Build a Career in Data Science Gratis E–pub
I work with MS Analytics students at a large university and I think this book is a great resource for anyone interested in a career in data science Very ractical A Z guide to entering the exciting field of data analytics data science Highly recommend I m looking to otentially jump from engineering to data "SCIENCE BUT LET S BE REAL SWITCHING CAREERS ISN "but let s be real switching careers isn to be done on a whim This book has rovided genuine insight as to the ins and outs of this career and a few aths on how to get there It was exactly what I was looking for in exploring a otential career moveI appreciate knowing what the bumps are in a young field how management might view the osition what to Summary You
are going togoing to technical knowledge to succeed as a data scientist Build a Career in Data Science teaches you what school leaves out from how to land your first job to the lifecycle of a data science roject and even how to become a manager Purchase of the rint book includes a free eBook in PDF Kindle and ePub formats from Manning Publications About the technology What are the keys to a data scientist's long term success Blending your technical know how with the right soft skills turns out to be a central ingredient of a rewarding career About the book Build a Career in Data Science is your guide to landing your first data science job *And Developing Into A *developing into a senior employee By following clear and simple Ook for in otential organizations where jobs might be found Knowing there s a glut of *Talent And How To Work *and how to work in this area is also valuable switching in from another discipline This book is great It takes a warm approach to learning about entering the field of data science This was helpful to me because they describe what different data science jobs and what you can expect from different types of companies However "it s also very discouraging because they basically tell you that " s also very discouraging because they basically tell you that you ll have thousands of eople competing with you for every job and Lignin Biodegradation people are getting degreesfinishing bootcamps all the time 2 large companies like Google or Facebook won t eve. Nstructions you'll learn to craft an amazing resume and ace your interviews In this demanding rapidly changing field it can be challenging to keeprojects on track adapt to company needs and manage tricky stakeholders You'll love the insights on how to handle expectations deal with failures and Pure Chance plan your careerath in the stories from seasoned data scientists included in the book What's inside Creating a The Lady and the Lionheart portfolio of data sciencerojects Assessing and negotiating an offer Leaving gracefully and moving up the ladder Interviews with rofessional data scientists About the reader For readers who want to begin or advance a data science career About the author Emily Robinson is a data scientist at Warby Parker Jacueline Nolis is N look at you unless your from an ivy league "School 3 If You Work For A Company Like A " 3 if you work for a company like a government contractor then you ll never get to work on anything new or excitingI mean I appreciate the realistic attitude instead of most
CAREER BOOKS THAT ARE FULL OF FLUFF BUT Ibooks that are full of fluff But I had to stop reading it because it was depressing and discouraging I loved this book Super ractical advice that I was I had when I had graduated university but I also found it entertaining and interesting to read as the authors did a great job writing it and letting their experience shine through The additional interviews with data scientists at the end of the chapters were excellent as well. Data science consultant and mentor Table of Contents PART 1 GETTING STARTED WITH *DATA SCIENCE 1 What Is Data Science *SCIENCE 1 What is data science Data science companies 3 Getting the skills 4 Building a ortfolio PART 2 FINDING YOUR DATA SCIENCE JOB 5 The search Identifying the right job for you 6 The application Résumés and cover letters 7 The interview What to expect and how to handle it 8 The offer Knowing what to accept PART 3 SETTLING INTO DATA SCIENCE 9 The first months on the job 10 Making an effective analysis 11 Deploying a model into roduction 12 Working with stakeholders PART 4 GROWING IN YOUR DATA SCIENCE ROLE 13 When your data science roject fails 14 Joining the data science community 15 Leaving your job gracefully 16 Moving up the ladder. .