What do readers say? "This book represents an essential guide to terminologies and techniques that anyone working in Recruitment, Talent or Human Resources for the Data Science industry should know. I strongly advise anyone who has ever sat, bemused, as Data Scientists try to explain what their work involves - absorb this book in its entirety" - Robin Huggins (Director of Academy & Client Services at MBN Solutions & Data IQ 100 recipient) "I love the concept of this book. Anything to help recruiters be more engaging and understanding of their customers is key to their success" - Alex Moyle (Founder of Recruiting Gym) A.I. is driving an unprecedented demand for Data Scientists For those searching for talent, whether in-house or agency side - this handbook will give you a competitive edge in what is a fast paced, rapidly growing, and highly technical field Author Andrew Jones leans away from mathematical notation and jargon, explaining all the concepts and tools commonly listed on job descriptions and CVs in a lightweight, interesting, and fun manner throughout. The learnings will get you closer to the distinct needs of your clients, and a richer understanding of candidate skill and experience - of course resulting in a boost to your efficiency, but no doubt also causing impressed chirrups from your clients as you freely discuss the difference between Convolutional & Recurrent Neural Networks, TensorFlow & PyTorch, Python & R, and more! You may also find you get a few slightly agitated “um’s and ah’s” from unscrupulous candidates who you now nab attempting to hoodwink you with technical buzzwords… The handbook covers - An introduction to the fascinating world of A.I - An exploration into the key components of a Machine Learning project, namely; Data, Features, Algorithms, and Models - A look at commonly used programming languages, and the differences between them - A high level run through of the essential tools, both Hardware and Software, that are heavily relied upon, as well as a look at how A.I. is being integrated in the Cloud - An overview of commonly used Deep Learning Frameworks and other key tools in the Data Scientist’s toolbox - A deep dive into the essential techniques & algorithms that are being used in the industry - A review of some ways candidates are choosing to learn & advance their skillset - and what to make of these when you see them on a CV - Thoughts, learnings, and a template for interviewing & screening candidates About the Author Andrew Jones has over 12 years experience in A.I., Data Science, and Machine Learning within the Digital, Retail, Telecoms, Travel, and Gaming industries. He has been heavily involved in technical recruitment throughout his career, including over 100 interviews during his time at Amazon.