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Data Science
Explore the programme
Our Data Science Traineeship gets you job-ready in just a few months, through our proven 4-step training path.
Study 100% online with the flexibility to learn around your lifestyle - ideal for full-time, part-time, or unemployed learners.
Entry-level Data Science roles typically start at around £30K, increasing to £50K+ once you specialise within the industry.
Our expert recruitment team works only with our graduates to secure your dream role through our UK-wide partnerships.
If you don’t receive a job offer within 12 weeks of completing your studies, we will refund 100% of your course fees.
Each stage moves you from core data learning into recognised Microsoft certification, practical projects and recruitment support for your first data role.
Step 1
Begin with industry-recognised data science training that builds the core skills needed for junior data roles.
Step 2
Progress into Microsoft Power BI training designed to develop your data analysis, modelling and visualisation skills.
Step 3
Sit the Microsoft PL-300 exam to validate your ability to analyse and visualise data for decision making.
Step 4
Complete two practical projects based on real-world data science scenarios.
Step 5
Work with a dedicated Recruitment Mentor who will tailor your CV, prepare you for interviews and help source suitable data roles.
Data science, analytics and Power BI training modules
Step 1 foundation
Data Science is one of the most in-demand skillsets that companies are constantly hiring for. This Skill Path will teach you the basics of cleaning, analysing, and visualizing data.
You will learn industry-standard languages and libraries including Python, pandas, and SQL. Along the way, you will create real-world projects to practice and demonstrate your analytics skills.
Step 1 programming
Python is a general-purpose, versatile, and powerful programming language. It is a great first language because Python code is concise and easy to read.
From web development to machine learning to data science, Python is a great language to know and gives you a strong base for practical data work.
Step 1 statistics
R is a powerful programming language built specifically for data science by actual data scientists. In this Skill Path, you will learn to clean and process data, build statistical models, and create meaningful data visualizations.
Along the way, you will use real-world data to demonstrate your skills by producing analytics reports.
Step 1 AI module
Machine Learning and AI are at the forefront of some of the most exciting modern technologies. From fraud detection systems to dating apps, machine learning engineering is changing the world.
Becoming confident in this area requires a solid foundation in data literacy, programming, mathematics, statistics, and visualization. This Skill Path is that foundation.
Step 1 database module
All companies use data now, and most of it is stored in databases. In this Skill Path, you will use SQL queries to create databases, pull data from databases, and analyse the results.
You will practise your skills with real-world marketing and user analysis case studies, prepare for technical interviews, and build prompt engineering confidence through hands-on exercises.
Step 1 analytics module
Companies are looking for Data Scientists who can manage data, get results, and drive decision-making. Analytics is all about using data to answer questions, and this Career Path will teach you just that.
You will learn how to analyse data, build dashboards, and deliver impactful reports. Along the way, you will build portfolio-worthy projects that help you get job-ready.
Step 1 deep learning
Deep learning is a cutting-edge form of machine learning inspired by the architecture of the human brain, but it does not have to be intimidating.
In this Skill Path, you will use TensorFlow and Keras to train, test, and tune neural networks for regression and classification. Along the way, you will demonstrate your skills by building actual models with real data.
Step 1 machine learning preparation
A machine learning model is only as good as the data it learns from. Feature Engineering helps ensure data quality by scaling, normalizing, and transforming raw data before using it in a machine learning model.
In this Skill Path, you will learn to safeguard data quality, turn attributes into features, and verify that your data meets the assumptions of the model you want to train.
Step 2 Microsoft certification
This course is designed to equip you with the skills and knowledge necessary for effective data analysis and visualization using Microsoft Power BI.
It focuses on the core competencies required for data analysts to prepare, model, visualize, and analyze data effectively. After completing this course, you will be well-prepared to pass the PL-300 exam and will receive access to official Microsoft Power BI Data Analyst mock tests.
Expert support that keeps your progress practical and focused
Specialist tutor
As a self-taught full stack web developer with php, javascript, react, python experience, I understand the struggles students go through when trying to learn. In addition, I have data science experience including the python data science stack, sql, power BI and other data visualisation technologies as well as statistics. I bring a unique combination of web development and data science skills that help me provide support to students in a well-rounded manner.
My focus is on helping students overcome challenges they cannot do so on their own. Based on my experience, I will recommend the best techniques to employ in overcoming a particular challenge the student is facing. I am confident that anyone can learn if they're willing to work hard and ask for help when required
Your recruitment phase is delivered as a guided process, with clear actions at each stage so you can move from training and project work into real data roles with confidence.
Open each stage to review exactly what support is included.
Your CV will be professionally rewritten and tailored specifically for the data industry, highlighting your Python skills, analytical ability, project work and transferable experience. We focus on aligning your profile with what employers look for in junior data candidates, helping you stand out and improve your chances of securing interviews.
The consultation sets the foundation for your move into data. You will begin with a dedicated consultation to understand your background, goals and preferred direction, allowing us to identify suitable data-focused roles for you. From there, we create a clear recruitment plan so your applications are targeted, relevant and competitive.
Our job placement support is designed to connect you with suitable data opportunities quickly and effectively. Your dedicated consultant will help source relevant roles such as Data Analyst, Junior Data Analyst, Reporting Analyst and BI Assistant, while preparing you to explain your projects, technical skills and analytical approach confidently in interviews.
Once you have completed the required training, practical projects and programme milestones, our recruitment team will support you towards your first data-focused role. The initial goal is to help you secure a realistic entry point into the data industry where you can begin building commercial experience.
From there, you can continue developing your analytical, programming and business insight skills, giving you a pathway into more advanced roles such as Data Scientist as your experience grows.
Prospective Role
Data Analyst
This is where most trainees begin applying their data skills in a commercial environment, helping businesses understand information, spot trends and make better decisions.
Read moreAs a Data Analyst, you will work with raw information and turn it into something useful. This can include cleaning data, preparing reports, building dashboards, identifying trends and presenting findings to managers or wider teams.
Typical responsibilities include:
Typical starting salary: £25,000-£35,000
Prospective Role
Data Scientist
After building experience in data analysis, you can progress towards more advanced data science work involving modelling, prediction, automation and deeper analytical problem-solving.
Read moreAs a Data Scientist, you move beyond reporting into deeper analysis and predictive work. The role focuses on using data, statistics and programming to solve more complex business problems.
Typical responsibilities include:
Typical progression salary: £40,000-£60,000+
Organisations our students have gone on to work with
We've got you covered. Under our job guarantee or your money back policy, we'll place you into an Data Science role within 12 weeks of completing your Traineeship, within 20 miles of your home and with an average starting salary of £30,000. If we're unable to do so, we'll refund all your course fees within 10 working days - no hassle, no questions.
Secure a role close to home. We guarantee job opportunities within 20 miles, so you will not need to relocate.
Step into a high-paying career, with our graduates earning £30,000+ on average in their first role.
After completing your training, we have a 12-week recruitment window to secure your new role.
No job? No risk. If we cannot get you into a role within 12 weeks, your course fees will be refunded within 10 days.
We're committed to helping you launch a successful career - or your money back.
See what a typical day looks like for our Traineeship graduates as they build confidence and grow in their new careers.
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Straightforward answers to the questions most people ask before starting a data-focused career.
Yes. Practical work is a core part of the Traineeship.
You will complete data-focused projects that involve analysing datasets, identifying trends and presenting insights. These projects help demonstrate your ability to employers.
Most learners begin in an entry-level data or analyst role.
With experience, you can progress into more advanced data science or machine learning roles.
Standard
A complete entry route with core training, exam support, practical labs and job-focused guidance.
Your success is our priority.
See what our candidates say about their experience.
