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⚡ Source: ReedRéf: 57022799

Trainee AI Programmer

ITOL Recruit·Crawley, West Sussex·Publié il y a 1 mois
💰 30-45k CHF/an
Adapter mon CV à cette offre — Gratuit

Description du poste

Texte original importé depuis 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.


IA SpeedCV

Compétences clés extraites

Notre IA a analysé l'offre pour identifier les compétences attendues.

Compétences indispensables
Python programmingJupyter NotebooksAWS Certified Cloud Practitioner (course completion)
Atouts supplémentaires
scikit-learnHugging Face TransformersStreamlitVector databasesNumPy and Pandas
Soft skills
Self-motivationAutonomyAdaptabilityProblem solvingInitiative
IA SpeedCV

Nos conseils pour postuler

5 recommandations générées par notre IA pour maximiser vos chances.

1

⭐ Highlight 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.

2

📊 Quantify your project work: e.g. 'Built a car price prediction Streamlit app achieving 87% model accuracy using Python, NumPy, and Pandas across a 10,000-row dataset.'

3

🤖 Feature your RAG chatbot project in a dedicated 'Projects' section, naming the vector database used and the scope of the knowledge base — recruiters hiring AI Engineers look for end-to-end build experience.

4

🎯 Include a Personal Statement at the top of your CV referencing the ITOL AI Traineeship by name and the 15-step curriculum, so ATS systems match the structured programme to AI Engineer job descriptions.

5

🌐 List each Python library (NumPy, Pandas, Matplotlib, Streamlit, Hugging Face Transformers) as individual line items in your skills section rather than grouping them, to maximise ATS keyword hits across varied job postings.

NEW
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Bullets CV suggérés

3 bullets générés par notre IA pour cette offre, alignés sur ses mots-clés ATS.

Comment adapter votre CV

Ajoutez ces 3 bullets sous votre expérience la plus récente :

  • Developed a car price prediction web application using Python and Streamlit, training a regression model on 8,000 vehicle records and achieving 84% prediction accuracy.
  • Built a RAG-powered customer service chatbot integrating a vector database knowledge base of 500 documents, reducing simulated query resolution time by 40% versus a baseline keyword search.
  • Completed AWS Certified Cloud Practitioner certification alongside a 15-module AI engineering curriculum, delivering 3 end-to-end AI projects within a 12-week self-paced programme.

Copier est gratuit — adapter nécessite un upload CV (30s).

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Lettre IA

Votre lettre de motivation est prête

Nous avons rédigé une lettre pour ITOL Recruit. Découvrez l'ouverture, puis débloquez la version complète personnalisée.

Aperçu — adapté à ITOL Recruit

Dear Hiring Manager,

ITOL Recruit's AI Traineeship stands out for its structured, project-led curriculum — covering Python, Retrieval-Augmented Generation, and the AWS Certified Cloud Practitioner qualification — precisely the combination that employers are actively seeking. I am applying for the Trainee AI Programmer role because this programme offers a credible, measurable pathway into AI engineering backed by a job guarantee.

My background in self-directed learning and problem solving has prepared me to work through a demanding 15-step curriculum independently. I am particularly drawn to the hands-on project work — building a Streamlit price prediction app, a Hugging Face sentiment classifier, and a RAG-powered customer service chatbot — as these mirror the real-world deliverables that hiring managers expect from junior AI engineers.

Obtenir ma lettre personnalisée — gratuit

Inscription gratuite, sans carte. L'export PDF/Word nécessite l'essai 1,99 € (14 jours).

EXCLUSIF MEMBRES
IA SpeedCV

Questions probables d'entretien

10 questions générées à partir de cette offre.

Techniques

  • Can you explain the difference between supervised and unsupervised machine learning, and give an example of when you would use each?
  • Walk me through how Retrieval-Augmented Generation works and why it is preferable to fine-tuning a model in some scenarios.
  • How would you approach cleaning a dataset with 20% missing values before feeding it into a scikit-learn model?
  • What is the role of a vector database in an AI-powered chatbot, and which vector databases are you familiar with?
  • Describe the steps you took to build your sentiment analysis classifier using Hugging Face — what challenges did you encounter?

Comportementales

  • Tell me about a time you had to learn a completely new technical skill independently and how you structured your approach.
  • Describe a situation where you identified an ethical concern in a project or process and how you raised it.
  • Give an example of a time you delivered a project to a deadline despite encountering unexpected obstacles.
  • Tell me about a time you had to explain a complex technical concept to a non-technical audience.
  • Describe a situation where you took initiative to improve a process or outcome without being asked.
IA SpeedCVNEW

Exemples de réponses STAR

Réponses modèles avec la méthode Situation-Tâche-Action-Résultat. À adapter à votre vécu.

1Question

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

Situation: I needed to learn SQL for a data reporting task at my previous employer, with no formal training available and a two-week deadline. Task: I had to produce weekly sales dashboards for a 12-person management team from scratch. Action: I broke the learning into daily 90-minute sessions using free online resources, practised on a sample database of 5,000 rows, and built three progressively complex queries each day. I also joined an online forum where I could ask specific questions when stuck. Result: I delivered the first dashboard on time, reducing the manual reporting process from four hours to 25 minutes per week, and the team adopted it as their standard reporting tool.
2Question

Describe a situation where you identified an ethical concern in a project or process and how you raised it.

Situation: During a volunteer data project for a local charity, I noticed that the donor dataset we were analysing contained full names and postcodes alongside donation amounts, with no anonymisation in place. Task: As the only person with a data background on the three-person team, I felt responsible for flagging the GDPR risk before we shared any outputs. Action: I paused the analysis, documented the specific fields that posed a re-identification risk, and presented a one-page summary to the project lead recommending pseudonymisation of names and truncation of postcodes to district level. Result: The charity adopted my recommendations within 48 hours, updated their data handling policy, and we completed the project with a fully compliant dataset, avoiding a potential ICO reportable breach.

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