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Career Milestone Guarantee

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 — whether you're changing fields or advancing in data science.

Includes up to 12 months of 1:1 coaching, extended free if needed, until you reach your milestone*

Starts 27 Oct 2025
Apply by 20 Oct 2025

7 Months part-time and 100% online. Requires 20 hours per week.

Support includes 12 months of 1:1 career coaching plus bi-weekly mentoring with industry experts

This is not a bootcamp; it’s not where you go to learn to code, it’s where you go to actually become a fully-fledged data scientist.

Giwa
Career Accelerator Learner

Get more info

Complete the form below to receive more information about the Career Accelerator curriculum, programme fees, how you’ll learn, and how we’ll coach you one-to-one until you reach your goal. You will be redirected to the programme brochure on submission.

Why choose this Career Accelerator?

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

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.

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

Learn the practical aspects of deploying machine learning models and ensuring their scalability and efficiency in real-world scenarios.

Set yourself apart with insights into the ethical considerations and regulatory requirements associated with data science and AI applications.

Prepare for the future of data science by exploring the latest advancements in generative AI and large language models, including instruction tuning, reinforcement learning from human/AI feedback, and parameter-efficient fine-tuning.

Benefit from a structured learning experience with personalised career coaching and a network of peers, providing support and guidance every step of the way.

Enhance your professional credibility with a data science qualification from a world-renowned institution, giving you a competitive edge.

Programme Curriculum

Bridge the gap between theoretical knowledge and practical application

with a comprehensive and industry-relevant curriculum that covers the advanced tools, techniques, and skills that are currently getting data professionals promoted.

Tools & Languages

- 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 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.

Career Milestone Guarantee

Outcomes, not just a course: 1:1 Coaching + Our Milestone Guarantee

Start with your coach in Week 1 and keep them for a full 12 months from programme start. If you haven't hit your agreed milestone by month 12, we extend coaching for 6 more months—free. No job placement guarantee; terms apply.

12-month 1:1 Coaching

Operate at the next level.

1:1 coaching that upgrades judgment, confidence, communication, and execution

Strategic thinking under uncertainty
Stakeholder narratives that land
Evidence you can point to (projects, case studies)
A system that sustains momentum beyond Month 12*

*If you haven’t reached your agreed milestone by Month 12, the Guarantee extends coaching a further 6 months—free. T&Cs apply

Career Milestone Guarantee

If you don't hit your goal, we extend.

Qualifying milestones: new role, promotion or pay raise, paid consulting, or an agreed alternative
If not achieved within 12 months, we extend 1:1 coaching for 6 months at no cost
No job placement guarantee. See full T&Cs

Programme
(7 months)

1:1 Coaching
(up to 12 months)

Guarantee
(+6 months if needed)

Ready to start your data science career journey with guaranteed support?

Live business project with industry leaders

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, present your findings to industry professionals and gain invaluable feedback.

Learn from leading experts

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

Who is this programme for?

This programme is for you if you:

Already possess some foundational knowledge in data science or a related field and are seeking to formalise your skills, gain real experience, and accelerate your career trajectory.

Desire to transition into a practical, industry-focused data science role from academia or a related quantitative field like engineering or economics.

Are looking to develop an impressive portfolio of business-led projects that showcase your abilities to potential employers.

Value structured learning with the support of industry experts, career coaching, and a network of like-minded peers.

Want the credibility and recognition of a qualification from University of Cambridge Professional and Continuing Education to bolster your professional profile.

FAQs

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 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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