Register Your Interest!

The Experience Accelerator runs Monday to Friday from 9am to 5pm. We observe UK bank holidays. On rare occasions some sessions may last later in the day and advanced notice will be provided. We do our best to ensure mandatory sessions do not conflict with religious observances and are used to working with people from all different backgrounds, religions, and cultural groups. If you do have any questions or require any specific accommodation, please contact us at info@io-sphere.io.

For the experienced tracks (Senior Analyst, Data Scientist, Analytics Engineering, and Data Leadership), the Acquire portion of the course has a minimum commitment of 14 hours per week, however this can scale to full-time depending on an individuals availability.  The part-time commitment is in place for those who are working full-time during Acquire. For those who are not working full-time, we encourage you to actively take part in as much of the full-time Acquire programme as possible! The Experience Accelerator is one big programme encompassing all 5 job profiles, each with their own technical and professional curriculum. There is a full schedule of content running through Acquire as the Data Analyst track is full-time throughout the Experience Accelerator, and those sessions are open to all of our trainees.

The majority of the minimum commitment of 14 hours per week for the experienced tracks can be done asynchronously, however there are group coaching sessions late on Wednesday afternoons which are mandatory. If you cannot make late afternoons on Wednesday work, please let us know on your application so that we can accommodate you or contact us at info@io-sphere.io.

The first part of the Experience Accelerator (ACQUIRE) is online and the second part (APPLY) is a combination of online and face-to-face.

During APPLY, you will need to be able to attend our training location in either London or Manchester for a minimum of 3 days every week.

You will be using your own laptop through the duration of the course and we will provide the relevant licenses as we move through the course. However, please note that we cannot provide technical support for Macs, and we require the PC Desktop version of both Excel and Power BI.

This means that Mac users will need to purchase a Parallels subscription (about £90) and troubleshoot issues that arise on their own. We have found that some students find it easier to borrow a PC from a friend or family member for the duration of the course.

We love for international applicants to participate in our Experience Accelerator! It is the best, most employer-led data training programme in the UK. We give you the experience you need in order to confidently apply to jobs in data.

For those without the permanent right to work in the United Kingdom, you are still able to participate in our Experience Accelerator by paying the full course fees in advance or in instalments over the course of the programme –£5,400 (£4,500 + VAT). This is the same price that all of our trainees pay and you will receive the exact same level of coaching and ongoing career support.

The reason that we are not able to offer our job guarantee or fund the up-front training costs for international candidates, is that we are unable to guarantee your future right to work in the UK. In order to participate, you must still meet the entry requirements and pass the interview process.

This model applies to:

• – Student visas or Post Study Work Visas (PSWs)
• – Other temporary visas lasting less than 3 years*
• – Visas without work authorisation

*If you are on a Spousal Visa, you may be eligible for the standard fee model unless there is less than 1 year to your visa expiry date, in which case the temporary visa fees will apply. Your spouse must not be on a temporary work visa.

Please note that as a full fee paying student, you will not be eligible for the Fellowship programme.

You are welcome to apply, but please note attendance to the in-person portion of the programme is mandatory. We are a UK business focussed on serving UK based trainees and UK employers. In order to qualify for our job guarantee, you need to be physically present in the UK 75% of the time and be intending to relocate to the UK following the completion of the programme. If you do not intent to relocate to the UK or satisfy the job guarantee, you will be liable for the full course fees as described on our website.

The Experience Accelerator is for anyone looking to kickstart or accelerate their career in analytics and data. There are only a limited available places on each cohort so it will be selective but it really doesn’t matter who you are and what your background is.

Applicants must be based in the UK, have the appropriate Right to Work, have completed their education and be available to accept a full time job.

• – Entry level – Data Analysts: the track for career-switchers and career-starters. This track requires no prior commercial work experience in data and is for the majority of our trainees. Over the course of the 10-weeks, we will take you from no experience in data to being a fully functioning data analyst
• – Experienced – Senior Analysts, Data Scientists, and Analytics Engineers: for those with at least 1-2 years of prior commercial work experience in data who are looking to take their career to the next level. Over the course of the 10-weeks, we will specialise you technically into your chosen job profile, and also teach you how to work effectively across job profiles using agile as a methodology
• – Leader – Data Leaders, People Managers: the track for those with significant experience in data (min 4 years) as a technical individual contributor who want to take the next step in their career and learn how to properly manage and lead technical teams

No, you do not!

The majority of our applicants do have a Maths A-Level or equivalent, however we have had very successful trainees who do not. The reason we ask for a Maths A-Level or equivalent is that the Experience Accelerator is an intensive training programme, and we do not have time to cover maths and general numeracy during the programme itself. We have purposely compressed the Experience Accelerator down into 10-weeks in order to get people through, trained up, and back onto the job market as quickly as possible. That means that during the programme we focus on the skills and experience that are required to be a data professional.

One of the big myths in data is that you need to be an advanced maths wizz in order to be successful. That simply is not true. If you don’t have an A-Level and are comfortable working with numbers, looking at distributions, some algebra, understand some statistics (means, modes, medians, normal distributions), and are keen to learn and up-skill, you should be fine! One great place to up-skill on maths for free if you are worried is Khan Academy (https://www.khanacademy.org/).

We recommend the high school statistics (https://www.khanacademy.org/math/probability), Algebra Units 1-12 (https://www.khanacademy.org/math/algebra), and Probabilities Units 1-12 (Units 13-16 are good, just a bit more advanced) (https://www.khanacademy.org/math/statistics-probability).

For those with a Maths A-Level, and are worried it’s been too long and it’s all forgotten. Don’t worry! Half of our trainees are career-switchers with an average of 5-7 years of experience and up to 20+. You can also brush up using Khan Academy, and there will be some refresher materials during the programme. If you are concerned, please reach out to info@io-sphere.io.

If you do not have a maths A-Level, please select ‘No’ or ‘Unsure’ on your application and give a bit of background about your own experience and skill in maths and numeracy.

What equivalents do we accept? We are looking for a higher level of study than GCSEs in a numerate discipline – economics, physics, biology, chemistry. Many university courses like psychology will have an introduction to statistics. International equivalents are also accepted.

• Data Analysts: Create insights, recommendations, work on strategic decisions, build reports and dashboards, automate workflows and processes, use statistical techniques to create forecasts, understand causes and effects, analyse tests, etc. Analytics is often the quicker route to value realisation by companies because it doesn’t rely on infrastructure and deployment capabilities. This is often the harder job because it requires excellent interpersonal skills and very strong business acumen
• Data Scientists: Build products that automate decision making – mostly in the form of statistical models but sometimes much simpler decision trees. Statistical models can range from simpler linear regression through to much more complicated machine learning algorithms. These roles tend to be more complicated technically – and a lot of the difficulty exists in the end-to-end process management of model building

1. True entry-level roles in data science are rare and as a result we cannot guarantee an entry-level job offer after graduating from the programme. The majority of entry-level roles are more aligned to the content in our data analyst experience accelerator, even if the jobs themselves might have a data science title
2. Building machine learning (ML) models isn’t the hard part of being a data scientist or ML specialist. For a lot of commercial applications at a lot companies, just a few lines of python will build you a model. What’s really hard is being able to manage the end-to-end process of project scoping, requirements gathering, stakeholder management, data gathering, pipeline building and monitoring (including data quality!), deploying models into production, monitoring their performance, ML ops, and change management/adoption – that all comes with experience

At iO-Sphere, we are laser focused on one thing – finding the right people and giving them the right training – so that employers want to hire them by the end of the experience accelerator. That means that all of our experience accelerators have been developed in partnership with leading employers and are based on industry experience – we train for the skills and experience they value most.

The reason that we do not offer training on neural networks, deep learning, or LLMs is that those skills are not required by employers unless you’re in very specialist, technical, or research focused roles. Those are unlikely to be the roles that our trainees will get coming out of our programmes as they usually require years of experience and academic study. They are also extremely rare.

Instead, we focus on the tools and techniques that are most relevant to a broad range of employers, and most importantly, that will allow our trainees to land their next job! That means within the experienced tracks we focus on more commercial applications like classification, forecasting, and propensity modelling using more commercial and well understood techniques like linear & logistic regression, decision trees, random forests, etc.

* We do show and encourage our trainees how to use LLMs like ChatGPT and Bard in order to be better at their job, improve their code, and help them find solutions to their questions. We just don’t teach how they work under the hood.

In order to qualify for our experienced tracks (senior analyst, data scientist, and analytics engineer), we require a minimum of 1-2 years of commercial, hands-on work experience in data. For our leadership track, we require a minimum of 4-5 years of similar experience.

We are not able to accept prior academic experience either in a masters degree, PhD, or research, as we find that the gap between academia and industry is too big. The approaches to depth of knowledge, work, and application are very different!

For those switching out of academia, the data analyst experience accelerator is the best one for you! This programme runs concurrently to the experienced tracks with a heavy focus on the soft-skills, professional skills, and business acumen that are required in order to land your first job in industry. If you’re concerned that you will be alone making that transition – don’t be! We generally have 4-5 PhDs or post-docs in any given experience accelerators.

Absolutely! We understand that your schedule and preferences may change. That’s why we offer the flexibility to switch cohorts or explore new options to better suit your needs.

In 2024, we have a lineup of cohorts scheduled. To stay in the loop and receive timely updates about upcoming cohorts, simply register your interest with us here! 

We are committed to providing an amazing and transparent student experience. There are no hidden fees or exit fees, and you’re not locked into a long-term contract with us or an employer you don’t get to choose. We have spent a lot of time constructing the funding model to be as accessible, affordable and transparent as possible!

We are currently working with more than 20 employers and they range from big brands names you’ll be very familiar with, fast growth businesses, specialist data consultancies and SME’s.

We use the 10-weeks of the Experience Accelerator to identify the top performers on behalf of our partner employers regardless of previous experience and background. We are able to do this because the programme allows us to assess individuals across multiple dimensions over time including communication, collaboration, prioritisation, professionalism, working under pressure, technical skills, critical thinking and problem solving, etc. When introductions are then requested by our partner employers, we provide them with the CVs of our top performers for them to interview, but ultimately it is still up to the hiring company to offer a position and the individual’s decision to accept it. We aim for the top 40-50% of our Trainees profiles to be shared with our partner employers and the top 20% to receive an offer from a partner, however this depends on the hiring requirements of our partners and the career aspirations of our Trainees. We have a full-time team of four experienced data professionals that are continuously growing the employer network, you can see them here.

The majority of our graduates receive offers from employers that are outside the iO-Sphere network. We support all of our Trainees for 6 months after graduation as part of the Accelerate section of our Experience Accelerator, which includes weekly career coaching, interview prep, practice interviews, continuous technical upskilling, CV reviews, and LinkedIn reviews. This gives all of our Trainees the flexibility to pursue their career in data, however they would like to and not just be limited to the iO-Sphere network of employers. If you do get a job outside of the iO-Sphere network, that is when you pay back a portion of the cost of your training. The best thing about Accelerate is that it begins as soon as you start the Experience Accelerator and ends when you get a job or 6 months after the programme finishes. 82% of our first cohort had an offer within 4 months of graduating, and we expect 90%+ within 6 months. We won’t stop until you get a job!

Yes! If your job offer allows it, you are welcome to complete the programme before starting your new role. You also have the option to drop out at any point of the programme to take up your new role (please note that you will be liable for any fees up to the point of withdrawal. Please see our Cancellation Policy for more details).