Grow in-house Data Science capabilities within your teams utilising Apprenticeship Levy funding

Cambridge Spark is a leader in personalised Data Science training. We offer intensive bootcamps, apprenticeships, graduate schemes and bespoke corporate training courses that are delivered by industry and academic experts, complemented by our proprietary AI-powered data science talent development platform, K.A.T.E.®.

Our team consists of field specialists and come from a range of backgrounds, including PhDs and Researchers in Machine Learning from Cambridge University, Oxford University and UCL - as well as Developers with industry experience from leading companies including Google, Microsoft Research, Amazon, Morgan Stanley and Oracle.

About us

Selection of Clients and Engagements

University Tech Recruitment Talent PipelineJPMC Data Science Academy Internal Skills Assessment

Applied Data Science Part-time Bootcamp

Two week Internal Data Science BootcampApplied Data Science Bootcamp Project Partner

Data Science Training for Executives

Introduction to Data Science in Python Private Training Course

University Tech Recruitment Talent PipelineApplied Data Science Bootcamp Project Partner

3Data Science Graduate Recruitment

Our Process

TrainingOur modularised curriculum comprises of comprehensive lectures led by industry experts, interactive Python notebooks with exercises and solutions, industry projects to complete using K.A.T.E.®, and further reading materials to help students get the most out of the experience. Each module approximately requires 10 hours of work, per week.

AnalyticsK.A.T.E.® features an analytics and monitoring dashboard for management and stakeholders to track employee progression, performance and scores on project assignments to ensure ROI along the learning journey.

AssessmentK.A.T.E.® is a proprietary adaptive assessment learning system. When training with Cambridge Spark, participants use K.A.T.E.® to conduct continuous learning projects and receive immediate feedback on their code submissions. This ensures your employees get the personalised support they need to maintain their momentum.

SupportWe have an integrated support system to ensure students prosper. Students will have access to personalised, immediate feedback on assignments via K.A.T.E.®, quarterly diagnostic sessions and access to our Slack channels to encourage ongoing communication, collaboration and peer-to-peer learning. Students can also utilise our ticketing system built into K.A.T.E.® to ask for help and specific feedback.

Python

Throughout the programme, students will focus on embedding the best-practices of applying advanced Data Science tools and techniques with Python; an easy-to-learn general-purpose programming language that’s powering the world’s leading companies.

This “most-searched-for language” sits in the top three programming languages used in the world, with nearly 40% of developers working with Python, and a further 25% wishing to do so. It’s also widely adopted in industry and currently used by Pixar for producing films, Netflix for recommending content and Google for crawling the web, amongst many other innovative giants.

“The language’s two main advantages are its simplicity and flexibility. Its

straightforward syntax and use of indented spaces make it easy to learn, read and

share.”

– The Economist

The Four Analytic Capabilities

Our curriculum ensures students will gain and reinforce the technical capabilities and competencies required to perform different types of analytics, from descriptive and diagnostic analysis to provide business insights, through to predictive and prescriptive analytics to develop business solutions.

Descriptive: What happened? Example: What is the turnover this month?

Diagnostic: Why did it happen? Example: In your monthly report, you can see that last month’s sales performance declined. What caused this?

Predictive: What will happen? Example: Imagine you are a retailer and you want to maximise product sales while minimising waste. How can you accurately forecast how much stock you need?

Prescriptive: What should I do? Example: Based on the traffic predictions, what are the best marketing initiatives you can put in place to maximise the prospects-to-lead ratio?

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Libraries and Technologies

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Students will gain experience of working with the complete Data Science toolkit, comprising of the following widely used languages and libraries.

Apprenticeship-Levy Funding and Curriculum

Apprenticeship Levy Funding

The apprenticeship levy is paid by organisations with a staff bill of over £3m/annum

Money can be used for approved apprenticeship programmes for new and existing staff by UK-based organisations

Unclaimed levy funding paid to HMRC expires after 24 months if not used for training

Curriculum and training is highly regulated to ensure effective transfer of skills into the workplace

Training delivery must combine learning on the job with 20% time off the job

Cambridge Spark is a BCS accredited training partner. We currently offer the Data Analyst Apprenticeship Standard (https://bit.ly/2ClVvco). End point assessment is provided by BCS.

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Data Science Apprenticeship Curriculum

Achieve wider organisational transformation by building an internal Data Science Academy

If you’re an organisation paying the apprenticeship levy, and you need to bring new data skills into the organisation,  then the levy funding represents an opportunity to create an internal data training academy to upskill cohorts of relevant staff. This approach is used by Cambridge Spark client, JPMorgan, to level up their current analysts.

Programme Summary- 13-month flexible programme with continuous support, designed to build Data Science skills and capabilities at scale

- 6 months Core Data Science (Level 1); 6 months optional advanced topics (Level 2)- Online platform with live-coded video lectures, Python notebooks with exercises and solutions, practical projects

and reading materials- Each online content module requires approximately 10 hours per week to complete- Personalised, immediate feedback on assignments via K.A.T.E.®- Bi-weekly diagnostic group sessions- Slack channels for ongoing communication, collaboration and peer-to-peer learning

- Follows a modularised structure of levels allows individuals with different experience obtain the best training suited for their background

- Participants gain the Data Science Associate certification from EMC

Level 1Compulsory Modules

Level 2OptionalSpecialisedModules

Module 1 - Building Foundations: Tools, Mathematics, and Best Practices for Data Scientists (4 wks)Module 2 - Exploratory Data Analysis, Feature Engineering and Linear Regression (4 wks)Module 3 - Classification, Hyperparameters Tuning and Model Evaluation (4 wks)Module 4 - Time Series Analysis and Clustering (4 wks)Module 5 - Cloud Computing and Databases (3 wks)Module 6 - Processing Big Data (3 wks)

Module 7 - Ensemble Methods and Machine Learning for Production (6 ws)Module 8 - Neural Networks and Deep Learning (6 wks)Module 9 - Natural Language Processing (6 wks)Module 10 - Recommender Systems, Pragmatic Evaluation and Model Interpretability (6 wks)End Assessment and Certification

Apprenticeship Curriculum

Prerequisites:- Prior Python programming experience - Mathematical aptitude including fundamentals of linear algebra and

statistics- Individuals plan to apply these skills in their job

An initial skill level assessment will be carried out by using K.A.T.E.® to baseline knowledge. 11

Capstone Project (4 wks)

Ensuring ROI

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Get the most out of your training using K.A.T.E.®

We invest in ensuring your training investments are effective, placing importance on:

Inspiring and helping your employees want to learn

- K.A.T.E.® (Knowledge Assessment Teaching Engine) provides immediate and personalised feedback to students to accelerate progress

- Offers personalised sets of exercises to help bridge skill gaps quicker and more effectively- Generates personalised further reading recommendations to support continuous learning

Alignment with the core business needs and objectives

- K.A.T.E.® supports custom content to match projects to your training requirements- Provides a fully integrated solution supporting git for version control- Performs source code analysis, correctness, quality, convention, Machine Learning metrics- Reports relevant learning analytics and diagnostics to benchmark code submissions

The transfer of knowledge into a Production environment

- K.A.T.E.® unique is focused on production-ready Data Science code rather than "toy" learning examples and exercises

- Emmerses participants in a simulated work environment

Further information about K.A.T.E.® can be viewed at: https://edukate.ai

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K.A.T.E.® for Learning and Development

Upskill, reskill and onboard team members quickly and effectively

K.A.T.E.® provides structured, expert-led data science and coding projects, enabling you to build internal Data Science capability and close technical skill gaps at scale.

key features of using K.A.T.E.® for Learning and Development:

- Customisable content supports your organisation’s needs and objectives

- Live-coded online videos, interactive exercises and project-based assignments offer an interactive, blended learning experience

- Instant personalised feedback and content recommendations to address each individual’s skill gaps

- Industry-simulated learning environment ensures the use of version control tools and coding best practices

- Monitoring and Analytics Dashboard enabling you to track progress and quantify improvement in technical proficiency

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Data Science Training for Professionals

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