Limited-time offer:
Coaching until you reach your goals

Register and pay for the upcoming intake of the Career Accelerator before 10 June and get free, extended 1:1 coaching until you achieve your career goal.

Variant A

Data Science With Machine
Learning & AI Career Accelerator

Gain advanced data science skills, hands-on project experience, and industry insights to excel in your career.

Programme Duration: 7 Months, 100% Online
Start date: 7 October 2024
Accepting late registrations until 21 October

Limited places available - past intake fully subscribed

Limited places available - past intake fully subscribed

Machine Learning and AI Focus

Gain advanced skills in Machine Learning and AI | Covering topics like NLP, time series analysis, and generative AI

Time commitment

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

Support

One-to-one career coaching | plus bi-weekly mentoring with industry experts

Start date icon

Portfolio development

Work on 20+ industry-relevant projects | including a 6-Week project with the Bank of England

Payment plans

Flexible payment options available | 6-9 months + StepEx (Interest-free payment plan)

Discover the future of data science

Watch the programme trailer to see how the Data Science With Machine Learning & AI Career Accelerator can transform your career. Learn about the advanced skills, industry projects, and personalised support that sets our programme apart.

NEXT INTAKE: 7 October 2024
Data Science With Machine
Learning & AI Career Accelerator
NEXT INTAKE: 7 October 2024
Data Science With Machine
Learning & AI Career Accelerator

Why choose this Career Accelerator

Our programme ensures that your data science skills are not only advanced but also aligned with real-world business needs, providing you with a competitive edge. Throughout this Career Accelerator, you will:

Develop a portfolio of real-world projects based on challenges set by leading employers.
Work on 20+ industry-relevant projects, including a 6-week project with the Bank of England, to showcase your practical skills and expertise.

Learn the advanced tools, techniques, and skills from the foremost academic and industry practitioners, currently being promoted by data professionals.
Gain hands-on experience with cutting-edge technologies and methodologies used in today's data science and AI landscape.

Master the essential statistical concepts and principles to future-proof your data science career in the era of AI and Machine Learning.
Understand and apply advanced statistical techniques and machine learning algorithms to solve complex business problems.

Cultivate your ability to think commercially by tackling business challenges presented throughout the programme.
Learn to align data science solutions with business objectives to drive impactful results.

Become a more holistic practitioner by understanding how to make data science models implementable within business.
Learn the practical aspects of deploying machine learning models and ensuring their scalability and efficiency in real-world scenarios.

Set yourself apart by demonstrating legal, moral, and ethical responsibility and awareness of cutting-edge technologies.
Gain insights into the ethical considerations and regulatory requirements associated with data science and AI applications.

Deep dive into Generative AI and Large Language Models in Course 4.
Explore the latest advancements in Generative AI, including instruction tuning, reinforcement learning from human/AI feedback, and parameter-efficient fine-tuning, preparing you for the future of data science.

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What our learners say

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 - Career Accelerator Graduate

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

    Develop critical statistical thinking and problem-solving skills.

    Learn how to apply unsupervised learning to solve business problems.

    Gain proficiency in feature engineering and statistical analysis to drive business insights.

  • Course 2

    Solving Business Problems with Supervised Learning

    Master supervised learning techniques including regression, classification, and ensemble methods.

    Build and optimise machine learning models to generate actionable business insights.

    Explore deep learning methods to uncover hidden patterns in complex datasets.

  • Course 3

    Applying Advanced Data Science Techniques

    Dive deeper into advanced machine learning models, NLP and Time Series Analysis.

    Understand the intricacies of neural networks and deep learning.

    Leverage frameworks like TensorFlow for efficient model development and tuning.

  • Course 4

    Exploring the Future of Data Science + Capstone Employer Project

    Engage in advanced topics in Generative AI and other large language models (LLMs).

    Learn cutting-edge techniques like instruction tuning, reinforcement learning from human/AI feedback, and parameter-efficient fine-tuning.

    Work on a culminating project to showcase your skills and competencies, collaborating with leading employer partners on real-world data science problems.

  • Tools & Languages:

    Google Colab, GitHub, Python, TensorFlow, LangChain, Hugging Face and more

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

Capstone Project with the Bank of England

Apply your knowledge to real-world problems using Generative AI and LLMs. Present your findings to industry professionals and receive invaluable feedback.

Generative AI and LLMs:

Explore the latest advancements in Generative AI, including instruction tuning datasets, reinforcement learning, and low-rank adaptation for fine-tuning models.

Frameworks and Methodologies:

Learn about frameworks like Langchain, retrieval-augmented generation (RAG), and techniques to enhance and assess the performance of language models.

Real-World Applications:

Apply your knowledge to a significant business problem, presenting your findings to industry professionals and gaining invaluable feedback..

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

Learn from Leading Experts

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 The 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.

Alexander Smirnov

Data Science Consultant

Alex advises merchants and banks on applying data science to improve their sales performance. In his previous roles Alex consulted clients on the issues of analytics and finance across multiple sectors, including energy, transport, and fixed income markets. Alex holds an MSc Financial Economics from Oxford and MSc Machine Learning from UCL. He has also successfully completed all CFA and CAIA examinations.

FAQ's

  • What is the cost of this programme?

    The tuition fee for this programme is £8,395 £7,895* (upfront). Benefit from a reduced rate by making payment upfront, prior to the start of the programme, or ask an 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 StepEx, 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.

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