Data Science
Career Accelerator

Build the skills, project experience, and commercial mindset to succeed as a leading data scientist in the world of business.

7 months, online

4601 people already shown interest in this programme

Start Date

24 June 2024

(Apply by 17 June)

Time commitment

20 hours per week, 7 months online learning (plus break weeks)

Support

One-to-one career coaching plus bi-weekly mentoring with an industry expert

Start date icon

Portfolio development

Work on 20+ industry-relevant projects and assignments, including a live 6 week project with the Bank of England

Payment plans

Flexible options available (6-9 months + EdAid, an interest-free payment plan.

The time to advance your data science career is now.

Why choose this Data Science Career Accelerator

The aim of this programme is to ensure that acquired data science skills and competencies are purposeful, aligned with real-world business needs, and offer the depth required to ensure a competitive edge. Throughout this Career Accelerator, you will:

develop a portfolio of real-world projects based on challenges set by leading employers

learn the advanced tools, techniques, and skills from the foremost academic and industry practitioners, currently being promoted by data professionals

master the essential statistical concepts and principles to future-proof your data science career in the era of AI

cultivate your ability to think commercially by tackling business challenges presented throughout the programme

become a more holistic practitioner by understanding how to make data science models implementable within business

set yourself apart by demonstrating legal, moral, and ethical responsibility and awareness of cutting-edge technologies.

spacer

This Data Science Career Accelerator from the University of Cambridge Institute of Continuing Education is focused on shaping the future of business through data. It's not just about algorithms, statistics, or utilising AI and Machine Learning techniques; it’s also about generating meaningful, actionable insights that can challenge conventional wisdom and enable commercial success

Dr. Ali Al-Sherbaz
Assistant Professor and Academic Director for Digital Skills courses at University of Cambridge Institute of Continuing Education

This isn’t your typical online programme or boot camp.
This is a Career Accelerator.

A rich career-first learning experience tailored to help you go further, faster.

Cultivate your technical, business and human skills

Don’t just learn to perform the role, learn to make a real impact. Develop the critical human and commercial skills that will set you apart from other data scientists.

Prove yourself in real-world projects

Apply your learning by tackling data science challenges with real employers. Work as a team, build a powerful portfolio and showcase your hands-on experience and problem-solving skills.

Advance your development goals with a personal career coach

Work with a dedicated career coach and success manager to proactively set your career goals and build the path that gets you where you want to go.

Learn from leading academics and industry experts

Study from experts at the University of Cambridge and from industry, and earn a valuable certificate from the University of Cambridge Institute of Continuing Education.

Develop a portfolio of real-world projects based on challenges set by leading employers

We are thrilled to be collaborating on the Employer Project to not only provide the learners with the unique opportunities to practise data science on offer at the Bank of England, but to also give us the opportunity to reach a broader pool of potential talent from diverse backgrounds and experience who we know have the skills we need to help us achieve our mission.

James Benford
Chief Data Officer at Bank of England

What you could earn as a Data Scientist per year

Get started today

Download Brochure

Applications for this Data Science Career Accelerator are now open.

Graduates of Career Accelerators have been employed and promoted at these top companies

Meet a Career Accelerator past learner

The Career Accelerator has opened up a whole world that I never knew was out there before. I love what I do… but sometimes I felt like, “what’s next?“ But now there’s so much opportunity – so many doors have opened up for me…

Haroon Miah

Programme Details

Learn the advanced tools, techniques, and skills that are currently getting data professionals promoted.

  • Course 1

    Applying statistics and core data science techniques in business

    What you’ll learn

    Critical thinking and problem solving

    Statistical skills for data science

    Applying feature engineering

    Unsupervised learning

  • Course 2

    Solving business problems with supervised learning

    What you’ll learn

    Machine learning concepts

    Linear/polynomial/logistic regression

    Decision trees, random forest

    Ensemble methods: Bagging and boosting

    XGBoost

    Neural networks and deep learning (Tensorflow)

    Model tuning

  • Course 3

    Applying advanced data science techniques

    What you’ll learn

    NLP

    Time series analysis and forecasting

    MLOps (Modelling: Deployment, monitoring and assessment) is taught in each of the courses.

  • Course 4

    Exploring the future of data science, with a live business project

    Generative AI, Chat GPT and other LLMs - ethical AI and business applications

    Culminating project to showcase the range of skills and competencies gained throughout the course. Collaborate effectively within a cross-functional team, using multidisciplinary approaches to solve complex real-world problems set by leading industry partners, and create strategies that maximise potential business value

  • Tools/Platforms

    Google Colab, Jupyter Notebook and GitHub

    Programming Language: Python

  • Benefit from 1:1 executive coaching

    • Benefit from six 1:1 coaching sessions that provide tailored career advice, aiming to enhance your professional growth in data science. The sessions focus on your unique career aspirations, tackling your questions, and equipping you with practical strategies for success.
    • Participate in four group sessions that address essential career topics, such as how to set meaningful career goals and stay on track, managing your mindset for career success, navigating imposter syndrome with confidence, and forming effective teams.
    • These sessions offer a shared learning experience, enabling you to gain insights from your peers while understanding the broader context of your career journey.

Who you’ll learn from

This programme brings together academic and industry perspectives to design, build and deliver a curriculum that represents the best of both worlds.

Dr. Ali Al-Sherbaz
PhD, MSc, BSc, Electronic and Communications Engineering

Assistant Professor in Digital Skills at University of Cambridge Institute of Continuing Education

Author of more than 80 peer-reviewed papers with expertise in Cybersecurity, IoT, Data Science, AI, Blockchain and 5G. Passionate about guiding research and innovation strategies.

Shanup Peer
MBA, Operations/Marketing, MS, Electrical Engineering, B.Tech, Electrical and Electronics Engineering

Data Scientist and Programme Industry Expert

Principal Data Scientist, AI Curriculum Architect and Data Science Mentor, having fulfilled engagements with Government entities and corporate clients, developing technology solutions that have been deployed on a country-wide scale.

Robert Hardman
Chief AI & Innovation Transformation Officer, Inchcape Digital

Robert is an industry trailblazer with a career spanning over 25 years working with Fortune 100 companies, such as Facebook and Uber, guiding them through digital business transformations. His command over advanced mathematical techniques and knowledge of global technological ecosystems has made him a specialist in employing state-of-the-art technologies such as Generative AI, LLM’s, ML to transform & reimagine businesses.

Dr. Alexia Cardona
BSc, MSc, PhD

Training Programme Lead in Data Science at Newnham College, University of Cambridge.

Alexia is also a Tutor and Postgraduate Mentor at Newnham College, and a Senior Teaching Associate in the Department of Genetics. Her research interests focus on teaching and learning in the areas of data science, reproducibility, and Bioinformatics.

Dr Giovanna Maria Dimitri

Assistant professor in deep learning and artificial intelligence, University of Cambridge

Giovanna is a researcher at the University of Siena. She completed her Master's and PhD in Computer Science at the University of Cambridge under the supervision of Prof. Pietro Liò, focusing on Artificial Intelligence and Machine Learning for biomedical data processing at the Department of Computer Science. She has a research publication record of over 45 papers in peer-reviewed and international journals, as well as broad experience in teaching and supervising. She has been interviewed by several journals and TV shows in Italy for her expertise in Artificial Intelligence and Computer Science and has considerable experience in science communication events. Her research interests focus on artificial intelligence, in a wide spectrum of applications, as well as in the development of foundational models.

Dr Russell Hunter

PhD Computational Neuroscience, Senior Teaching Associate (Online Education and Web Technology), Department of Engineering, University of Cambridge

Dr Hunter's varied career has spanned industry, research and teaching. His PhD was in the field of Computational Neuroscience, and his research has focused on image processing and computer vision in Formula One motor racing. He continues his research as a Post Doctoral Candidate in the Department of Engineering, developing novel educational tools. Dr Hunter is also R&D in a personalisation team, working with big data, data science, and machine learning to develop industry-first products from end-to-end. In this role, he leads on innovation strategy.

Jon Howells

AI and Data Science professional and founder of AI consultancy, Qualifai

Jon Howells is a seasoned AI and Data Science professional with a decade of experience in the field. He runs an AI consultancy called Qualifai and is currently working on a book titled "Data Science for Decision Makers". Jon has worked with various companies, including Nestlé, Unilever, and Capgemini, developing and deploying data science services and solutions. He holds a Master's degree in Computational Statistics & Machine Learning from UCL. Jon is particularly interested in the application of Large Language Models (LLMs) in consumer-focused businesses, such as leveraging LLMs for consumer research and feedback analysis, personalised content generation, and enhanced customer support, ultimately helping businesses better understand and engage with their customers.

Jack Gannaway

Data Analytics Leader and founder, Future Consulting

Jack Gannaway has been working in data analytics and data science across the UK and Netherlands for the past 16 years. Spanning roles in both the public and private sector, his work has focussed on how to support decision-making with data.
Throughout his career Jack has worked with a huge variety of data, models and methodologies including demand modelling, b2b cross-sell prediction, predicting bankruptcy using accounting data, discrete event simulation and his favourite, dynamic stochastic microsimulation.

Diwakar Patwal

Head of Data Science and Chief Data Officer, Doji

Diwakar is leading the Data and AI practice at Doji, a UK based tech start-up which is reinventing the way consumers buy and sell refurbished electronics. He has had a long global career in building Data Science and AI solutions across the financial services, e-commerce and logistics industry.Developing complex ML and AI solutions in marketing optimisation, operational automation, customer engagement and logistics optimisation have been some of his career highlights. He has leveraged advanced machine learning techniques such as Computer Vision, Natural Language Processing, LLMs and Supervised ML models to deliver effective and impactful solutions.

Jack Gannaway

Data Analytics Leader and founder, Future Consulting

Jack Gannaway has been working in data analytics and data science across the UK and Netherlands for the past 16 years. Spanning roles in both the public and private sector, his work has focussed on how to support decision-making with data.
Throughout his career Jack has worked with a huge variety of data, models and methodologies including demand modelling, b2b cross-sell prediction, predicting bankruptcy using accounting data, discrete event simulation and his favourite, dynamic stochastic microsimulation.

More academic and industry educators to be announced

FAQ's

  • What is the cost of this programme?

    The tuition fee for this programme is £8,000 including VAT. Ask your Enrolment Advisor about our flexible payment plans. 

  • Do you have flexible payment options available?

    We have a variety of flexible payment options available for this programme. We also offer EdAid, a 24-month, interest-free payment plan.

  • Do I need to attend classes at certain times?

    The majority of learning requirements can be completed asynchronously, in your own time. While attendance is strongly recommended for live webinar sessions and masterclasses, recordings will be made available at the conclusion of each session.

    Live classes run mid-week and outside of standard working hours.

  • Why should I choose a Career Accelerator?

    Career Accelerators deliver the technical skills needed to perform in real-world roles, the understanding necessary to translate those abilities into meaningful value, the human skills crucial for gaining and retaining jobs, and the reflective capabilities essential for ongoing growth.

  • How is the programme delivered?

    The programme is delivered entirely online through a virtual learning environment which is accessible from your personal computer or smartphone. Your personal success manager will be available to offer support and guide you through your learning journey.

  • What are the entry requirements?

    This is an advanced data science programme, therefore there are a few prerequisites before the learner can enrol, these include:


    • an undergraduate degree that features at least one unit of quantitative studies (such as mathematics, statistics, accounting or finance)
    • at least 1 year of work experience in a field broadly related to data or business analytics
    • an IELTS certificate with an overall band score of 7.0 with no less than 7.0 in speaking, listening, and writing, and 6.5 in reading – if English is not your first language
    • Foundational technical skills, which include:
      • the ability to interpret data and analytic output and draw conclusions that help to inform data-driven decision-making
      • basic Python programming skills (if you don't have these skills yet, don't worry, we have a few free courses to get you prepared)
      • practical experience in accessing, manipulating, querying, and analysing data using a range of software and tools, including Python for data analysis (e.g. NumPy, Pandas, scikit-learn), Python for data visualisation (e.g. matplotlib, seaborn) and SQL
      • knowledge and application of statistical principles for descriptive analysis.

    In some cases, we can be flexible with certain requirements. For example, if you lack an undergraduate degree we may still be able to accept your application if you are able to demonstrate equivalent professional experience.


    If you are unsure whether you meet the requirements, please speak to one of our enrolment advisors.

  • Do I need to provide any supporting documents?

    As part of the application process you will be required to provide a copy of an academic transcript, a one-page CV or LinkedIn profile, an IELTS certificate (if relevant) and a personal statement (up to 500 words). Depending on your education history and work experience you may be required to pass a short technical test.

  • What is the role of industry and employer partners in the Career Accelerator?

    The employer partners add industry experience to coursework development, share tech expertise, and play a direct role in the portfolio project design. Through their insight into the ever-changing landscape in the digital economy, they ensure students develop skills aligned to workplace demand, equipping them for job opportunities.

Please note: University of Cambridge ICE is in the process of developing this programme and details are subject to change.

spacer

CONTACT

cambridge.ice@fourthrev.com

CONNECT WITH US

Footer_ICE-FR Logo