into cloud and core data concepts through a vendor pathway, subject to prior experience and attainment. Finally, you will complete practical sessions in Azure Machine Learning, learning how to run experiments, optimise models, deploy endpoints, and monitor performance. The capstone project ties everything together, helping you demonstrate an end-to-end workflow in a realistic scenario.
Who is This Bootcamp For?
This Skills Bootcamp is ideal for adults looking to start a career in the fast-growing data sector. Whether you’re reskilling from another profession or looking to upskill for a new role, this course is accessible to learners from non-technical backgrounds. No previous qualifications are required, though basic digital literacy and numeracy are expected.
The programme starts with onboarding and a skills diagnostic, then builds steadily through data foundations, cloud and core data concepts, and applied machine learning using Azure Machine Learning.
If you are exploring a new career direction, want to strengthen your digital capability, or are aiming to progress into an entry-level data science or machine learning pathway, this bootcamp offers structured support and clear progression routes.
Course content
What You'll Learn
You’ll build a practical understanding of data science foundations and applied machine learning, covering data-driven decision making, storage and protection, presentation skills, cloud and core data concepts, hands-on learning in Azure Machine Learning, and applied learning through a capstone project and employability preparation.
Getting Started and Programme Foundations
- Enrolment, onboarding, digital skills diagnostic, and gap analysis.
- Introduction to the Data Skills pathway, employer expectations, and the Aspire360 learning environment.
- Bootcamp induction, initial BCS registration, paperwork completion, and an introduction to the curriculum and delivery structure.
Data Visualisation Foundations (BCS aligned)
Data-Driven Decision Making
- How organisations use data to support effective, evidence-based decisions.
- Data preparation and formatting, and common decision-making challenges such as bias and poor-quality data.
- Essential foundations in organisational data literacy.
Data Storage, Protection and Analysis Tools
- Data storage methods and the role of tools in analysis.
- Legal data protection requirements including GDPR awareness.
- How compliant storage and appropriate technologies support reliable insights.
Data Presentation and Human–Machine Collaboration
- Presenting data clearly through written, visual, verbal, dashboard, and immersive formats.
- How AI, VR/AR, and human–machine learning environments can enhance interpretation.
- Strengthening communication and stakeholder understanding across complex data scenarios.
Revision Session and Exam Preparation
Consolidation across organisational data use, GDPR awareness, analysis tools, and data presentation.
Focused revision to strengthen understanding and confidence for the assessment.
Employability and Progression Workshops
- Job-readiness through data-focused interview preparation, CV development tailored to technical roles, and analysing real entry-level job requirements.
- Preparation for relevant vendor qualifications to build confidence, competence, and readiness for progression.
- Career and self-employment action planning, including goal setting, skills assessment, and progression planning.
- Final end session including feedback, personalised careers guidance, interview coaching, and next-step planning.
Cloud and Core Data Vendor Pathway (subject to prior experience and attainment)
Fundamental Cloud Concepts
- Core cloud concepts, global architecture, and key services including compute, storage, and networking.
- Governance, security, compliance, management tools, and cost models including pricing, SLAs, and lifecycle considerations.
- Building a foundation for understanding and adopting cloud services effectively.
Core Data Concepts (Part 1)
- Structured, semi-structured, and unstructured data.
- Relational and non-relational databases, and the difference between OLTP and OLAP workloads.
- How data is stored, processed, and applied within modern cloud environments.
Core Data Concepts (Part 2)
- Key data services and selecting appropriate solutions for business scenarios.
- Relational data services and SQL workloads, and globally distributed non-relational approaches.
- Scalable analytics services and integrated processing approaches used in cloud data environments.
Revision Session and Exam Preparation
- Consolidating understanding across relational and non-relational data, analytics workloads, and key services.
- Targeted practice to strengthen readiness for the chosen route.
Applied Data Science Skills (Microsoft Applied Skills)
Data Scientist (Day One)
- Introducing the Azure Machine Learning workspace and configuring compute, environments, and data assets.
- Running and tracking machine learning experiments using notebooks and MLflow.
- Structuring, submitting, and evaluating training jobs within Azure Machine Learning’s managed environment.
Data Scientist (Day Two)
- Optimising models using sweep jobs and AutoML.
- Deploying trained models to online endpoints and testing predictions via REST.
- Exploring monitoring capabilities and building practical skills for scaling and integrating models into applications.
Capstone Project
Data Scientist (Day One)
- Introducing the Azure Machine Learning workspace and configuring compute, environments, and data assets.
- Running and tracking machine learning experiments using notebooks and MLflow.
- Structuring, submitting, and evaluating training jobs within Azure Machine Learning’s managed environment.
Data Scientist (Day Two)
- Optimising models using sweep jobs and AutoML.
- Deploying trained models to online endpoints and testing predictions via REST.
- Exploring monitoring capabilities and building practical skills for scaling and integrating models into applications.
Certified qualifications
What You'll Achieve
You’ll develop a strong foundation in data literacy and data visualisation principles, alongside applied understanding of cloud and core data concepts. You will also build practical data science capability through hands-on learning in Azure Machine Learning and complete a capstone project that demonstrates an end-to-end analytics and machine learning workflow.
Qualifications learners will work achieve:
- BCS Foundation Award in Data Visualisation (BCS)
- Microsoft Applied Skills: Data Scientist
- One of the following, subject to prior experience and attainment:
- Microsoft Azure Fundamentals and Microsoft Azure Data Fundamentals
- AWS Cloud Practitioner and AWS Certified Data Engineer Associate (Amazon Web Services)
- CompTIA Data+ (Uncertified)*
*Where learners do not have the experience, qualifications, or technical foundation needed for AWS or CompTIA+ pathways, they will follow Microsoft Fundamentals as the default route. This includes those without prior IT or cloud exposure, Level 2‑equivalent qualifications, or confidence for advanced vendor‑neutral exams, ensuring an accessible, structured, and supportive progression into technical learning.
Entry Requirements
At least
19 years old
Right to live/work in the UK
Employed or living in a funded authority area
Course benefits
Employability Support (CIAG)
In addition to technical training, learners will receive comprehensive employability support designed to improve job readiness and support successful career transitions.
This includes:
- CV development tailored to specific job roles
- Interview techniques and preparation
- Guidance on reviewing and applying for live entry-level vacancies
- Interview simulations and confidence-building activities
- One-to-one careers coaching and personalised action planning
- Support with progression into further training, apprenticeships, or employment
- Employer engagement opportunities throughout the programme
All employability activities will be supported by a dedicated Employability Coach and nationwide recruitment partners, working closely with learners to ensure they are prepared and confident.
Career Outcomes
Where This Bootcamp Can Take You
On completion, you’ll be better prepared to support analytics and machine learning work in a modern cloud environment, contributing to insight, experimentation, and model deployment. With data and AI capability increasingly valued across every sector, this bootcamp can support progression into a range of entry-level roles, as well as further specialist training pathways.
Typical roles include:
- Junior Data Analyst
- Junior Data Scientist
- Junior Machine Learning Assistant
- Data and Insights Assistant
- Analytics Support Officer
- Junior AI and Data Project Assistant
- Graduate or Entry-level Data Science Associate
FREQUENTLY ASKED QUESTIONS
Funding is available, subject to eligibility. We’ll confirm what support applies during the enrolment process.
You can contact us directly via the contact page, or fill out the form here.
No. The programme begins with onboarding and a digital skills diagnostic, then builds confidence step by step through foundations, vendor pathway learning, applied Azure Machine Learning sessions, and a capstone project.
The programme plan is structured across 15 weeks, with a typical weekly session format. Skills Bootcamps can run up to 16 weeks depending on delivery model.
Delivery is online, with guided sessions, supported learning activities, structured revision, and exam preparation. You will also complete hands-on applied learning in Azure Machine Learning, plus a capstone project.
You will work towards the BCS Foundation Award in Data Visualisation and Microsoft Applied Skills: Data Scientist, plus one additional vendor pathway subject to prior experience and attainment. The CompTIA Data+ route is delivered as an uncertified pathway, as set out in the programme.
We can’t guarantee employment, but you will receive structured employability support including CV development, interview preparation, vacancy guidance, and 1:1 coaching to strengthen your progression plan.