A data-driven organisation requires a minimum level of data skills across the workforce. Employees need to understand what is achievable with data, embed data in their daily work to make data-led decisions and maximise new tools and technologies in data and AI. As organisations increase the number of technical teams working in Python programming, other teams need to be data literate to maximise working effectively with technical teams.
- Efficiently prepare and analyse data
- Visualise and present actionable data-driven insights
- Use industry-standard tools including Excel, Power BI and Tableau
- Build basic data literacy skills across the organisation
- Empower the general population to work more effectively with technical data teams
Build your organisation’s Data Analytics and Python capabilities at scale with our Data Analyst Academy. Equip your employees with the technical skill set to extract, manipulate and visualise data, empowering them to answer complex questions and drive strategic value.
- Use Python programming and data analysis tools such as Pandas and Numpy to create insights that can drive commercial decision-making
- Use data visualisation to summarise, present and make recommendations from the results of data analysis
- Make commercial decisions informed by impactful data analysis
- Reduce costs through automation of manual processes and increased staff productivity
Cambridge Spark’s Data Engineer Academy teaches your workforce the skills to design, construct and maintain the infrastructure to support data science.
- How to extract, clean and prepare data ready for analysis
- How to work with large complex datasets
- How to maintain the infrastructure needed to scale data science across an organisation
- Scale the data science and analytics capability of an organisation
- Increase the return on investment from data science and analytics teams through an efficient infrastructure providing the required data
Currently in development - due for delivery late 2021
The breadth of skills required to deliver end-to-end data science and AI projects are complex and constantly evolving. Data science roles are now becoming more specialist, as are the tool kits used, with more demand for advanced machine learning and AI skills. It can take organisations a long time to find talent with the specific skills they need.
- Identify and devise data-driven AI solutions to address business opportunities and customer needs
- Use Data Science and AI techniques to automate and optimise business processes
- Build capability to enable and deploy AI across the organisation
- Drive business growth with AI solutions to address business opportunities
- Reduce costs through automating and optimising manual processes
Machine Learning Engineer
Successfully deploying data science and machine learning models in production requires a specialist skillset blending traditional software engineering with modern data science techniques.
- Be able to put into production the models create by data science teams and scale them across an organisation
- Feed and manage the data being fed into those models to optimise and automate business processes
- Scale AI and machine learning capability across the organisation effectively
- Increased ROI from Data and AI projects
Register your interest
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We look forward to speaking with you.
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