- Data Science Principles
- Introduction to Machine Learning
- Further Machine Learning
- AI (Artificial Intelligence) and Digital Innovation
- Neural Networks and Deep Learning
- Model Interpretability
- Ensemble Methods in Machine Learning
- Data Science Toolbox
- Software Development
- Big Data
- Data Security
- Data Science for Business
- Data Architecture and Data Pipelines
- AI Project, Development and Management
- Presentation Skills
- Technical Testing and EPA Support
- 18-month program.
- £17,000 Levy Funded, with no cost to learners!
- Acquire Artificial Intelligence (AI) Data Specialist Level 7 Apprentice Qualification.
- Learn whilst being paid a full salary!
- Entry to the largest project data community and project hackathon in the UK.
- Understand the principles of artificial intelligence (AI) and machine learning (ML). This
includes understanding the different types of AI and ML algorithms, how they work, and
- Use AI and ML techniques to solve problems. This includes being able to identify problems that can be solved using AI and ML, and then designing and implementing solutions.
- Communicate effectively about AI and ML. This includes being able to explain AI and ML
concepts to stakeholders, and presenting the results of AI and ML projects in a clear and
- Work effectively in a team. This includes being able to collaborate with others, share ideas, and resolve conflicts.
- Adopt a professional approach to work. This includes being able to work independently,
manage time effectively, and meet deadlines.
These are just some of the key learning outcomes from the AI Data Specialist apprenticeship standard.
- Power BI
- Chat GPT
- Google Bard
- Improved data management practices: Employers will have a better understanding of the principles of data management, such as data governance, data quality, and data security. This will allow them to manage their data more effectively, which can lead to improved decision-making and increased productivity.
- Enhanced data analysis capabilities: Employers will be able to use more advanced data analysis techniques, such as machine learning and deep learning. This will allow them to identify patterns and trends in their data that would not be visible using traditional methods.
- Improved communication about data: Employers will be able to communicate data findings in a more technical and sophisticated way. This will allow them to build trust with stakeholders and improve decision-making. Enhanced teamwork skills: Employers will have employees who are able to collaborate effectively with others in order to build and deploy AI and ML models. This will lead to better problem-solving and innovation.
- Increased employee engagement: The apprenticeship standard can help employers to create a more engaging work environment for their employees by providing them with opportunities to work on challenging and cutting-edge AI and ML projects.
- Improved ability to compete in the global market: By using AI and ML, employers can gain a competitive advantage by being able to make better decisions, improve their products and services, and communicate more effectively with stakeholders.
- Strong understanding of AI and machine learning principles.
- Experience in developing and implementing AI strategies.
- Experience in developing and deploying machine learning models.
- Experience in applying machine learning to solve business problems.
- Ability to communicate effectively with stakeholders.
- Strong analytical, leadership and problem-solving skills.
- Candidates who have completed the Level 4 apprenticeship.
Typical Job titles include: AI Strategy Manager, Artificial Intelligence Engineer, Artificial Intelligence Specialist, AI Director, Machine Learning Engineer, Machine Learning Specialist.
- Possess a valid passport/ birth certificate/residence permit and NI number.
- Must have lived in the UK and /or EU prior to start date.
- Must not be undertaking another apprenticeship at the same time.
- The apprenticeship must offer substantive new skills and knowledge in your existing or new role.
- Honours degree (2:2 or above) in an appropriate discipline or other relevant qualifications/experience.
- GCSE Maths and English (you will be enrolled onto Level 2 Functional Skills Maths and English to gain your qualification if you do not have these).