AI / ML Specialist in Walsall

Trainee AI Engineer – No Experience Needed

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

Why AI?

AI is reshaping every industry you can think of. 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 – Hands-on Tools: 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 – Integrating Knowledge: 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 – Virtual 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.

100% online, self-paced training · Microsoft AI-900 certification included · Real-world project experience · Five months from complete beginner to AI engineer.

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