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| data science internship resume: RESUME SAMPLES 60 for IT & Others Gyan Shankar, 2024-07-24 This book contains sixty sample resumes for various IT and other job roles, which are distinct for freshers and seniors. This guidebook offers a new approach and a well-marked path to the construction of an effective résumé, in formats hiring managers prefer. The opening chapter provides the different formats of resumes, for freshers and seniors and explains each one and provides the information you need to ensure that you use the right format for your resume depending on your profile, overall work history and the type of job you're seeking. |
| data science internship resume: Build a Career in Data Science Emily Robinson, Jacqueline Nolis, 2020-03-24 Summary You are going to need more than 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 project, and even how to become a manager. Purchase of the print 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 valued senior employee. By following clear and simple instructions, you’ll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You’ll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the book. What's inside Creating a portfolio of data science projects Assessing and negotiating an offer Leaving gracefully and moving up the ladder Interviews with professional 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. Jacqueline Nolis is a data science consultant and mentor. Table of Contents: PART 1 - GETTING STARTED WITH DATA SCIENCE 1. What is data science? 2. Data science companies 3. Getting the skills 4. Building a portfolio 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 production 12. Working with stakeholders PART 4 - GROWING IN YOUR DATA SCIENCE ROLE 13. When your data science project fails 14. Joining the data science community 15. Leaving your job gracefully 16. Moving up the ladder |
| data science internship resume: Ace the Data Science Interview Kevin Huo, Nick Singh, 2021 |
| data science internship resume: Hands-On Data Science and Python Machine Learning Frank Kane, 2017-07-31 This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale machine learning using Apache Spark. About This Book Take your first steps in the world of data science by understanding the tools and techniques of data analysis Train efficient Machine Learning models in Python using the supervised and unsupervised learning methods Learn how to use Apache Spark for processing Big Data efficiently Who This Book Is For If you are a budding data scientist or a data analyst who wants to analyze and gain actionable insights from data using Python, this book is for you. Programmers with some experience in Python who want to enter the lucrative world of Data Science will also find this book to be very useful, but you don't need to be an expert Python coder or mathematician to get the most from this book. What You Will Learn Learn how to clean your data and ready it for analysis Implement the popular clustering and regression methods in Python Train efficient machine learning models using decision trees and random forests Visualize the results of your analysis using Python's Matplotlib library Use Apache Spark's MLlib package to perform machine learning on large datasets In Detail Join Frank Kane, who worked on Amazon and IMDb's machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them. Based on Frank's successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis. Style and approach This comprehensive book is a perfect blend of theory and hands-on code examples in Python which can be used for your reference at any time. |
| data science internship resume: The Great Cloud Migration Michael C. Daconta, 2013 - Learn how to migrate your applications to the cloud! - Learn how to overcome your senior management's concerns about Cloud Security and Interoperability! - Learn how to explain cloud computing, big data and linked data to your organization! - Learn how to develop a robust Cloud Implementation Strategy! - Learn how a Technical Cloud Broker can ease your migration to the cloud! This book will answer the key questions that every organization is asking about emerging technologies like Cloud Computing, Big Data and Linked Data. Written by a seasoned expert and author/co-author of 11 other technical books, this book deftly guides you with real-world experience, case studies, illustrative diagrams and in-depth analysis. * How do you migrate your software applications to the cloud? This book is your definitive guide to migrating applications to the cloud! It explains all the options, tradeoffs, challenges and obstacles to the migration. It provides a migration lifecycle and process you can follow to migrate each application. It provides in-depth case studies: an Infrastructure-as-a-Service case study and a Platform-as-a-Service case study. It covers the difference between application migration and data migration to the cloud and walks you through how to do both well. It covers migration to all the major cloud providers to include Amazon Web Services (AWS), Google AppEngine and Microsoft Azure. * How do you develop a sound implementation strategy for the migration to the cloud? This book leverages Mr. Daconta's 25 years of leadership experience, from the Military to Corporate Executive teams to the Office of the CIO in the Department of Homeland Security, to guide you through the development of a practical and sound implementation strategy. The book's Triple-A Strategy: Assessment, Architecture then Action is must reading for every project lead and IT manager! * This book covers twenty migration scenarios! Application and data migration to the cloud |
| data science internship resume: How to Land a Top-Paying Federal Job Lily WHITEMAN, 2008-09-08 A comprehensive guide to landing one of the hundreds of thousands of jobs filled each year by the nation''s largest employerOC the U.S. government. |
| data science internship resume: The Google Resume Gayle Laakmann McDowell, 2011-01-25 The Google Resume is the only book available on how to win a coveted spot at Google, Microsoft, Apple, or other top tech firms. Gayle Laakmann McDowell worked in Google Engineering for three years, where she served on the hiring committee and interviewed over 120 candidates. She interned for Microsoft and Apple, and interviewed with and received offers from ten tech firms. If you’re a student, you’ll learn what to study and how to prepare while in school, as well as what career paths to consider. If you’re a job seeker, you’ll get an edge on your competition by learning about hiring procedures and making yourself stand out from other candidates. Covers key concerns like what to major in, which extra-curriculars and other experiences look good, how to apply, how to design and tailor your resume, how to prepare for and excel in the interview, and much more Author was on Google’s hiring committee; interned at Microsoft and Apple; has received job offers from more than 10 tech firms; and runs CareerCup.com, a site devoted to tech jobs Get the only comprehensive guide to working at some of America’s most dynamic, innovative, and well-paying tech companies with The Google Resume. |
| data science internship resume: Improving Equity in Data Science Colby Tofel-Grehl, Emmanuel Schanzer, 2024-06-03 Improving Equity in Data Science offers a comprehensive look at the ways in which data science can be conceptualized and engaged more equitably within the K-16 classroom setting, moving beyond merely broadening participation in educational opportunities. This book makes the case for field wide definitions, literacies and practices for data science teaching and learning that can be commonly discussed and used, and provides examples from research of these practices and literacies in action. Authors share stories and examples of research wherein data science advances equity and empowerment through the critical examination of social, educational, and political topics. In the first half of the book, readers will learn how data science can deliberately be embedded within K-12 spaces to empower students to use it to identify and address inequity. The latter half will focus on equity of access to data science learning opportunities in higher education, with a final synthesis of lessons learned and presentation of a 360-degree framework that links access, curriculum, and pedagogy as multiple facets collectively essential to comprehensive data science equity work. Practitioners and teacher educators will be able to answer the question, “how can data science serve to move equity efforts in computing beyond basic inclusion to empowerment?” whether the goal is to simply improve definitions and approaches to research on data science or support teachers of data science in creating more equitable and inclusive environments within their classrooms. |
| data science internship resume: 50 Ways to Get a Job Dev Aujla, 2018-04-03 A new personalized way to find the perfect job—while staying calm during the process. You are so much more than a resume or job application, but how can you communicate that to your potential employer? You need to learn to ask the right questions, stop using job sites, and start doing the work that actually counts. Based on information gained from over 400,000 individuals who have used these exercises, this book reveals career expert Dev Aujla’s tried-and-tested method for job seekers at every stage of their career. Filled with anecdotes and advice from professionals ranging from a wilderness guide to an architect, it includes quick-step exercises that help you avoid the common pitfalls of navigating a modern career. Whether you've just decided to start the hunt or you're gearing up for a big interview, 50 Ways to Get a Job will keep you poised, on-track, and motivated right up to landing your dream career. |
| data science internship resume: Introduction to Data Science Rafael A. Irizarry, 2019-11-20 Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert. |
| data science internship resume: Using WebPageTest Rick Viscomi, Andy Davies, Marcel Duran, 2015-10-13 Learn basic and advanced uses of WebPagetest, the performance measurement tool for optimizing websites. This practical guide shows users new to this tool how run tests and interpret results, and helps experienced users gain a better and more thorough understanding of hidden features in WebPagetest that make testing easier. Written by WebPagetest power users and performance experts, this book will help web developers and frontend engineers solve the problem of slow sites. Topics include: Basic test setup—shows beginners how to get meaningful results Advanced test setup—provides another level of technical depth by explaining features not thoroughly documented at webpagetest.org Analysis of results—helps you understand of how to interpret test results Private instance setup—teaches power users the intricacies of the webpagetest private instance and how it works API and external tools—provides a detailed reference for the API and demonstrates tools already using the API to extend WebPagetest |
| data science internship resume: Applying Data Science and Learning Analytics Throughout a Learner’s Lifespan Trajkovski, Goran, Demeter, Marylee, Hayes, Heather, 2022-05-06 Research in the domains of learning analytics and educational data mining has prototyped an approach where methodologies from data science and machine learning are used to gain insights into the learning process by using large amounts of data. As many training and academic institutions are maturing in their data-driven decision making, useful, scalable, and interesting trends are emerging. Organizations can benefit from sharing information on those efforts. Applying Data Science and Learning Analytics Throughout a Learner’s Lifespan examines novel and emerging applications of data science and sister disciplines for gaining insights from data to inform interventions into learners’ journeys and interactions with academic institutions. Data is collected at various times and places throughout a learner’s lifecycle, and the learners and the institution should benefit from the insights and knowledge gained from this data. Covering topics such as learning analytics dashboards, text network analysis, and employment recruitment, this book is an indispensable resource for educators, computer scientists, faculty of higher education, government officials, educational administration, students of higher education, pre-service teachers, business professionals, researchers, and academicians. |
| data science internship resume: Busy Chipmunk Kirsten Hall, 2001 Rhyming tale of a chipmunk gathering nuts and other food to prepare for winter. |
| data science internship resume: Ask a Manager Alison Green, 2018-05-01 From the creator of the popular website Ask a Manager and New York’s work-advice columnist comes a witty, practical guide to 200 difficult professional conversations—featuring all-new advice! There’s a reason Alison Green has been called “the Dear Abby of the work world.” Ten years as a workplace-advice columnist have taught her that people avoid awkward conversations in the office because they simply don’t know what to say. Thankfully, Green does—and in this incredibly helpful book, she tackles the tough discussions you may need to have during your career. You’ll learn what to say when • coworkers push their work on you—then take credit for it • you accidentally trash-talk someone in an email then hit “reply all” • you’re being micromanaged—or not being managed at all • you catch a colleague in a lie • your boss seems unhappy with your work • your cubemate’s loud speakerphone is making you homicidal • you got drunk at the holiday party Praise for Ask a Manager “A must-read for anyone who works . . . [Alison Green’s] advice boils down to the idea that you should be professional (even when others are not) and that communicating in a straightforward manner with candor and kindness will get you far, no matter where you work.”—Booklist (starred review) “The author’s friendly, warm, no-nonsense writing is a pleasure to read, and her advice can be widely applied to relationships in all areas of readers’ lives. Ideal for anyone new to the job market or new to management, or anyone hoping to improve their work experience.”—Library Journal (starred review) “I am a huge fan of Alison Green’s Ask a Manager column. This book is even better. It teaches us how to deal with many of the most vexing big and little problems in our workplaces—and to do so with grace, confidence, and a sense of humor.”—Robert Sutton, Stanford professor and author of The No Asshole Rule and The Asshole Survival Guide “Ask a Manager is the ultimate playbook for navigating the traditional workforce in a diplomatic but firm way.”—Erin Lowry, author of Broke Millennial: Stop Scraping By and Get Your Financial Life Together |
| data science internship resume: Data Structures and Algorithm Analysis in Java, Third Edition Clifford A. Shaffer, 2012-09-06 Comprehensive treatment focuses on creation of efficient data structures and algorithms and selection or design of data structure best suited to specific problems. This edition uses Java as the programming language. |
| data science internship resume: Multivariable Calculus James Stewart, 2011-09-27 Success in your calculus course starts here! James Stewart's CALCULUS, 7e, International Metric texts are world-wide best-sellers for a reason: they are clear, accurate, and filled with relevant, real-world examples. With MULTIVARIABLE CALCULUS, 7e, International Metric Edition Stewart conveys not only the utility of calculus to help you develop technical competence, but also gives you an appreciation for the intrinsic beauty of the subject. His patient examples and built-in learning aids will help you build your mathematical confidence and achieve your goals in the course! |
| data science internship resume: Cracking the Data Science Interview Leondra R. Gonzalez, Aaren Stubberfield, 2024-02-29 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. |
| data science internship resume: Encylopedia of Job-winning Resumes Myra Fournier, Jeffrey Spin, 2006-01-01 This is the most helpful and comprehensive resume book you can buy. It includes more than 400 success-proven resume expamples that teach you how to personalize your resume according to your own unique career situation. The 17 chapters contain resumes that cover all major industries, span all job levels from entry-level to CEO, and are helpfully arranged by both job field and title to make it easy for you to quickly locate the resumes that address your particular field or situation. The first chapter includes expert advice on what to include on your resume and what to omit, what to emphasize and what to tone down. It is specifically designed to keep reading to a minimum, so you can start sending out your resume as soon as possible. The second chapter, devoted to creating hard-hitting cover letters, includes 40 examples tht cover a wide varitey of typical career situtations, while the third chapter include 30 includres 30 resumes that cover difficult circumstance. There is even a chapter devoted to students to help new graduates joining the workforce. |
| data science internship resume: Pristine Seas Enric Sala, Leonardo DiCaprio, 2015 National Geographic Explorer-in-Residence Enric Sala takes readers on an unforgettable journey to 10 places where the ocean is virtually untouched by man, offering a fascinating glimpse into our past and an inspiring vision for the future. From the shark-rich waters surrounding Coco Island, Costa Rica, to the iceberg-studded sea off Franz Josef Land, Russia, this incredible photographic collection showcases the thriving marine ecosystems that Sala is working to protect. Offering a rare glimpse into the world's underwater Edens, more than 200 images take you to the frontier of the Pristine Seas expeditions, where Sala's teams explore the breathtaking wildlife and habitats from the depths to the surface--thriving ecosystems with healthy corals and a kaleidoscopic variety of colorful fish and stunning creatures that have been protected from human interference. With this dazzling array of photographs that capture the beauty of the water and the incredible wildlife within it, this book shows us the brilliance of the sea in its natural state.-- |
| data science internship resume: The Internship Bible Mark Oldman, Samer Hamadeh, 2005-01-25 Lists internship opportunities in a variety of fields, giving information about selectivity, compensation, deadlines, and duration. |
| data science internship resume: A Celebration of the EDGE Program’s Impact on the Mathematics Community and Beyond Susan D'Agostino, Sarah Bryant, Amy Buchmann, Michelle Craddock Guinn, Leona Harris, 2019-08-31 The Enhancing Diversity in Graduate Education (EDGE) Program began twenty years ago to provide support for women entering doctoral programs in the mathematical sciences. With a steadfast commitment to diversity among participants, faculty, and staff, EDGE initially alternated between Bryn Mawr and Spelman Colleges. In later years, EDGE has been hosted on campuses around the nation and expanded to offer support for women throughout their graduate school and professional careers. The refereed papers in A Celebration of the EDGE Program’s Impact on the Mathematics Community and Beyond range from short memoirs, to pedagogical studies, to current mathematics research. All papers are written by former EDGE participants, mentors, instructors, directors, and others connected to EDGE. Together, these papers offer compelling testimony that EDGE has produced a diverse new generation of leaders in the mathematics community. This volume contains technical and non-technical works, and it is intended for a far-reaching audience, including mathematicians, mathematics teachers, diversity officers, university administrators, government employees writing educational or science policy, and mathematics students at the high school, college, and graduate levels. By highlighting the scope of the work done by those supported by EDGE, the volume offers strong evidence of the American Mathematical Society’s recognition that EDGE is a program that makes a difference.” This volume offers unique testimony that a 20-year old summer program has expanded its reach beyond the summer experience to produce a diverse new generation of women leaders, nearly half of whom are underrepresented women. While some books with a women-in-math theme focus only on one topic such as research or work-life balance, this book's broad scope includes papers on mathematics research, teaching, outreach, and career paths. |
| data science internship resume: Fifty Challenging Problems in Probability with Solutions Frederick Mosteller, 2012-04-26 Remarkable puzzlers, graded in difficulty, illustrate elementary and advanced aspects of probability. These problems were selected for originality, general interest, or because they demonstrate valuable techniques. Also includes detailed solutions. |
| data science internship resume: Hadoop For Dummies Dirk deRoos, 2014-04-14 Let Hadoop For Dummies help harness the power of your data and rein in the information overload Big data has become big business, and companies and organizations of all sizes are struggling to find ways to retrieve valuable information from their massive data sets with becoming overwhelmed. Enter Hadoop and this easy-to-understand For Dummies guide. Hadoop For Dummies helps readers understand the value of big data, make a business case for using Hadoop, navigate the Hadoop ecosystem, and build and manage Hadoop applications and clusters. Explains the origins of Hadoop, its economic benefits, and its functionality and practical applications Helps you find your way around the Hadoop ecosystem, program MapReduce, utilize design patterns, and get your Hadoop cluster up and running quickly and easily Details how to use Hadoop applications for data mining, web analytics and personalization, large-scale text processing, data science, and problem-solving Shows you how to improve the value of your Hadoop cluster, maximize your investment in Hadoop, and avoid common pitfalls when building your Hadoop cluster From programmers challenged with building and maintaining affordable, scaleable data systems to administrators who must deal with huge volumes of information effectively and efficiently, this how-to has something to help you with Hadoop. |
| data science internship resume: Theoretical Statistics Robert W. Keener, 2010-09-08 Intended as the text for a sequence of advanced courses, this book covers major topics in theoretical statistics in a concise and rigorous fashion. The discussion assumes a background in advanced calculus, linear algebra, probability, and some analysis and topology. Measure theory is used, but the notation and basic results needed are presented in an initial chapter on probability, so prior knowledge of these topics is not essential. The presentation is designed to expose students to as many of the central ideas and topics in the discipline as possible, balancing various approaches to inference as well as exact, numerical, and large sample methods. Moving beyond more standard material, the book includes chapters introducing bootstrap methods, nonparametric regression, equivariant estimation, empirical Bayes, and sequential design and analysis. The book has a rich collection of exercises. Several of them illustrate how the theory developed in the book may be used in various applications. Solutions to many of the exercises are included in an appendix. |
| data science internship resume: The Professor Is In Karen Kelsky, 2015-08-04 The definitive career guide for grad students, adjuncts, post-docs and anyone else eager to get tenure or turn their Ph.D. into their ideal job Each year tens of thousands of students will, after years of hard work and enormous amounts of money, earn their Ph.D. And each year only a small percentage of them will land a job that justifies and rewards their investment. For every comfortably tenured professor or well-paid former academic, there are countless underpaid and overworked adjuncts, and many more who simply give up in frustration. Those who do make it share an important asset that separates them from the pack: they have a plan. They understand exactly what they need to do to set themselves up for success. They know what really moves the needle in academic job searches, how to avoid the all-too-common mistakes that sink so many of their peers, and how to decide when to point their Ph.D. toward other, non-academic options. Karen Kelsky has made it her mission to help readers join the select few who get the most out of their Ph.D. As a former tenured professor and department head who oversaw numerous academic job searches, she knows from experience exactly what gets an academic applicant a job. And as the creator of the popular and widely respected advice site The Professor is In, she has helped countless Ph.D.’s turn themselves into stronger applicants and land their dream careers. Now, for the first time ever, Karen has poured all her best advice into a single handy guide that addresses the most important issues facing any Ph.D., including: -When, where, and what to publish -Writing a foolproof grant application -Cultivating references and crafting the perfect CV -Acing the job talk and campus interview -Avoiding the adjunct trap -Making the leap to nonacademic work, when the time is right The Professor Is In addresses all of these issues, and many more. |
| data science internship resume: 50 Successful Harvard Medical School Essays Staff of the Harvard Crimson, 2020-05-05 Fifty all-new essays that got their authors into Harvard Medical School, including MCAT scores, showing what worked, what didn’t, and how you can do it too. Competition to get into the nation’s top medical schools has never been more intense. Harvard Medical School in particular draws thousands of elite applicants from around the world. As admissions departments become increasingly selective, even the best and brightest need an edge. Writing a personal statement is a daunting part of the application process. In less than 5,300 characters, applicants must weave together experiences and passions into a memorable narrative to set them apart from thousands of other applicants. While there is no magic formula for writing the perfect essay, picking up this book will put them on the right track. 50 Successful Harvard Medical School Essays is the first in a new line of books published by the Staff of the Harvard Crimson. It includes fifty standout essays from students who successfully secured a spot at Harvard Medical School. Each student has a unique set of experiences that led them to medicine. Each essay includes analysis by Crimson editors on essay qualities and techniques that worked, so readers can apply them to their own writing. This book will aid applicants in composing essays that reveal their passion for medicine and the discipline they will bring to this demanding program and profession. It will give them the extra help they need to get into the best medical school programs in the world. |
| data science internship resume: BEST Lorena Infante Lara, Laura Daniel, Roger Chalkley, 2020-02-18 BEST: Implementing Career Development Activities for Biomedical Research Trainees provides an instructional guide for institutions wanting to create, supplement or improve their career and professional development offerings. Each chapter provides an exclusive perspective from an administrator from the 17 Broadening Experiences in Scientific Training (BEST) institutions. The book can aid institutions who train graduate students in a variety of careers by teaching faculty and staff how to create and implement career development programming, how to highlight the effectiveness of offerings, how to demonstrate that creating a program from scratch is doable, and how to inform faculty and staff on getting institutional buy-in. This is a must-have for graduate school deans and faculty and staff who want to implement and institutionalize career development programing at their institutions. It is also ideal for graduate students and postdocs. - Provides an instructional guide for institutions wanting to create or supplement their career and professional development offerings - Contains perspectives from administrators from the 17 Broadening Experiences in Scientific Training (BEST) institutions - Addresses what graduate students and postdoctoral populations can implement now to help broaden career outcomes |
| data science internship resume: Heard in Data Science Interviews Kal Mishra, 2018-10-03 A collection of over 650 actual Data Scientist/Machine Learning Engineer job interview questions along with their full answers, references, and useful tips |
| data science internship resume: Cracking the Coding Interview Gayle Laakmann McDowell, 2011 Now in the 5th edition, Cracking the Coding Interview gives you the interview preparation you need to get the top software developer jobs. This book provides: 150 Programming Interview Questions and Solutions: From binary trees to binary search, this list of 150 questions includes the most common and most useful questions in data structures, algorithms, and knowledge based questions. 5 Algorithm Approaches: Stop being blind-sided by tough algorithm questions, and learn these five approaches to tackle the trickiest problems. Behind the Scenes of the interview processes at Google, Amazon, Microsoft, Facebook, Yahoo, and Apple: Learn what really goes on during your interview day and how decisions get made. Ten Mistakes Candidates Make -- And How to Avoid Them: Don't lose your dream job by making these common mistakes. Learn what many candidates do wrong, and how to avoid these issues. Steps to Prepare for Behavioral and Technical Questions: Stop meandering through an endless set of questions, while missing some of the most important preparation techniques. Follow these steps to more thoroughly prepare in less time. |
| data science internship resume: Recommendation Engines Michael Schrage, 2020-09-01 How companies like Amazon, Netflix, and Spotify know what you might also like: the history, technology, business, and societal impact of online recommendation engines. Increasingly, our technologies are giving us better, faster, smarter, and more personal advice than our own families and best friends. Amazon already knows what kind of books and household goods you like and is more than eager to recommend more; YouTube and TikTok always have another video lined up to show you; Netflix has crunched the numbers of your viewing habits to suggest whole genres that you would enjoy. In this volume in the MIT Press's Essential Knowledge series, innovation expert Michael Schrage explains the origins, technologies, business applications, and increasing societal impact of recommendation engines, the systems that allow companies worldwide to know what products, services, and experiences you might also like. |
| data science internship resume: Resumes For Dummies Laura DeCarlo, 2019-02-22 Polish up that old resume—and land your dream job We've all been there: it's time to apply for a job or internship and you have to create or revise your resume. Many questions pop in your head. What do employers want? What skills should I highlight? How do I format this? How do I get noticed? But resume writing doesn't have to be a daunting task. The latest edition of Resumes For Dummies answers all of these questions and more—whether you're a resume rookie, looking for new tips, or want to create that eye-catching winning resume. In this trusted guide, Laura DeCarlo decodes the modern culture of resume writing and offers you insider tips on all the best practices that’ll make your skills shine and your resume pop. Let's start writing! Write effective resumes that will stand out in a crowd Understand Applicant Tracking Systems and how to adapt your resume Keep your resume up with the current culture Position a layoff or other career change and challenge with a positive spin Leverage tips and tricks that give your resume visual power In order to put your best foot forward and stand out in a pile of papers, it’s important to have an excellent and effective resume—and now you can. |
| data science internship resume: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| data science internship resume: The Damn Good Resume Guide Yana Parker, 1983 Yana Parker has helped hundreds of thousands of job seekers write and refine their resumes to damn near perfection. Her resume guides have been praised for their user-friendly style and savvy advice and, rightly so, have become staples in libraries, career centers, and employment offices nationwide. Now, in this fully revised and updated edition of the best-seller, you can quickly garner resume-writing wisdom by following 10 easy steps to a damn good resume. Also included are completely new sections on formatting resumes and submitting resumes over the Internet. Here is a resume guide you can count on to help you get that resume done fast and get it done right. |
| data science internship resume: Good with Words Patrick Barry, 2019-05-31 If your success at work or in school depends on your ability to communicate persuasively in writing, you'll want to get Good with Words. Based on a course that law students at the University of Michigan and the University of Chicago have called outstanding, A-M-A-Z-I-N-G, and the best course I have ever taken, the book brings together a collection of concepts, exercises, and examples that have also helped improve the advocacy skills of people pursuing careers in many other fields--from marketing, to management, to medicine. There is nobody better than Patrick Barry when it comes to breaking down how to write and edit. His techniques don't just make you sound better. They make you think better. I'm jealous of the people who get to take his classes. --Professor Lisa Bernstein, University of Chicago Law School and Oxford University Center for Corporate Regulation Whenever I use Patrick Barry's materials in my class, the student reaction is the same: 'We want more of them.' --Professor Dave Babbe, UCLA School of Law Working one-on-one with Patrick Barry should be mandatory for all lawyers, regardless of seniority. This book is the next best thing. --Purvi Patel, Partner at Morrison Foerster LLP I am proud to say that, when it comes to writing, I speak Patrick Barry. What I mean is that I use, pretty much every day, the writing vocabulary and techniques he offers in this great book. So read it. Share it. And then, if you can, teach it. There are a lot of good causes in the world that could use a new generation of great advocates. --Professor Bridgette Carr, Assistant Dean of Strategic Initiatives and Director of the Human Trafficking Clinic at the University of Michigan Law School Patrick Barry is my secret weapon. I use his techniques every time I write, and I also teach them to all my students. --Professor Shai Dothan, Copenhagen Faculty of Law I know the materials in this book were originally created for lawyers and law students. But I actually find them really helpful for doctors as well, given that a lot of what I do every day depends on effective communication. There is a tremendous upside to becoming 'Good with Words. --Dr. Ramzi Abboud, Washington University School of Medicine in St. Louis. |
| data science internship resume: Programming Interviews Exposed John Mongan, Noah Suojanen Kindler, Eric Giguère, 2011-08-10 The pressure is on during the interview process but with the right preparation, you can walk away with your dream job. This classic book uncovers what interviews are really like at America's top software and computer companies and provides you with the tools to succeed in any situation. The authors take you step-by-step through new problems and complex brainteasers they were asked during recent technical interviews. 50 interview scenarios are presented along with in-depth analysis of the possible solutions. The problem-solving process is clearly illustrated so you'll be able to easily apply what you've learned during crunch time. You'll also find expert tips on what questions to ask, how to approach a problem, and how to recover if you become stuck. All of this will help you ace the interview and get the job you want. What you will learn from this book Tips for effectively completing the job application Ways to prepare for the entire programming interview process How to find the kind of programming job that fits you best Strategies for choosing a solution and what your approach says about you How to improve your interviewing skills so that you can respond to any question or situation Techniques for solving knowledge-based problems, logic puzzles, and programming problems Who this book is for This book is for programmers and developers applying for jobs in the software industry or in IT departments of major corporations. Wrox Beginning guides are crafted to make learning programming languages and technologies easier than you think, providing a structured, tutorial format that will guide you through all the techniques involved. |
| data science internship resume: Law and Policy for the Quantum Age Chris Jay Hoofnagle, Simson L. Garfinkel, 2022-01-06 The Quantum Age cuts through the hype to demystify quantum technologies, their development paths, and the policy issues they raise. |
| data science internship resume: The Analytics Edge Dimitris Bertsimas, Allison K. O'Hair, William R. Pulleyblank, 2016 Provides a unified, insightful, modern, and entertaining treatment of analytics. The book covers the science of using data to build models, improve decisions, and ultimately add value to institutions and individuals--Back cover. |
| data science internship resume: Machine Learning Bookcamp Alexey Grigorev, 2021-11-23 The only way to learn is to practice! In Machine Learning Bookcamp, you''ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what you''ve learned in previous chapters. By the end of the bookcamp, you''ll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technology Machine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, that''s exactly what you''ll be doing in Machine Learning Bookcamp. about the book In Machine Learning Bookcamp you''ll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you''ll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You''ll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you''re done working through these fun and informative projects, you''ll have a comprehensive machine learning skill set you can apply to practical on-the-job problems. what''s inside Code fundamental ML algorithms from scratch Collect and clean data for training models Use popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlow Apply ML to complex datasets with images and text Deploy ML models to a production-ready environment about the reader For readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning. |
| data science internship resume: The New Rules of Work Alexandra Cavoulacos, Kathryn Minshew, 2017 In this definitive guide to the ever-changing modern workplace, Kathryn Minshew and Alexandra Cavoulacos, the co-founders of popular career website TheMuse.com, show how to play the game by the New Rules. The Muse is known for sharp, relevant, and get-to-the-point advice on how to figure out exactly what your values and your skills are and how they best play out in the marketplace. Now Kathryn and Alex have gathered all of that advice and more in The New Rules of Work. Through quick exercises and structured tips, the authors will guide you as you sort through your countless options; communicate who you are and why you are valuable; and stand out from the crowd. The New Rules of Work shows how to choose a perfect career path, land the best job, and wake up feeling excited to go to work every day-- whether you are starting out in your career, looking to move ahead, navigating a mid-career shift, or anywhere in between-- |
| data science internship resume: Python for Everybody Charles R. Severance, 2016-04-09 Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.Python is an easy to use and easy to learn programming language that is freely available on Macintosh, Windows, or Linux computers. So once you learn Python you can use it for the rest of your career without needing to purchase any software.This book uses the Python 3 language. The earlier Python 2 version of this book is titled Python for Informatics: Exploring Information.There are free downloadable electronic copies of this book in various formats and supporting materials for the book at www.pythonlearn.com. The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course. |
Data Scientist Intern Resume Example
As a Data Scientist Intern with over 1 year of experience, I have honed my analytical and problem-solving skills to work with large data sets. I have developed strong experience in data …
Trish Mathers - d25zcttzf44i59.cloudfront.net
Innovative and scientifically rigorous graduate with significant data science internship experience to bring to the table. With a team-oriented attitude, I'm eager to contribute my abilities in …
ROBERT SMITH - QwikResume.com
To obtain a Data Scientist Intern student with relevant coursework includes Decision Analysis, Predictive Modeling, Machine Learning, R and Python for Statistical Inference and Data …
RESUME BASICS SPECIAL CONSIDERATIONS FOR DATA …
Data Analytics Intern Jun 2021-Current • Utilize data mining techniques to collect, process, and analyze large datasets to support business decision-making • Develop and implement data …
GW Data Science Resume and Cover Letter Guide
Data Scientist with 5+ years of extensive experience leveraging BI technologies, big data, and machine learning algorithms to build predictive models and generate insights for healthcare …
Resume Sample: Data Analytics - Ohio State University
Employers looking for data analytics talent will scan your resume for examples of how you have used analytics to advance a project. Have you done risk assessment for a company, …
Aspiring Data Scientist | Data Analyst - datawithsahil.github.io
8 years of Industry Experience with 1 year of internship as a Data Scientist in ineuron.ai, looking for transition to the Data Science Role. With interest in analyzing raw data and statistics, …
Jamar L. Johnson - Pennsylvania State University
Team Lead, PSU Machine Learning for Data Analytics January 2023 – Present • Worked in a team to apply applications of machine learning algorithms to real-life customer data provided …
SCIENCES, TECHNOLOGY, MATHEMATICS, RESEARCH Resume …
Talented new professional with leading-edge degree and hands-on experience with technology, data management, and data analysis. Working knowledge of specialized GIS concepts.
Resumes & Cover Letters for Master's Students - Harvard …
Master’s degree candidates in the Harvard Griffin GSAS are able to search for and apply to many Recruiting Program jobs and internships, including some with campus interviews. Be aware …
Resume Resume Sample: Data Analytics - Ohio State University
This portion of your resume should include internship, research, tutoring, or part-time jobs that have allowed you to gain knowledge, skills, and insight relevant to the position you are …
DATA SCIENCE RESUME - Amazon Web Services, Inc.
Show exactly what you have accomplished with numbers and metrics, explain what type of data you were processing, and tell what programming language or software you used.
OM PRABHU R Aspiring Data Scientist Ó Student, IIT Bombay
As a technical enthusiast, I thrive on exploring the frontiers of data science and deep learning. SKILLS Languages:Python, R, SQL, C++, C#, Octave, CSS, JavaScript. Tools:PyTorch, …
Below is an example of a job announcement. Your resume …
Martin’s University involved an internship at the Institute for Systems Biology and courses such as Probability and Statistics, Mathematics for Computer Science, and Math Modeling. My studies …
Data Scientist Resume Example
I am a Data Scientist with over 3 years of experience in developing predictive models and uncovering insights from large datasets. I specialize in building machine learning models, …
GET STARTED NOW! - University of California, San Diego
When you apply to an internship, organizations are looking for the following: Relevant Information. Truthful Information. A reader-friendly resume that is easy to follow. Flowing content with …
TYLER RUSSELL - d25zcttzf44i59.cloudfront.net
A future-driven and methodical individual with data entry experience and a knack for solving problems in data hackathons, seeking a data science internship at Talus Bio.
Sample resume for a college student seeking an internship
I am looking for an internship opportunity for the Summer of 2022. I am currently a junior at Ocean Bay University where I am majoring in Computer Science with a minor in Mathematics. Attend …
Building a Resume for Data Analytics
This portion of your resume should include internship, research, tutoring, or jobs that have allowed you to gain knowledge, skills, and insights relevant to the position you are interested in. In this …
GSICE Class #6: Setting Internship Goals - Office of Career and ...
GOAL 1: I want to establish two mentors in data science who may be able to help me later on in my job search. • Before my internship: I will practice my “elevator pitch” in an informational …
Data Scientist Intern Resume Example
As a Data Scientist Intern with over 1 year of experience, I have honed my analytical and problem-solving skills to work with large data sets. I have developed strong experience in data mining, …
Trish Mathers - d25zcttzf44i59.cloudfront.net
Innovative and scientifically rigorous graduate with significant data science internship experience to bring to the table. With a team-oriented attitude, I'm eager to contribute my abilities in …
ROBERT SMITH - QwikResume.com
To obtain a Data Scientist Intern student with relevant coursework includes Decision Analysis, Predictive Modeling, Machine Learning, R and Python for Statistical Inference and Data …
RESUME BASICS SPECIAL CONSIDERATIONS FOR …
Data Analytics Intern Jun 2021-Current • Utilize data mining techniques to collect, process, and analyze large datasets to support business decision-making • Develop and implement data …
GW Data Science Resume and Cover Letter Guide
Data Scientist with 5+ years of extensive experience leveraging BI technologies, big data, and machine learning algorithms to build predictive models and generate insights for healthcare …
Resume Sample: Data Analytics - Ohio State University
Employers looking for data analytics talent will scan your resume for examples of how you have used analytics to advance a project. Have you done risk assessment for a company, …
Aspiring Data Scientist | Data Analyst - datawithsahil.github.io
8 years of Industry Experience with 1 year of internship as a Data Scientist in ineuron.ai, looking for transition to the Data Science Role. With interest in analyzing raw data and statistics, …
Jamar L. Johnson - Pennsylvania State University
Team Lead, PSU Machine Learning for Data Analytics January 2023 – Present • Worked in a team to apply applications of machine learning algorithms to real-life customer data provided …
SCIENCES, TECHNOLOGY, MATHEMATICS, RESEARCH …
Talented new professional with leading-edge degree and hands-on experience with technology, data management, and data analysis. Working knowledge of specialized GIS concepts.
Resumes & Cover Letters for Master's Students - Harvard …
Master’s degree candidates in the Harvard Griffin GSAS are able to search for and apply to many Recruiting Program jobs and internships, including some with campus interviews. Be aware …
Resume Resume Sample: Data Analytics - Ohio State …
This portion of your resume should include internship, research, tutoring, or part-time jobs that have allowed you to gain knowledge, skills, and insight relevant to the position you are …
DATA SCIENCE RESUME - Amazon Web Services, Inc.
Show exactly what you have accomplished with numbers and metrics, explain what type of data you were processing, and tell what programming language or software you used.
OM PRABHU R Aspiring Data Scientist Ó Student, IIT Bombay
As a technical enthusiast, I thrive on exploring the frontiers of data science and deep learning. SKILLS Languages:Python, R, SQL, C++, C#, Octave, CSS, JavaScript. Tools:PyTorch, …
Below is an example of a job announcement. Your resume …
Martin’s University involved an internship at the Institute for Systems Biology and courses such as Probability and Statistics, Mathematics for Computer Science, and Math Modeling. My studies …
Data Scientist Resume Example
I am a Data Scientist with over 3 years of experience in developing predictive models and uncovering insights from large datasets. I specialize in building machine learning models, …
GET STARTED NOW! - University of California, San Diego
When you apply to an internship, organizations are looking for the following: Relevant Information. Truthful Information. A reader-friendly resume that is easy to follow. Flowing content with …
TYLER RUSSELL - d25zcttzf44i59.cloudfront.net
A future-driven and methodical individual with data entry experience and a knack for solving problems in data hackathons, seeking a data science internship at Talus Bio.
Sample resume for a college student seeking an internship
I am looking for an internship opportunity for the Summer of 2022. I am currently a junior at Ocean Bay University where I am majoring in Computer Science with a minor in Mathematics. Attend …
Building a Resume for Data Analytics
This portion of your resume should include internship, research, tutoring, or jobs that have allowed you to gain knowledge, skills, and insights relevant to the position you are interested in. In this …
GSICE Class #6: Setting Internship Goals - Office of Career …
GOAL 1: I want to establish two mentors in data science who may be able to help me later on in my job search. • Before my internship: I will practice my “elevator pitch” in an informational …
