WEBINAR

Programme Q&A with faculty:
Data Science Career Accelerator

Wednesday, 21 February at 12 pm (GMT) Online

What is a Career Accelerator; will I meet the entry requirements; what skills will I enter the job market with; how will a Career Coach help me achieve my goals?

These are some of the questions we’ll discuss in our Q&A with the Cambridge ICE faculty who designed the Data Science Career Accelerator. Walk away from the session knowing if this programme is the right fit for you and your career goals.

What you’ll learn during this session

Why data science is a critical skill in the digital economy, and what you can look forward to in the field – as told by experts.

The tools, languages and software you’ll gain on the Career Accelerator, and how they’ll give you an edge in the job market.

The features that make this Career Accelerator unique, like career coaching and the 20+ practical projects.

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What you'll take away

Meet the experts:
Gain unique insight into the programme content from the academics who designed it, plus the live six-week business project run by The Bank of England.

Data resources:
Understand the workplace-ready skills you could walk away with, and get access to resources and insights to help you go further in your career, faster.

Get your questions, answered:
Speak to the academics you’ll learn from and understand the enrolment process and on-programme support available.

 

Speakers

Daniel Cairns

HOST

Head of Enrolments at FourthRev

Dr. Ali Al-Sherbaz

Assistant Professor and Academic Director for Digital Skills courses 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. Ali is passionate about guiding research and innovation strategies.

Dr. Alexia Cardona

Training Programme Lead in Data Science at the Department of Genetics, 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.

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CONTACT

cambridge.ice@fourthrev.com

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