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  "job_description": "Trainee AI Engineer - No Experience Needed\n\nFuture-proof your career in Artificial Intelligence - starting today.\n\nLooking for a career change? Currently employed but want something better? Or maybe you're between jobs and ready for a fresh start?\n\nTrain online at your own pace and land your first AI Engineer role in 1-3 months.\n\nPlease note this is a training course and fees apply\n\nJob guaranteed - complete the programme and get a job or get your money back.\n\nOur candidates earn £28,000-£45,000.\n\nHow It Works\n\nStep 1 - AI Engineering Fundamentals\n\nStart with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering.\n\nStep 2 - Data Fundamentals\n\nUnderstand the data workflow, from collection to cleaning, and learn how to prepare data for AI applications.\n\nStep 3 - Notebooks & IDEs\n\nGet hands-on with industry-standard tools like Jupyter Notebooks and VS Code to develop AI systems.\n\nStep 4 - Python Programming\n\nMaster Python, covering everything from the basics to object-oriented programming (OOP).\n\nStep 5 - Python Streamlit Project\n\nApply your Python skills by building a car price prediction app using Python and Streamlit.\n\nStep 6 - Python for Data\n\nLearn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation.\n\nStep 7 - AI Sentiment Analysis Project\n\nWork with Hugging Face to build a sentiment analysis classifier using real-world AI techniques.\n\nStep 8 - AI Prompt Engineering\n\nMaster prompt engineering, learning how to craft effective prompts for controlling AI outputs.\n\nStep 9 - Retrieval-Augmented Generation (RAG)\n\nLearn how to integrate external knowledge into AI systems using RAG techniques and vector databases.\n\nStep 10 - AI Specialised Customer Service Chatbot Project\n\nCombine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases.\n\nStep 11 - Machine Learning Fundamentals\n\nUnderstand machine learning principles and algorithms, and how to train and test models using scikit-learn.\n\nStep 12 - Machine Learning Project\n\nPut your machine learning knowledge into practice with a hands-on project.\n\nStep 13 - AI & Data Ethics\n\nStudy the ethical considerations in AI, including issues of bias, fairness, and data privacy.\n\nStep 14 - Oral Exam\n\nComplete a virtual oral exam to assess your understanding and ability to apply your learning.\n\nStep 15 - AWS Certified Cloud Practitioner\n\nFinish with the AWS Certified Cloud Practitioner course and exam to gain essential cloud computing knowledge.\n\nWe Get You Hired\n\nOur job programmes include certified tutors, UK-accredited qualifications, and one-on-one support from a recruitment adviser focused on placing you.\n\nWe 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.\n\n\"Five months from complete beginner to AI engineer. Best decision I ever made.\" - Jamie W., now working as a Junior AI Engineer in London\n\nReady to Start?\n\nIf you're motivated, curious, and excited about technology, we'll help you turn that into a career you can be proud of.\n\nApply now, and one of our expert Career Advisors will be in touch within 4 working hours to guide you through your next steps.",
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