Data Science Careers, Training, and Hiring

Data Science Careers, Training, and Hiring
Author: Renata Rawlings-Goss
Publisher: Springer
Total Pages: 96
Release: 2019-08-02
Genre: Education
ISBN: 3030224074
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This book is an information packed overview of how to structure a data science career, a data science degree program, and how to hire a data science team, including resources and insights from the authors experience with national and international large-scale data projects as well as industry, academic and government partnerships, education, and workforce. Outlined here are tips and insights into navigating the data ecosystem as it currently stands, including career skills, current training programs, as well as practical hiring help and resources. Also, threaded through the book is the outline of a data ecosystem, as it could ultimately emerge, and how career seekers, training programs, and hiring managers can steer their careers, degree programs, and organizations to align with the broader future of data science. Instead of riding the current wave, the author ultimately seeks to help professionals, programs, and organizations alike prepare a sustainable plan for growth in this ever-changing world of data. The book is divided into three sections, the first “Building Data Careers”, is from the perspective of a potential career seeker interested in a career in data, the second “Building Data Programs” is from the perspective of a newly forming data science degree or training program, and the third “Building Data Talent and Workforce” is from the perspective of a Data and Analytics Hiring Manager. Each is a detailed introduction to the topic with practical steps and professional recommendations. The reason for presenting the book from different points of view is that, in the fast-paced data landscape, it is helpful to each group to more thoroughly understand the desires and challenges of the other. It will, for example, help the career seekers to understand best practices for hiring managers to better position themselves for jobs. It will be invaluable for data training programs to gain the perspective of career seekers, who they want to help and attract as students. Also, hiring managers will not only need data talent to hire, but workforce pipelines that can only come from partnerships with universities, data training programs, and educational experts. The interplay gives a broader perspective from which to build.

R for Data Science

R for Data Science
Author: Hadley Wickham
Publisher: "O'Reilly Media, Inc."
Total Pages: 521
Release: 2016-12-12
Genre: Computers
ISBN: 1491910364
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Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

IGNOU Data Science & Big Data

IGNOU Data Science & Big Data
Author: Manish Soni
Publisher:
Total Pages: 32
Release: 2024-11-10
Genre: Study Aids
ISBN:
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This book, "IGNOU Data Science and Big Data: Previous Years Unsolved Papers," has been meticulously compiled to serve as a vital resource for students pursuing this course. The collection of previous years' unsolved papers included in this book is intended to provide students with a clear understanding of the exam format, the variety of questions posed, and the key topics that have been emphasized in past assessments. These papers are an invaluable tool for students to practice and hone their problem-solving skills, gain familiarity with the types of challenges they may encounter in exams, and identify areas where further study may be needed. By working through these unsolved papers, students are not merely preparing for their exams; they are also deepening their understanding of the core principles and advanced techniques of Data Science and Big Data. Each question in these papers has been designed to test not just knowledge, but the ability to apply concepts to real-world problems, analyse data critically, and derive meaningful conclusions—skills that are essential for any aspiring data scientist or big data professional.

Class 12 CBSE Data Science Previous Year Unsolved Questions Paper Book

Class 12 CBSE Data Science Previous Year Unsolved Questions Paper Book
Author: Manish Soni
Publisher:
Total Pages: 44
Release: 2024-11-10
Genre: Reference
ISBN:
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Prepare for success in data science with Data Science Class 12 Previous Years Unsolved Questions Paper Book! This essential resource compiles unsolved questions from previous years' exams, tailored for Class 12 students to strengthen their understanding and problem-solving skills in data science. Each question is designed to challenge students and enhance their analytical thinking, covering key topics in data handling, statistics, probability, and more. Ideal for self-assessment and exam practice, this book is perfect for students aiming to build confidence and excel in their data science studies.

Cracking the Data Science Interview

Cracking the Data Science Interview
Author: Leondra R. Gonzalez
Publisher: Packt Publishing Ltd
Total Pages: 404
Release: 2024-02-29
Genre: Computers
ISBN: 1805120190
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Rise above the competition and excel in your next interview with this one-stop guide to Python, SQL, version control, statistics, machine learning, and much more Key Features Acquire highly sought-after skills of the trade, including Python, SQL, statistics, and machine learning Gain the confidence to explain complex statistical, machine learning, and deep learning theory Extend your expertise beyond model development with version control, shell scripting, and model deployment fundamentals Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe data science job market is saturated with professionals of all backgrounds, including academics, researchers, bootcampers, and Massive Open Online Course (MOOC) graduates. This poses a challenge for companies seeking the best person to fill their roles. At the heart of this selection process is the data science interview, a crucial juncture that determines the best fit for both the candidate and the company. Cracking the Data Science Interview provides expert guidance on approaching the interview process with full preparation and confidence. Starting with an introduction to the modern data science landscape, you’ll find tips on job hunting, resume writing, and creating a top-notch portfolio. You’ll then advance to topics such as Python, SQL databases, Git, and productivity with shell scripting and Bash. Building on this foundation, you'll delve into the fundamentals of statistics, laying the groundwork for pre-modeling concepts, machine learning, deep learning, and generative AI. The book concludes by offering insights into how best to prepare for the intensive data science interview. By the end of this interview guide, you’ll have gained the confidence, business acumen, and technical skills required to distinguish yourself within this competitive landscape and land your next data science job.What you will learn Explore data science trends, job demands, and potential career paths Secure interviews with industry-standard resume and portfolio tips Practice data manipulation with Python and SQL Learn about supervised and unsupervised machine learning models Master deep learning components such as backpropagation and activation functions Enhance your productivity by implementing code versioning through Git Streamline workflows using shell scripting for increased efficiency Who this book is for Whether you're a seasoned professional who needs to brush up on technical skills or a beginner looking to enter the dynamic data science industry, this book is for you. To get the most out of this book, basic knowledge of Python, SQL, and statistics is necessary. However, anyone familiar with other analytical languages, such as R, will also find value in this resource as it helps you revisit critical data science concepts like SQL, Git, statistics, and deep learning, guiding you to crack through data science interviews.

How to Lead in Data Science

How to Lead in Data Science
Author: Jike Chong
Publisher: Simon and Schuster
Total Pages: 510
Release: 2021-12-21
Genre: Computers
ISBN: 1617298891
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Lead your data science teams and projects to success! To make a consistent, meaningful impact as a data science leader, you must articulate technology roadmaps, plan effective project strategies, support diversity, and create a positive environment for professional growth. This book delivers the wisdom and practical skills you need to thrive as a data science leader at all levels, from team member to the C-suite. "How to lead in data science" shares unique leadership techniques from high-performance data teams. It's filled with best practices for balancing project trade-offs and producing exceptional results, even when beginning with vague requirements or unclear expectations. You'll find a clearly presented modern leadership framework based on current case studies, with insights reaching all the way to Aristotle and Confucius. As you read, you'll build practical skills to grow and improve your team, your company's data culture, and yourself.

Data Analysis for Business, Economics, and Policy

Data Analysis for Business, Economics, and Policy
Author: Gábor Békés
Publisher: Cambridge University Press
Total Pages: 741
Release: 2021-05-06
Genre: Business & Economics
ISBN: 1108483011
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A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.

MCAT Critical Analysis and Reasoning Skills Review 2024-2025

MCAT Critical Analysis and Reasoning Skills Review 2024-2025
Author: Kaplan Test Prep
Publisher: Simon and Schuster
Total Pages: 335
Release: 2023-07-04
Genre: Language Arts & Disciplines
ISBN: 1506286895
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Kaplan’s MCAT Critical Analysis and Reasoning Skills Review 2024-2025 offers an expert study plan, detailed subject review, and hundreds of online and in-book practice questions—all authored by the experts behind the MCAT prep course that has helped more people get into medical school than all other major courses combined. Prepping for the MCAT is a true challenge. Kaplan can be your partner along the way—offering guidance on where to focus your efforts and how to organize your review. This book has been updated to match the AAMC’s guidelines precisely—no more worrying about whether your MCAT review is comprehensive! The Most Practice More than 100 questions in the book and access to even more online—more practice than any other MCAT CARS book on the market. The Best Practice Comprehensive CARS subject review is written by top-rated, award-winning Kaplan instructors. All material is vetted by editors with advanced science degrees and by a medical doctor. Online resources, including a full-length practice test, help you practice in the same computer-based format you’ll see on Test Day. Expert Guidance We know the test: The Kaplan MCAT team has spent years studying every MCAT-related document available. Kaplan’s expert psychometricians ensure our practice questions and study materials are true to the test.

Big Data at Work

Big Data at Work
Author: Scott Tonidandel
Publisher: Routledge
Total Pages: 321
Release: 2015-11-06
Genre: Psychology
ISBN: 1317702697
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The amount of data in our world has been exploding, and analyzing large data sets—so called big data—will become a key basis of competition in business. Statisticians and researchers will be updating their analytic approaches, methods and research to meet the demands created by the availability of big data. The goal of this book is to show how advances in data science have the ability to fundamentally influence and improve organizational science and practice. This book is primarily designed for researchers and advanced undergraduate and graduate students in psychology, management and statistics.