Build your organisation’s Data Analytics capabilities at scale
Cambridge Spark's Data Analyst Academy will equip learners with the technical skill set to empower them to extract, manipulate and visualise data, enabling organisations 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
- Work with different data formats, types and databases such as SQL
- Use data visualisation to summarise, present and make recommendations from the results of data analysis
- Test and prototype code in a production environment, follow industry best practices and use collaborative workflows
- Make commercial decisions informed by impactful data analysis
- Reduce costs through automation of manual processes and increased staff productivity
Who It Is For:
- Data-driven departments and teams looking to add more strategic value, for example business intelligence, finance, marketing, sales, or supply chain
- Employees looking to automate the manual collation and processing of data
- Employees wanting to future-proof their skill set by learning in-demand, industry-relevant skills
Task automation has been the biggest benefit. It’s taking away the manual intervention part as it’s all happening by itself now, producing up to date insights at any given moment”
Saad Abdullah, Data Analyst Apprentice at GSK
Experts in Online Delivery
We deliver all of our programmes online, helping our clients offer flexible and inclusive programmes open to all of their staff. We believe that the gold standard for online delivery is to offer a mix of experiential learning, coaching, technical mentorship and peer support.
- Live instructor-led lectures
- Technical mentor
- Experienced coach
- EDUKATE.AI, our online learning platform for data science
- Industry Expert Community
- Work-based Projects
The EDUKATE.AI platform forms part of our learning solution for a Data Science upskilling program we run called Data Science Academy. To make these technology solutions most effective, the key consideration for us is the balance between learner experience and scale/automation which the EDUKATE.AI platform delivers on."
Derek Joyce, MD at J.P. Morgan
Our curriculum is developed by our leading Faculty, made up of data scientists in leading industry positions and academics from some of the top universities in the world. Our curriculum is continuously updated and reiterated to incorporate the most cutting-edge skills.
We take a modular approach to how we offer our curriculum. The full Data Analyst Academy learning pathway includes all of the below modules. We also offer curated shorter tracks and can offer a fully tailored pathway based on a skills gap analysis.
- Introduction to PythonUnderstand and become familiar with Python syntax, structure and programming concepts.
- Data Processing with PandasJoin, manipulate and summarise datasets using the Pandas library.
- Data VisualisationLearn how to construct compelling charts and visualisations to communicate data-driven insights to technical and non-technical audiences, using libraries such as Seaborn and Bokeh.
- Power BI and TableauGain familiarity with industry standard tools for creating interactive visualisations and business intelligence capabilities.
- Data Science for BusinessLearn to identify practical applications and use cases for Data Science & AI that deliver and create business value.
- Databases and SQLLearn how to use SQL languages to store, query and retrieve structured and unstructured data and interact with databases.
- Text-mining, JSON and APIsRead and write JSON data with Python and learn automated methods for retrieving structured and unstructured data from a range of web-based sources.
- HackathonReinforce and develop the technical knowledge, practical skills and data analyst behaviours with a halfway hackathon.
- Maths for Data ScienceLearn the essential mathematical concepts that underpin much of the AI and Data Science domain, including probabilities, statistical significance and linear algebra.
- Introduction to Machine LearningBuild familiarity with a wide range of essential concepts and tools required to unlock the use of different types of machine learning models and techniques.
- Time Series AnalysisLearn to analyse and model series data with Python, Pandas and Numpy.
- Big Data SystemsLearn to identify big data-related opportunities within an organisation and to leverage the power of distributed computing to extract value and insight at scale.
- Data Privacy, Ethics and RegulationsLearn about key ethical, legal and regulatory issues relating to the use of data.
The skills being taught by this programme allows us to use Python as a tool which means that as a business we can now develop and use the data to form trend analysis to determine if there are issues and problems in our pipeline and where to focus improvement activities"
Angus Taylor, Commercial Reporting Manager at Royal Mail
What delivery options do you offer?
We tailor our delivery to your workforce needs. This ranges from from independent, immersive elearning supported by EDUKATE.AI through to tailored bootcamps to our structured Fellowship and Apprenticeship programmes. The Level 4 Data Analyst Apprenticeship is available to learners based in England.
Are you able to tailor the programme to the organisation and sector?
Yes. We work with our clients to contextualise our programmes to their organisation and sectors they operate in. We do this through tailored hackathons, bespoke assignments and guest lectures from industry experts. We also work with a range of partners to create bespoke programmes for sectors including health, retail and journalism.
What is an apprenticeship?
Apprenticeships are a long-term training commitment which seek to support people into the workforce and upskill existing UK-based employees within an organisation, enabling employers to foster a workforce consisting of highly-skilled and highly-engaged talent.
The Cambridge Spark Data Analyst Apprenticeship runs 14 months plus 3 months End Point Assessment and includes a minimum of 20% off-the-job training, enabling a blended approach between theory and practical-learning.
What is the Apprenticeship Levy?
The UK government’s Apprenticeship Levy scheme came into effect in April 2017 as a way to drive investment in strengthening the country’s skills base.
All organisations with annual staff costs of over £3m have to pay 0.5% of their salary bill into a ring-fenced apprenticeship levy pot. The money is collected monthly via PAYE and must be spent within 24 months and used for training on approved apprenticeship schemes (such as the Level 4 Data Analyst Apprenticeship that we offer).
What does 20% off-the-job training mean?
Off-the-job training is defined as learning which is undertaken outside of the day-to-day work duties and it must take place within the apprentice’s normal working hours.
Our off-the-job training is delivered on a flexible basis and can be carried out at the apprentice’s place of work or from home.
The 20% off-the-job training provides learners with the time to focus and develop the required skills, knowledge and behaviours to achieve the apprenticeship.
How much do managers need to be involved?
Managers will need to ensure apprentices achieve the 20% off-the-job training hours and work on their project portfolio.
We also encourage managers to have regular one-to-one meetings with apprentices to catch up on how they are progressing and to join the apprentice and their coach for thirty minutes every 3-4 months for a general catch up about the programme.
Register your interest
Fill out the following form and we’ll email you within the next two business days to arrange a quick call to help with any questions about the programme.
We look forward to speaking with you.
Who's benefitted from our academies
Read case studies on the impact we have made for our clients.
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