Confident Data Skills 2nd Edition - How to Work With Data and Futurproof Your Career

Data has dramatically changed how our world works. Understanding and using data is now one of the most transferable and desirable skills. Whether you're an entrepreneur wanting to boost your business, a jobseeker looking for that employable edge, or simply hoping to make the most of your current career, Confident Data Skills is here to help. This updated second edition takes you through the basics of data: from data mining and preparing and analysing your data, to visualizing and communicating your insights. It now contains exciting new content on neural networks and deep learning. Featuring in-depth international case studies from companies including Amazon, LinkedIn and Mike's Hard Lemonade Co, as well as easy-to understand language and inspiring advice and guidance, Confident Data Skills will help you use your new-found data skills to give your career that cutting-edge boost. About the Confident series... From coding and web design to data, digital content and cyber security, the Confident books are the perfect beginner's resource for enhancing your professional life, whatever your career path.

Product details

• Authors: Kirill Eremenko
• Publisher: Kogan Page
• Languages: English
• Product format: Paperback
• Released: 30.06.2020
• EAN: 9781789664386
• ISBN: 978-1-78966-438-6
• No. of pages: 304
• Dimensions: 137 mm x 214 mm x 17 mm
• Series: Confident Series; Confident
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; Social sciences, law, business > Business; BUSINESS & ECONOMICS / Entrepreneurship, Entrepreneurship, BUSINESS & ECONOMICS / Skills, BUSINESS & ECONOMICS / Careers / General, BUSINESS & ECONOMICS / Personal Success, Advice on careers & achieving success, Advice on careers and achieving success, COMPUTERS / Data Science / Data Visualization, Data analysis: general, Data science and analysis: general, Entrepreneurship / Start-ups, Data capture and analysis, Data Capture & Analysis