Trainee AI Programmer
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.
Key skills
AI-extracted from the job advert
Application advice
5 AI-generated recommendations to maximise your chances.
⭐ Feature your AWS Certified Cloud Practitioner certification prominently in your CV header or skills section, as the advert lists it as the programme's final milestone and employers will scan for it first.
📊 Quantify your project work: e.g. 'Built a sentiment analysis classifier using Hugging Face, achieving 91% accuracy on a 10,000-record dataset' to demonstrate real output.
🎯 Create a dedicated Projects section listing all three portfolio builds (car price prediction app, sentiment analysis classifier, customer service chatbot) with links to GitHub repositories to evidence hands-on skills.
🌐 Highlight RAG and vector database experience explicitly in your skills list, as these are specialist AI techniques that appear in fewer than 20% of junior AI CVs and will differentiate you.
🤝 Include a Personal Statement at the top of your CV referencing your career transition into AI, citing the structured 15-step programme and the oral exam passed, to pre-empt recruiter questions about non-traditional background.
Suggested CV bullets
3 bullets our AI drafted for this specific advert, mirroring its ATS keywords.
Add these 3 bullets under your most recent experience:
- •Built an AI-powered customer service chatbot combining RAG techniques and vector databases using Python, delivering contextually accurate responses across a 500-entry knowledge base.
- •Developed a car price prediction Streamlit application using scikit-learn regression models trained on 8,000 records, achieving a mean absolute error of under £1,200.
- •Completed AWS Certified Cloud Practitioner certification alongside 14 structured AI engineering modules, producing 3 deployable Python projects within a 12-week self-paced programme.
Free to copy — tailoring requires a 30-sec CV upload.
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 AI Traineeship is precisely the structured pathway I have been seeking to transition into AI Engineering. The programme's depth — spanning Python, Retrieval-Augmented Generation, Hugging Face sentiment analysis, and the AWS Certified Cloud Practitioner qualification — aligns directly with the skills employers are actively hiring for across healthcare, finance, and retail sectors.
My background in self-directed learning and project delivery has equipped me with the discipline to complete a 15-module online programme while building three portfolio projects: a car price prediction app, a sentiment analysis classifier, and an AI-powered customer service chatbot. I am confident these tangible outputs will demonstrate practical capability to prospective employers from day one.
Free signup, no card needed. Export to PDF/Word requires a £1.99 trial (14 days).
Interview questions
10 questions generated from this advert.
Technical
- ›Explain the difference between supervised and unsupervised machine learning and give an example use case for each.
- ›How does Retrieval-Augmented Generation (RAG) work, and why would you choose it over fine-tuning a large language model?
- ›Walk me through how you would clean and prepare a raw dataset using Pandas before feeding it into a scikit-learn model.
- ›What is prompt engineering and what techniques did you use when building your customer service chatbot project?
- ›Describe the AWS Certified Cloud Practitioner exam domains and how cloud infrastructure supports AI application deployment.
Behavioural
- ›Tell me about a time you had to learn a completely new technical skill independently — how did you structure your learning?
- ›Describe a situation where you identified an error or bias in a dataset or process. What did you do about it?
- ›Give an example of a project you completed from start to finish without direct supervision. What challenges did you face?
- ›Tell me about a time you had to explain a technical concept to a non-technical person. How did you approach it?
- ›Describe a moment when you received critical feedback on your work. How did you respond and what changed as a result?
STAR answer examples
Model answers using the Situation-Task-Action-Result framework. Adapt to your own experience.
Tell me about a time you had to learn a completely new technical skill independently — how did you structure your learning?
Describe a situation where you identified an error or bias in a dataset or process. What did you do about it?