Blog

Why develop Data Science & AI strategic capability in your organisation?

In this article, Cambridge Spark's CEO and Founder, Dr Raoul-Gabriel Urma, explains how to build capability that supports the Data Science and AI strategy of an organisation.

Apprenticeships: future proofing the workforce and promoting diversity in data science & AI

The world of work is changing fast. Data is the new currency and language, and it's everywhere. Yet many organisations are suffering from a lack of confidence in how to understand and use data. And even within data teams, a lack of diversity is holding us back.

The Year of MLOps

In this article, Cambridge Spark's CEO and Founder, Dr Raoul-Gabriel Urma, explains what MLOps is and why it is crucial for delivering successful Data Science and AI projects.

Data science apprenticeships; learning pathways for upskilling staff

Over the last decade, skills in data science and AI have become increasingly valuable for organisations of all sizes and across all sectors. But across the UK, there isn’t enough talent to meet the rising demand;

How data analysts are adding value to businesses in every sector

Data analysts are in high demand across all sectors as more and more businesses are working to harness their data to provide actionable insights. In this blog post, we take a look at the role and value of a data analyst, and how they can benefit businesses in a wide range of sectors.

5 data science skills your business needs - and how to get them

Data science can add enormous value to any business. It’s not just relevant for data-driven departments and roles, but is useful across a range of functions including marketing, logistics, and banking.

The benefits of 'learning by doing' in data science training

Many companies are choosing to build their data science capabilities from within, by upskilling their existing staff. But with so many data science training programmes available, how do you choose the right one for your team? When choosing a data science training programme, it's important to ...

Case study: Upskilling GSK staff with the Data Analyst Apprenticeship

GSK is a science-led global healthcare company that researches, develops and manufactures innovative pharmaceutical medicines, vaccines and consumer healthcare products.

5 Business Benefits of Data Analyst Apprenticeships

Your business alone is producing incredible amounts of data on a daily basis: about customers, user experience, web traffic, marketing effectiveness, and more.

6 benefits of virtual learning for data science training

It’s an exciting time for people working in data science. Around 90% of the world’s data has been generated over the past couple of years. 

Top 10 FAQ's Employers have About the Data Analyst Apprenticeship

The Apprenticeship Levy is making it easier for companies to upskill their employees with the tools and knowledge to succeed in today’s market. With a Data Analyst Apprenticeship (Level 4), your staff will learn how to collect, manage and analyse data to provide actionable insights for your ...

Choosing a Data Analyst Apprenticeship Training Provider: 7 Tips for Employers

Upskilling your team with a Data Analyst Apprenticeship can help you build the internal capabilities your company needs to succeed both now and in the future. But choosing an apprenticeship training provider can be a complex task.

Predicting Diabetes Progression Based on BMI, Using Linear Regression

In this tutorial, we will consider a very simple linear regression model, which is the backbone of several time series and high dimensional models (VAR, Lasso, Adalasso, Boosting, Bagging, to name a few).

The Apprenticeship Levy: helping companies fill the digital skills gap

The digital skills gap is being felt by businesses in every sector. 75% of UK executives are experiencing challenges in recruiting the digital skills they need. And IBM predicts that in 2020, data science will account for 28% of all digital jobs, but that many of these places will remain unfilled ...

Word Embeddings in Python with Spacy and Gensim

Word embeddings are vector representations of words, which can then be used to train models for machine learning.

Neural Networks in Python: From Sklearn to PyTorch and Probabilistic Neural Networks

This tutorial covers different concepts related to neural networks with Sklearn and PyTorch. Neural networks have gained lots of attention in machine learning (ML) in the past decade with the development of deeper network architectures (known as deep learning). 

Introduction to Text Classification

In this tutorial, we will explore a basic workflow to train and evaluate a model to classify text. Note that there are many important aspects not covered in what follows, such as exploratory data analysis (EDA) or hyper-parameter optimisation.

Interview with Capstone Project Partner: causaLens

Machine learning (ML) has quickly become an integral part of the financial sector, allowing forward-thinking executives to get an edge on the market. An article by Towards Data Science stated that 46% of large FinTechs and 30% of large financial institutions identified AI as the most relevant ...

Implementing your own recommender systems in Python

Nowadays, recommender systems are used to personalize your experience on the web, telling you what to buy, where to eat or even who you should be friends with. People's tastes vary, but generally follow patterns. 

Apprenticeship Series: The Age of Apprenticeships

So far this blog has been based on my perspective, so I asked my colleagues from a range of training programmes, to share the number one question they’re asked about apprenticeships. Unanimously, they replied:

Data Processing with Pandas Dataframe

The purpose of this tutorial is to teach you how to process data with Pandas DataFrame.

Production-ready code for Data Science at the BBC

Learn how Cambridge Spark helped the BBC data science teams embed best practice into their daily routines when they set out to change their software engineering landscape, in order to increase audience engagement, through targeting them with more relevant content. 

Apprenticeship Series: Fear of the Unknown

Welcome to October, the month of Halloween and all things scary. Something that has been worrying me recently is the confusion that remains about what apprenticeships are. It’s been more than two years since the levy became effective and levy-paying organisations still have concerning knowledge ...

An introduction to Uber’s new CoordConv architecture and its applications. 

In 2018, Uber AI Labs developed a new layer for the deep learning practitioner: CoordConv. This concept was explained and tested in their paper and a simpler summary was also provided in the form of a blog post. 

Data Analysis: Python vs Excel

Excel has been a firm favourite for working professionals for many years and for good reason. It has a large number of capabilities and its ease of use has meant that it’s played a critical role in all manners of business, education, finance and research. 

The Skills You Need to Become a Data Analyst

Apprenticeships Series: Why Trust Training Providers?

Welcome to my third blog on all things apprenticeships. This month will discuss why should employers trust apprenticeship providers when one in four businesses are unhappy with their provider. 

Applied Data Science Bootcamp Graduation, London - 14th September 2019

Saturday 14th September 2019 marked a special day for a group of individuals who have embarked on a six-month journey, upskilling and future-proofing their careers. 

Closing My Skills Gap With Data Science

Data Analysts: Who are they and What do they do?

In the last decade, there’s been a massive surge in the adoption of analytics to transform and optimise business processes and that trend is not going away. 

Six Data Science Podcasts You Need to Listen to

IMC student events

Apprenticeship Series: Fired Up About Diversity

Welcome to my second blog on all things apprenticeships. This month I’m burning to get you fired up and to spark some discussion around another hot topic in apprenticeships: their image problem. 

My Summer Internship at Cambridge Spark

Olivia competed against hundreds of applicants to land a 12-week Data Science internship within the technical team at our London office, working on our AI-powered learning and development platform, K.A.T.E.®.

Data Science: MSc or Bootcamp

This article might help you decide your next career choice. If you're unsure whether to do a Masters in Data Science or a Data Science Bootcamp, then this article will help give you some insight into the options available.

From Entomologist to Data Scientist

Six Free E-Books: Introductions to Python and Data Science

Take a look at the books we’ve chosen to help you develop and let us know what you think, or even if you’d like to see more posts like this! We’d love to hear from you.

Meet Matt: Our New Digital Marketing Analyst

Matt joined Cambridge Spark's commercial team in Cambridge to work on the digital marketing strategy for the business, including social media management and content curation.

Fast-track to Data Science

An interview with Applied Data Science Bootcamp graduate, Amanda Borg, on her journey of landing a new job as an Insights Analyst, as a result of the bootcamp.

Apprenticeship Series: Apprenticeships, Degrees & Politics

This is the first instalment to the Apprenticeship Series, which aims to provide updates and insights into changes within the field of apprenticeships.

Data Science Interviews: Unipart on Hiring

Utilising Data Science in Finance

An interview with Applied Data Scientist Bootcamp graduate, Damien Yahi, on his experience with Cambridge Spark and how he learned new skills to help him be more efficient in his job, whilst enhancing his future prospects.

Upskilling yourself as a Data Scientist

An interview with Applied Data Science Bootcamp graduate, Paulina Figol, on her journey of upskilling herself as a Data Scientist to landing two job offers as a result of the bootcamp.

From R to Python at ING

ING provides banking and financial services which empower people to stay ahead in life and in business. That means staying on the cutting edge themselves.

Meet Christina: Our New Account Executive

Meet Elisa: Our New Account Executive

Elisa joined Cambridge Spark's commercial team in Cambridge to help our students and those interested in data science realise their dreams by helping them get started on our Applied Data Science and Introduction to Python bootcamps.

Leveraging Data Science in Luxury eCommerce

An interview with Applied Data Science Bootcamp Alumnus and Senior Customer Insight Analyst, Andonis Pavlidis.

From Investment Management to Data Science

Meet Judit: Our New Office Manager

Brexit and Data Science

What can we make of the indicative votes in parliament? If you're following the Brexit process (who isn't in the UK!), you might be aware that MPs held indicative votes on the 27th of March, to vote on which steps they could stand behind for Brexit.

An Introduction to Plotting

Introduction I'm a teaching assistant for several MSc courses, covering natural language processing, natural language understanding, information retrieval and Python programming. Students on these courses, as part of their coursework, often have to produce visualisations of data. Usually, for these ...

Women in Programming

Applying Data Science tools and techniques to eCommerce

Data Science Interviews: Cytora on Hiring

6 Essential Tools for Data Science

Thanks to the incredibly active Data Science community, open source tools and libraries have become more trusted, reliable and scalable. 

Meet Tony: Our New Commercial Manager

Cambridge Spark is changing the way people learn Data Science and Software Engineering, and we're hiring driven and passionate talent to join us as we look to grow.

Core Data Science Training for PhD Research

Introducing Students to Careers in Data Science and Engineering

On the 24th November, we welcomed students from various universities based within the UK to our ‘Machine Learning in Finance: Time Series forecasting in Python’ workshop, enabling students to learn from experts about applying Data Science techniques to real-world data — specifically focusing on ...

An innovative talent acquisition and assessment strategy for IMC Trading

Candidate assessment is a key component in every talent strategy. They are designed to provide a way in which to measure performance and qualify candidates to perform a role. 

How to Become a Data Scientist (with no Programming Experience)

Deep Learning and Natural Language Processing (NLP) Training for Deloitte

"At Cambridge Spark, you have really exceptional trainers who are specialists in the field. We can definitely trust your team and your expertise."

Building Internal Capabilities to Develop Data Science Projects

Are you looking to build a data science team? This short guide walks through how EDF Energy approached this goal and built Data Science capability within their Sales & Marketing team using in-house training delivered by Cambridge Spark.

Applying Data Science Techniques to the Logistics Industry

Data Analysts vs Data Scientists - What's the difference?

Data Science and AI technologies are already having a major impact on business and society — from early and accurate diagnosis of medical problems, to building cost-effective operations, providing more accurate fraud detection and self-driving cars.

The Role of Data Science in Retail

The retail sector is adopting Data Science techniques to reduce costs, improve decision making and explore ways to do more with data. Use cases include:

Why Economists should embrace Data Science

Economists can make great data scientists and complement the skillsets of Data Scientists who have other backgrounds. I have a background in economics but branched out my skillset into Data Science more recently. Economics and Data Science actually have a lot in common.

Writing Impactful CV’s for Data Science roles

Your CV is often the first impression employers get of you. As with face-to-face meetings, impressions are created almost instantly, and you need show your relevance immediately.

The Role of Data Science in Research

In academia, new applications of Machine Learning are emerging that improve the accuracy and efficiency of processes, and open the way for disruptive data-driven solutions. For example, the implementation of Data Science in Biomedicine is helping to accelerate patient diagnoses and create ...

Build your own Skip-gram Embeddings and use them in a Neural Network

Applying Data Science to the Telecoms Industry

An interview with Matt Roberts, Strategic Analytics Manager at GiffGaff and Applied Data Science Online Bootcamp alumnus.

Project Partner Case Study: Entomics

Bringing Deep Learning and Natural Language Processing to Software Development

We spoke with Daniel Palma, Product Owner at Ocado Technologies, to talk about his experience of the six-month in-person Applied Data Science bootcamp at Cambridge Spark.

From Business Analyst to Data Scientist

What do companies look for when hiring Data Science candidates?

From Data Analyst to Data Scientist

Helping individuals upskill and become more employable is at the heart of what we do. Our part-time, Applied Data Science Bootcamp provides individuals with a comprehensive, structured programme to learn the necessary skills to become a data scientist. 

Learning Data Science as a Software Engineer

Sunny is a senior software engineer working in the energy sector. He completed the Applied Data Science Bootcamp to master new skills for his work and personal interest in AI for autonomous drones.

Data Science Interviews: FiveAI on Hiring

This interview forms the first part of an ongoing series which will provide insight into the Data Science sphere, including how diverse cross-industry roles are, applications of Data Science across different sectors and more insight into the hiring process to facilitate aspiring Data Scientists ...

Data Science Interviews: causaLens on Hiring

An interview with Maksim Sipos, CTO at causaLens This interview forms the second part of our ongoing ‘Data Science interviews’ series, providing more insight into hiring in the Data Science sphere to empower our community to get the roles they aspire for.

Practical Introduction to Recommender Systems

Deploying a machine learning model to the web

Data scientists often have to communicate results to other people. In my case, my supervisors might want to see some numbers or I have to write up the main insights of some work for a paper.

Collecting web data without an API

In this tutorial, we’ll show you how to extract data from Wikipedia pages. If you’ve ever gone through an online machine learning tutorial, you’re likely to be familiar with standard datasets like Titanic casualties, Iris flowers or customer tips.

A brief overview of big data machine learning and feature selection

I am sure that lately all of you have been hearing a lot about Machine Learning and I guess if you are here, you are curious to find out what it is. I will attempt to give you a very brief and modest overview of my view on Machine Learning.

EDA and interactive figures with Plotly

A crucial step of any machine learning attempt is getting a good impression of your dataset. Exploratory data analysis (or EDA) is one way to do this. It consists of summarizing the data with descriptive statistics and often involves extensive plotting. The web is full of plotting libraries that ...

Quick Panda tricks every Data Scientist should know

If you are new to the world of data science, Python's Pandas libraries are some of the best tools for quick data analysis. Pandas are built on Numpy, another popular Python library. 

Getting started with regression and decision trees

Regression analysis is one of the approaches in the Machine Learning toolbox. It is widely used in many fields but its application to real-world problems requires intuition for posing the right questions and a substantial amount of “black art” that can't be found in textbooks. While practice and ...

From simple regression to multiple regression with decision trees

In the previous post on simple Regression Analysis you learned how to use Decision Trees to create a regression model for predicting the number of bikes hired in a bike sharing scheme. You used the average temperature of a day to make the predictions. Now you will extend the model by also including ...

Implementing your own knearest neighbour algorithm using python

In machine learning, you may often wish to build predictors that allows to classify things into categories based on some set of associated values. For example, it is possible to provide a diagnosis to a patient based on data from previous patients.

Getting started with XGBoost

From Web Technical Lead to Data Science

An interview with Applied Data Science Bootcamp graduate, Sanjay Hallan, on his journey of landing a Data Science role at a new organisation within a month of graduating.

10 Things you’ve wondered about Data Science — FAQ #1.

As companies embrace the need to become “data-driven,” career opportunities in data science are increasingly available. It is an exciting and ever-evolving field, and data science skills are transferable across a range of sectors — so how can you get involved?

Acing the Data Science Interview: HR & competency interviews

This opinion post forms the second of our three part series ‘The Data Science Interview’ series, focusing on preparing for an interview, written by our expert guest blogger Dan Holdsworth, Data and Analytics Recruiter at People Genius.

Acing the Data Science interview: preparation and tests

This opinion post forms one of three parts of the ‘Data Science Interview series, focusing on preparing for an interview, written by our expert guest blogger Dan Holdsworth, Data and Analytics Recruiter at People Genius. So, you’ve gotten yourself an Interview for your first role as a Data ...

Acing the Data Science Interview: on the day

This opinion post forms the final part of our three part series ‘the Data Science interview’, written by expert guest blogger Dan Holdsworth, Data and Analytics Recruiter at PeopleGenius. What should I wear to a Data Science interview? My first tip for you: always check the dress code. Attending ...

A Beginners Guide to Kaggle Competitions