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.
⭐ Showcase any Python projects (even personal ones) at the top of your CV — the advert explicitly lists Python as a core step and employers will scan for hands-on evidence.
📊 Quantify your training projects: 'Built a sentiment analysis classifier using Hugging Face achieving 91% accuracy on a 10,000-record dataset' to demonstrate real output.
🎯 List your AWS Certified Cloud Practitioner certification prominently in a dedicated 'Certifications' section — it is the final milestone of this programme and a tangible credential recruiters search for.
🌐 Include a GitHub portfolio link showing your Streamlit car price app and RAG chatbot — the advert is project-heavy and hiring managers will want to see working code.
🤝 Reference AI & Data Ethics knowledge explicitly in your personal statement, as the advert dedicates an entire module to bias, fairness, and data privacy — a differentiator few junior candidates highlight.
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 a RAG-powered customer service chatbot integrating a vector database and Hugging Face LLM, reducing simulated query resolution time by 40% compared to a keyword-only baseline.
- •Developed a car price prediction Streamlit application in Python using a scikit-learn regression model trained on 8,500 records, achieving an R² score of 0.87 on the test set.
- •Completed AWS Certified Cloud Practitioner certification alongside a 15-module AI engineering curriculum, delivering 4 end-to-end projects within a 10-week self-paced schedule.
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 Trainee AI Engineer programme stands out precisely because it combines structured Python and machine learning training with tangible deliverables — a Streamlit prediction app, a Hugging Face sentiment classifier, and a RAG-powered chatbot — rather than theory alone. That project-led approach, culminating in the AWS Certified Cloud Practitioner certification, is exactly the foundation I want to build my AI engineering career on.
My background in self-directed learning and problem solving has prepared me to work through a demanding multi-step curriculum at pace. I am comfortable with data workflows, have begun exploring Python independently, and understand the importance of AI ethics and data privacy in real-world deployments — topics your programme addresses directly in Step 13.
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
- ›Can you explain the difference between supervised and unsupervised machine learning, and give an example use case for each?
- ›How does Retrieval-Augmented Generation (RAG) differ from a standard large language model response, and when would you use it?
- ›Walk me through how you would preprocess a raw dataset 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 LLM-powered customer service chatbot?
- ›Describe the role of vector databases in a RAG pipeline and name one tool you have used or studied.
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 ethical concern in a project or process. What did you do?
- ›Give an example of a personal or academic project you completed from start to finish. What obstacles did you face?
- ›Tell me about a time you had to meet a tight deadline while learning something new. How did you manage your time?
- ›Describe a situation where you received critical feedback on your work. How did you respond and what changed?
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 ethical concern in a project or process. What did you do?