AI & Machine Learning Fellowship Programme Overview
This programme empowers data science teams with the skills to transform raw data into valuable business intelligence. By integrating AI and machine learning, it enables organisations to shift to proactive decision-making, enhance efficiency by reducing manual processes and human error, and identify new business opportunities. It is part of our AI Academy Programmes.
Key Skills Gained:
Python for ML
Data science
Machine learning
Feature engineering and selection
Model development and training
Ethical and responsible AI
Data governance
Data change management
Business Outcomes:
Extract better business intelligence: Equip your team with advanced skills to extract meaningful insights, transforming raw data into valuable business intelligence.
Improve efficiency: Optimise your ML operations to significantly improve operational efficiency and productivity.
Discover deeper insights: Develop predictive models and adaptive systems, shifting your organisation from reactive to proactive decision-making.
Apprenticeship Qualification Achieved: Level 6 Machine Learning Engineer Duration: 15 month delivery, plus 3 month assessment
Software Requirements: AI & Machine Learning Fellowship Software Requirements
AI & Machine Learning Fellowship Indicative Curriculum Breakdown
Foundations: harnessing AI and machine learning
Month 1: Fundamentals of machine learning and AI
Month 2: Solving business problems with machine learning
Month 3: Data ethics and responsible AI
Month 4: Data preparation and feature engineering
Month 5: Hackathon: planning and preparing an AI solution
Application: building AI models with security best practices
Month 6: Model engineering and training
Month 7: Model evaluation
Month 8: Data security, privacy, and governance
Month 9: Hackathon: engineering an AI solution
Deployment: monitoring and maintaining models
Month 10: Model deployment
Month 11: Monitoring, maintenance, continuous learning
Month 12: Stakeholder communication
Month 13: Hackathon: deploying an AI solution
Note: This is an example curriculum, and specific details may vary per cohort.
AI & Machine Learning Fellowship Indicative Delivery Model
Monthly delivery model, approx. 26 hours per month total commitment. The exact time commitment will be outlined in the training plan that apprentices will receive at the start of their apprenticeship.
Structured Learning (~40% - 10 hours/month):
Asynchronous learning (3.5 hours): Online, self-paced content that sets the foundation of skills for the module.
Live workshops (3.5 hours): Instructor-led, interactive learning that dives deeper and reinforces the asynchronous content.
Group coaching (1 hour): Peer support and feedback on project deliverables.
Coach support (2 hours): Includes tutoring, progress reviews, & other individual/group support.
Working in Existing Role (~60% - 16 hours/month):
Project and applied learning (16 hours): Structured and unstructured application of learning to apprentices’ roles.