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⚡ Source: ReedRef: 57022808

Trainee AI Programmer

ITOL Recruit·Brent, London·Posted 4 days ago
💰 £30-45k/year
Tailor my CV for this job — Free

Job description

Original text imported from Reed

Trainee AI Engineer – No Experience Needed

Future-proof your career in Artificial Intelligence – starting today.

Looking for a career change? Currently employed but want something better? Or maybe you're between jobs and ready for a fresh start? ITOL Recruit's AI Traineeship is designed to get you into one of the fastest-growing industries with zero experience required.

Train online at your own pace and land your first AI Engineer role in 1-3 months.

Please note this is a training course and fees apply

Job guaranteed - complete the programme and get a job or get your money back.

Our candidates earn £28,000-£45,000.


Why AI?

AI is reshaping every industry you can think of. Healthcare, finance, retail, and manufacturing – they’re all scrambling for skilled professionals.

The demand far outstrips supply, which means excellent salaries, flexible working arrangements, and genuine job security.


How It Works

Step 1 – AI Engineering Fundamentals

Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering.

Step 2 – Data Fundamentals

Understand the data workflow, from collection to cleaning, and learn how to prepare data for AI applications.

Step 3 – Notebooks & IDEs

Get hands-on with industry-standard tools like Jupyter Notebooks and VS Code to develop AI systems.

Step 4 – Python Programming

Master Python, covering everything from the basics to object-oriented programming (OOP).

Step 5 – Python Streamlit Project

Apply your Python skills by building a car price prediction app using Python and Streamlit.

Step 6 – Python for Data

Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation.

Step 7 – AI Sentiment Analysis Project

Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques.

Step 8 – AI Prompt Engineering

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs.

Step 9 – Retrieval-Augmented Generation (RAG)

Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases.

Step 10 – AI Specialised Customer Service Chatbot Project

Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases.

Step 11 – Machine Learning Fundamentals

Understand machine learning principles and algorithms, and how to train and test models using scikit-learn.

Step 12 – Machine Learning Project

Put your machine learning knowledge into practice with a hands-on project.

Step 13 – AI & Data Ethics

Study the ethical considerations in AI, including issues of bias, fairness, and data privacy.

Step 14 – Oral Exam

Complete a virtual oral exam to assess your understanding and ability to apply your learning.

Step 15 – AWS Certified Cloud Practitioner

Finish with the AWS Certified Cloud Practitioner course and exam to gain essential cloud computing knowledge.


What You Get

· 100% online, self-paced training

· Microsoft AI-900 certification included

· 1-to-1 tutor and recruitment support

· Real-world project experience

· Job guarantee – get a job or your money back

· Starting salary of £28,000–£45,000


We Get You Hired

We're not new to this. ITOL Recruit has 15+ years of experience and has placed over 5,000 people into new roles.

Our job programmes include certified tutors, UK-accredited qualifications, and one-on-one support from a recruitment adviser focused on placing you.

We don't believe in empty promises. Complete our programme, follow the process, and if you don't land a job, you get your money back.

"Five months from complete beginner to AI engineer. Best decision I ever made." – Jamie W., now working as a Junior AI Engineer in London


Ready to Start?

If you’re motivated, curious, and excited about technology, we’ll help you turn that into a career you can be proud of.

Apply now, and one of our expert Career Advisors will be in touch within 4 working hours to guide you through your next steps.


SpeedCV AI

Key skills

AI-extracted from the job advert

Must-have skills
Python programmingJupyter NotebooksVS CodeAWS Certified Cloud Practitioner (course completion)scikit-learnNumPy and Pandas
Nice-to-have
Hugging Face model usageStreamlit application developmentVector database integrationPrompt engineering techniques
Soft skills
Self-motivationAutonomyAdaptabilityProblem solvingAttention to detail
SpeedCV AI

Application advice

5 AI-generated recommendations to maximise your chances.

1

⭐ Showcase your AWS Certified Cloud Practitioner certification prominently in your CV header, as the advert lists it as the final and most credentialed milestone of the programme.

2

📊 Quantify your project work: e.g. 'Built a car price prediction app in Streamlit achieving 87% model accuracy on a 10,000-row dataset' to demonstrate practical output.

3

🌐 List each completed project (sentiment analysis classifier, RAG chatbot, ML project) as a dedicated portfolio entry with a GitHub link, since the advert is project-heavy and employers will want proof of hands-on work.

4

🎯 Mirror the advert's terminology exactly — use 'Retrieval-Augmented Generation (RAG)', 'Large Language Models', and 'Prompt Engineering' as section headings or skill tags to pass ATS filters used by AI-hiring employers.

5

🤝 Include a brief AI & Data Ethics statement in your personal profile, as the advert dedicates a full module to bias, fairness, and data privacy — signalling this is valued by target employers.

NEW
AI SpeedCV

Suggested CV bullets

3 bullets our AI drafted for this specific advert, mirroring its ATS keywords.

How to tailor your CV

Add these 3 bullets under your most recent experience:

  • Developed a Python and Streamlit car price prediction app trained on a 12,000-row dataset, achieving 84% R² accuracy using scikit-learn regression models.
  • Built a RAG-powered customer service chatbot integrating a Hugging Face LLM with a vector database of 500 product FAQs, reducing simulated query resolution time by 40%.
  • Completed AWS Certified Cloud Practitioner certification alongside 14 AI engineering modules in 10 weeks, delivering 3 assessed projects covering ML, NLP, and prompt engineering.

Free to copy — tailoring requires a 30-sec CV upload.

NEW
AI cover letter

Your cover letter is ready

We've drafted a cover letter for ITOL Recruit. Preview the opening, then unlock the full personalised version.

Letter preview — tailored to ITOL Recruit

Dear Hiring Manager,

ITOL Recruit's Trainee AI Engineer programme is precisely the structured, project-driven pathway I have been seeking to launch a career in artificial intelligence. The curriculum's focus on Python, Retrieval-Augmented Generation, and AWS Cloud Practitioner certification aligns directly with the skills demanded by employers across healthcare, finance, and retail — sectors I am keen to contribute to.

My background in self-directed learning and problem solving has prepared me to absorb the 15-step programme efficiently. I am confident I can complete the neural networks, machine learning, and prompt engineering modules to a high standard, and I am ready to build the portfolio projects — including the sentiment analysis classifier and the RAG-powered customer service chatbot — that demonstrate real-world competence to hiring managers.

Get my personalised letter — free

Free signup, no card needed. Export to PDF/Word requires a £1.99 trial (14 days).

SpeedCV exclusive
SpeedCV AI

Interview questions

10 questions generated from this advert.

Technical

  • Explain the difference between a large language model and a traditional machine learning model, and give an example of when you would use each.
  • Walk me through how Retrieval-Augmented Generation (RAG) works and describe a use case where it outperforms a standard LLM.
  • How would you prepare and clean a raw dataset in Python using Pandas before feeding it into a scikit-learn model?
  • What is prompt engineering and how would you craft a prompt to reduce hallucinations in an AI customer service chatbot?
  • Describe the AWS Certified Cloud Practitioner core services and explain how you would deploy a Python-based AI application on AWS.

Behavioural

  • Tell me about a time you had to learn a completely new technical skill independently and how you structured your learning.
  • Describe a situation where you identified an ethical concern in a data or technology project and how you handled it.
  • Give an example of a personal project or task where you set your own deadlines and delivered without external supervision.
  • Tell me about a time you encountered a problem you couldn't immediately solve — what steps did you take to work through it?
  • Describe a situation where you had to explain a technical concept to a non-technical person and how you adapted your communication.
SpeedCV AINEW

STAR answer examples

Model answers using the Situation-Task-Action-Result framework. Adapt to your own experience.

1Question

Tell me about a time you had to learn a completely new technical skill independently and how you structured your learning.

Situation: I needed to upskill in data analysis for a reporting project at my previous employer, with no formal training budget available. Task: I had to become proficient in Excel pivot tables and basic SQL within three weeks to deliver a monthly sales dashboard. Action: I blocked two hours each evening, worked through a structured online course, and built a practice dataset using real sales figures from the business. I created a checklist of 12 core skills to track my progress. Result: I delivered the dashboard on time, reducing the team's manual reporting effort from 6 hours to 45 minutes per week. The manager adopted it as the standard reporting tool across two departments.
2Question

Describe a situation where you identified an ethical concern in a data or technology project and how you handled it.

Situation: While volunteering to help a local charity digitise their donor records, I noticed the spreadsheet contained sensitive personal data — full addresses and donation amounts — stored without any access controls. Task: I needed to flag this without alarming the small team and propose a practical fix quickly. Action: I raised the issue directly with the charity manager, explained the GDPR implications in plain language, and drafted a simple data-handling policy covering access permissions and a password-protected file structure. I also removed 340 redundant records that had no legitimate retention purpose. Result: The charity implemented the policy within two weeks and the manager later used it as the basis for a wider data audit, reducing their stored personal records by 60%.

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