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| coding dojo data science: Ace the Data Science Interview Kevin Huo, Nick Singh, 2021 |
| coding dojo data science: The Power of Python Rachel Keranen, 2017-12-15 Though Python takes its name from the comical British television series Monty Python's Flying Circus, the coding language is seriously powerful. Guido van Rossum, the programmer who wrote Python, was motivated to create a coding language that is intuitive and easy to understand. This book traces how van Rossum achieved his goal and how both novice programmers and experts use Python to create apps like Instagram and Pinterest and to achieve other objectives. |
| coding dojo data science: Technical Agile Coaching with the Samman Method Emily Bache, 2021-01-25 Samman Technical Coaching is an approach to Agile training that focuses on technical questions concerning how code is written. It is a highly effective way of increasing agility in your software development organization. The first part of the Samman method involves the coach working in an ensemble with development teams, programming in their production codebase. This hands-on mentoring is accompanied by daily learning hour sessions for mastering particular techniques. In this book you will discover how to put Samman into practice, improve your coding procedures and how you collaborate. It is a practical guide for aspiring and experienced coaches looking for fresh ideas and new ways of teaching Agile. It is both challenging and fun for developers and coaches alike. |
| coding dojo data science: 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. |
| coding dojo data science: HTML and CSS Jon Duckett, 2011-11-08 Jon Duckett’s best-selling, full color introduction to HTML and CSS—making complex topics simple, accessible, and fun! Learn HTML and CSS from the book that has inspired hundreds of thousands of beginner-to-intermediate coders. Professional web designers, developers, and programmers as well as new learners are looking to amp up their web design skills at work and expand their personal development—yet finding the right resources online can be overwhelming. Take a confident step in the right direction by choosing the simplicity of HTML & CSS: Design and Build Websites by veteran web developer and programmer Jon Duckett. Widely regarded for setting a new standard for those looking to learn and master web development through his inventive teaching format, Jon Duckett has helped global brands like Philips, Nike, and Xerox create innovative digital solutions, designing and delivering web and mobile projects with impact and the customer at the forefront. In HTML & CSS, Duckett shares his real-world insights in a unique and highly visual style: Introduces HTML and CSS in a way that makes them accessible to everyone―from students to freelancers, and developers, programmers, marketers, social media managers, and more Combines full-color design graphics and engaging photography to explain the topics in an in-depth yet straightforward manner Provides an efficient and user-friendly structure that allows readers to progress through the chapters in a self-paced format Is perfect for anyone looking to update a content management system, run an e-commerce store, or redesign a website using popular web development tools HTML & CSS is well-written and readable, providing organized instruction in ways that other online courses, tutorials, and books have yet to replicate. For readers seeking a comprehensive yet concise guide to HTML and CSS, look no further than this one-of-a-kind guide. HTML & CSS is also available as part of two hardcover and paperback sets depending on your web design and development needs: Web Design with HTML, CSS, JavaScript, and jQuery Set Paperback: 9781118907443 Hardcover: 9781119038634 Front-End Back-End Development with HTML, CSS, JavaScript, jQuery, PHP, and MySQL Set Paperback: 9781119813095 Hardcover: 9781119813088 |
| coding dojo data science: Java By Comparison Simon Harrer, Jörg Lenhard, Linus Dietz, 2018-03-22 Write code that's clean, concise, and to the point: code that others will read with pleasure and reuse. Comparing your code to that of expert programmers is a great way to improve your coding skills. Get hands-on advice to level up your coding style through small and understandable examples that compare flawed code to an improved solution. Discover handy tips and tricks, as well as common bugs an experienced Java programmer needs to know. Make your way from a Java novice to a master craftsman. This book is a useful companion for anyone learning to write clean Java code. The authors introduce you to the fundamentals of becoming a software craftsman, by comparing pieces of problematic code with an improved version, to help you to develop a sense for clean code. This unique before-and-after approach teaches you to create clean Java code. Learn to keep your booleans in check, dodge formatting bugs, get rid of magic numbers, and use the right style of iteration. Write informative comments when needed, but avoid them when they are not. Improve the understandability of your code for others by following conventions and naming your objects accurately. Make your programs more robust with intelligent exception handling and learn to assert that everything works as expected using JUnit5 as your testing framework. Impress your peers with an elegant functional programming style and clear-cut object-oriented class design. Writing excellent code isn't just about implementing the functionality. It's about the small important details that make your code more readable, maintainable, flexible, robust, and faster. Java by Comparison teaches you to spot these details and trains you to become a better programmer. What You Need: You need a Java 8 compiler, a text editor, and a fresh mind.That's it. |
| coding dojo data science: Agile Processes in Software Engineering and Extreme Programming Hubert Baumeister, Horst Lichter, Matthias Riebisch, 2017-04-12 This book is open access under a CC BY license. The volume constitutes the proceedings of the 18th International Conference on Agile Software Development, XP 2017, held in Cologne, Germany, in May 2017. The 14 full and 6 short papers presented in this volume were carefully reviewed and selected from 46 submissions. They were organized in topical sections named: improving agile processes; agile in organization; and safety critical software. In addition, the volume contains 3 doctoral symposium papers (from 4 papers submitted). |
| coding dojo data science: Machine Learning in Python Michael Bowles, 2015-04-27 Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions. Machine learning algorithms are at the core of data analytics and visualization. In the past, these methods required a deep background in math and statistics, often in combination with the specialized R programming language. This book demonstrates how machine learning can be implemented using the more widely used and accessible Python programming language. Predict outcomes using linear and ensemble algorithm families Build predictive models that solve a range of simple and complex problems Apply core machine learning algorithms using Python Use sample code directly to build custom solutions Machine learning doesn't have to be complex and highly specialized. Python makes this technology more accessible to a much wider audience, using methods that are simpler, effective, and well tested. Machine Learning in Python shows you how to do this, without requiring an extensive background in math or statistics. |
| coding dojo data science: Sams Teach Yourself HTML and CSS in 24 Hours Dick Oliver, Michael Morrison, 2005-12-14 Learn from the newest, updated edition of the highly acclaimed introduction to HTML, Sams Teach Yourself HTML and CSS In 24 Hours. The seventh edition includes updates to introduce Cascading Style Sheets (CSS) in concert with HTML to produce quality web pages. You'll be able to study revisions that refine examples, as well as provide an enhanced integration with your web pages. You'll also gain a comprehensive understanding with new examples that match the current state of HTML. This carefully organized, well-written tutorial teaches beginning web page development skills, covering only those HTML and CSS tags that are likely to be used on creating a beginning web page. The 24 separate, one hour-long tutorials follow the process by which you should be creating your web page, building knowledge not only of how to create a web page, but building a general knowledge of how to use HTML and CSS in other projects as well. Chapters include: Understanding HTML and XHTML Creating Your Own Web Page Graphics Using Tables to Organize and Lay Out Your Pages Using Style Sheets for Page Layout Dynamic Web Pages |
| coding dojo data science: The Student's Code of Conduct (2013 Edition - EPUB) Lim SK, 2018-11-28 A true disciple is filial; has fraternal love; is vigilant and trustworthy; cares for the community; seeks the company of the virtuous, and pursues knowledge. Di Zi Gui, or The Student's Code of Conduct, has its origins from this line in Analects of Confucius. Inspired by it, Chinese scholar Li Yuxiu of the Kangxi era formulated seven categories of instruction for his disciples' conduct in relation to people and the environment. This set of instructions became Xun Meng Wen, or Lessons for Beginners, and was later revised and renamed as Di Zi Gui by Jia Cunren, a Qing scholar. Long regarded as an essential text for moral instruction, the classic serves as one of the most widely-used texts in educating generations of young Chinese. Its wisdom remains relevant and stands tall as a beacon in a sea of relentless change in today's world. With illustrations depicting modern-day context, this book attests to the classic's insight and practicality, rendering it a must-read that promises the essentials of all human relationships. |
| coding dojo data science: How to Write Good Programs Perdita Stevens, 2020-07-23 Accessible guide to writing good, clear, correct code without stress, aimed at students on early programming courses. |
| coding dojo data science: Beyond the Basic Stuff with Python Al Sweigart, 2020-12-16 BRIDGE THE GAP BETWEEN NOVICE AND PROFESSIONAL You've completed a basic Python programming tutorial or finished Al Sweigart's bestseller, Automate the Boring Stuff with Python. What's the next step toward becoming a capable, confident software developer? Welcome to Beyond the Basic Stuff with Python. More than a mere collection of advanced syntax and masterful tips for writing clean code, you'll learn how to advance your Python programming skills by using the command line and other professional tools like code formatters, type checkers, linters, and version control. Sweigart takes you through best practices for setting up your development environment, naming variables, and improving readability, then tackles documentation, organization and performance measurement, as well as object-oriented design and the Big-O algorithm analysis commonly used in coding interviews. The skills you learn will boost your ability to program--not just in Python but in any language. You'll learn: Coding style, and how to use Python's Black auto-formatting tool for cleaner code Common sources of bugs, and how to detect them with static analyzers How to structure the files in your code projects with the Cookiecutter template tool Functional programming techniques like lambda and higher-order functions How to profile the speed of your code with Python's built-in timeit and cProfile modules The computer science behind Big-O algorithm analysis How to make your comments and docstrings informative, and how often to write them How to create classes in object-oriented programming, and why they're used to organize code Toward the end of the book you'll read a detailed source-code breakdown of two classic command-line games, the Tower of Hanoi (a logic puzzle) and Four-in-a-Row (a two-player tile-dropping game), and a breakdown of how their code follows the book's best practices. You'll test your skills by implementing the program yourself. Of course, no single book can make you a professional software developer. But Beyond the Basic Stuff with Python will get you further down that path and make you a better programmer, as you learn to write readable code that's easy to debug and perfectly Pythonic Requirements: Covers Python 3.6 and higher |
| coding dojo data science: A New U Ryan Craig, 2018-09-11 Every year, the cost of a four-year degree goes up, and the value goes down. But for many students, there's a better answer. So many things are getting faster and cheaper. Movies stream into your living room, without ticket or concession-stand costs. The world's libraries are at your fingertips instantly, and for free. So why is a college education the only thing that seems immune to change? Colleges and universities operate much as they did 40 years ago, with one major exception: tuition expenses have risen dramatically. What's more, earning a degree takes longer than ever before, with the average time to graduate now over five years. As a result, graduates often struggle with enormous debt burdens. Even worse, they often find that degrees did not prepare them to obtain and succeed at good jobs in growing sectors of the economy. While many learners today would thrive with an efficient and affordable postsecondary education, the slow and pricey road to a bachelor's degree is starkly the opposite. In A New U: Faster + Cheaper Alternatives to College, Ryan Craig documents the early days of a revolution that will transform—or make obsolete—many colleges and universities. Alternative routes to great first jobs that do not involve a bachelor's degree are sprouting up all over the place. Bootcamps, income-share programs, apprenticeships, and staffing models are attractive alternatives to great jobs in numerous growing sectors of the economy: coding, healthcare, sales, digital marketing, finance and accounting, insurance, and data analytics. A New U is the first roadmap to these groundbreaking programs, which will lead to more student choice, better matches with employers, higher return on investment of cost and time, and stronger economic growth. |
| coding dojo data science: Program Arcade Games Paul Craven, 2015-12-31 Learn and use Python and PyGame to design and build cool arcade games. In Program Arcade Games: With Python and PyGame, Second Edition, Dr. Paul Vincent Craven teaches you how to create fun and simple quiz games; integrate and start using graphics; animate graphics; integrate and use game controllers; add sound and bit-mapped graphics; and build grid-based games. After reading and using this book, you'll be able to learn to program and build simple arcade game applications using one of today's most popular programming languages, Python. You can even deploy onto Steam and other Linux-based game systems as well as Android, one of today's most popular mobile and tablet platforms. You'll learn: How to create quiz games How to integrate and start using graphics How to animate graphics How to integrate and use game controllers How to add sound and bit-mapped graphics How to build grid-based games Audience“div>This book assumes no prior programming knowledge. |
| coding dojo data science: A Social-Scientific Examination of the Dynamics of Communication, Thought, and Selves Sekalala, Seif, 2022-06-17 Intrapersonal communication has been considered and studied less in comparison to general communication and other related topics. Moreover, intrapersonal communication is usually mentioned in the context of studying other topics, as opposed to being studied singularly. To fully understand the complexity and potential uses of this field of study, intrapersonal communication must be researched further. A Social-Scientific Examination of the Dynamics of Communication, Thought, and Selves focuses on the concept of intrapersonal communication, discusses how and why we communicate with ourselves, and considers how scholars can help humans improve and harness intrapersonal communication in fields such as artificial intelligence. The book also makes a forceful case for the importance and potential utility of intrapersonal communication. Covering topics such as language, sociology, and cognitive science, this reference work is ideal for sociologists, psychologists, industry professionals, academicians, scholars, researchers, practitioners, instructors, and students. |
| coding dojo data science: Makers at School, Educational Robotics and Innovative Learning Environments David Scaradozzi, Lorenzo Guasti, Margherita Di Stasio, Beatrice Miotti, Andrea Monteriù, Paulo Blikstein, 2021-12-10 This open access book contains observations, outlines, and analyses of educational robotics methodologies and activities, and developments in the field of educational robotics emerging from the findings presented at FabLearn Italy 2019, the international conference that brought together researchers, teachers, educators and practitioners to discuss the principles of Making and educational robotics in formal, non-formal and informal education. The editors’ analysis of these extended versions of papers presented at FabLearn Italy 2019 highlight the latest findings on learning models based on Making and educational robotics. The authors investigate how innovative educational tools and methodologies can support a novel, more effective and more inclusive learner-centered approach to education. The following key topics are the focus of discussion: Makerspaces and Fab Labs in schools, a maker approach to teaching and learning; laboratory teaching and the maker approach, models, methods and instruments; curricular and non-curricular robotics in formal, non-formal and informal education; social and assistive robotics in education; the effect of innovative spaces and learning environments on the innovation of teaching, good practices and pilot projects. |
| coding dojo data science: Artificial Intelligence with Python Prateek Joshi, 2017-01-27 Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application. |
| coding dojo data science: Learn Ruby the Hard Way Zed A. Shaw, 2014-12-01 You Will Learn Ruby! Zed Shaw has perfected the world’s best system for learning Ruby. Follow it and you will succeed—just like the hundreds of thousands of beginners Zed has taught to date! You bring the discipline, commitment, and persistence; the author supplies everything else. In Learn Ruby the Hard Way, Third Edition, you’ll learn Ruby by working through 52 brilliantly crafted exercises. Read them. Type their code precisely. (No copying and pasting!) Fix your mistakes. Watch the programs run. As you do, you’ll learn how software works; what good programs look like; how to read, write, and think about code; and how to find and fix your mistakes using tricks professional programmers use. Most importantly, you’ll learn the following, which you need to start writing excellent Ruby software of your own: • Installing your Ruby environment • Organizing and writing code • Ruby symbols and keywords • Basic mathematics • Variables and printing • Strings and text • Interacting with users • Working with files • Using and creating functions • Looping and logic • Arrays and elements • Hashmaps • Program design • Object-oriented programming • Inheritance and composition • Modules, classes, and objects • Project “skeleton” directories • Debugging and automated testing • Advanced user input • Text processing • Basic game development • Basic web development It’ll Be Hard At First. But Soon, You’ll Just Get It—And That Will Feel Great! This tutorial will reward you for every minute you put into it. Soon, you’ll know one of the world’s most powerful, popular programming languages. You’ll be a Ruby programmer. |
| coding dojo data science: Java Programming Ralph Bravaco, Shai Simonson, 2009-02-01 Java Programming, From The Ground Up, with its flexible organization, teaches Java in a way that is refreshing, fun, interesting and still has all the appropriate programming pieces for students to learn. The motivation behind this writing is to bring a logical, readable, entertaining approach to keep your students involved. Each chapter has a Bigger Picture section at the end of the chapter to provide a variety of interesting related topics in computer science. The writing style is conversational and not overly technical so it addresses programming concepts appropriately. Because of the flexibile organization of the text, it can be used for a one or two semester introductory Java programming class, as well as using Java as a second language. The text contains a large variety of carefully designed exercises that are more effective than the competition. |
| coding dojo data science: Business Statistics for Contemporary Decision Making Ignacio Castillo, Ken Black, Tiffany Bayley, 2023-05-08 Show students why business statistics is an increasingly important business skill through a student-friendly pedagogy. In this fourth Canadian edition of Business Statistics For Contemporary Decision Making authors Ken Black, Tiffany Bayley, and Ignacio Castillo uses current real-world data to equip students with the business analytics techniques and quantitative decision-making skills required to make smart decisions in today's workplace. |
| coding dojo data science: R for Data Science Hadley Wickham, Garrett Grolemund, 2016-12-12 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 |
| coding dojo data science: The Rust Programming Language (Covers Rust 2018) Steve Klabnik, Carol Nichols, 2019-09-03 The official book on the Rust programming language, written by the Rust development team at the Mozilla Foundation, fully updated for Rust 2018. The Rust Programming Language is the official book on Rust: an open source systems programming language that helps you write faster, more reliable software. Rust offers control over low-level details (such as memory usage) in combination with high-level ergonomics, eliminating the hassle traditionally associated with low-level languages. The authors of The Rust Programming Language, members of the Rust Core Team, share their knowledge and experience to show you how to take full advantage of Rust's features--from installation to creating robust and scalable programs. You'll begin with basics like creating functions, choosing data types, and binding variables and then move on to more advanced concepts, such as: Ownership and borrowing, lifetimes, and traits Using Rust's memory safety guarantees to build fast, safe programs Testing, error handling, and effective refactoring Generics, smart pointers, multithreading, trait objects, and advanced pattern matching Using Cargo, Rust's built-in package manager, to build, test, and document your code and manage dependencies How best to use Rust's advanced compiler with compiler-led programming techniques You'll find plenty of code examples throughout the book, as well as three chapters dedicated to building complete projects to test your learning: a number guessing game, a Rust implementation of a command line tool, and a multithreaded server. New to this edition: An extended section on Rust macros, an expanded chapter on modules, and appendixes on Rust development tools and editions. |
| coding dojo data science: The DevOps Handbook Gene Kim, Jez Humble, Patrick Debois, John Willis, 2016-10-06 Increase profitability, elevate work culture, and exceed productivity goals through DevOps practices. More than ever, the effective management of technology is critical for business competitiveness. For decades, technology leaders have struggled to balance agility, reliability, and security. The consequences of failure have never been greater―whether it's the healthcare.gov debacle, cardholder data breaches, or missing the boat with Big Data in the cloud. And yet, high performers using DevOps principles, such as Google, Amazon, Facebook, Etsy, and Netflix, are routinely and reliably deploying code into production hundreds, or even thousands, of times per day. Following in the footsteps of The Phoenix Project, The DevOps Handbook shows leaders how to replicate these incredible outcomes, by showing how to integrate Product Management, Development, QA, IT Operations, and Information Security to elevate your company and win in the marketplace. |
| coding dojo data science: The Clean Coder Robert C. Martin, 2011 Presents practical advice on the disciplines, techniques, tools, and practices of computer programming and how to approach software development with a sense of pride, honor, and self-respect. |
| coding dojo data science: Roundtable on Data Science Postsecondary Education National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Division on Engineering and Physical Sciences, Board on Science Education, Computer Science and Telecommunications Board, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, 2020-09-02 Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and government gathered with other experts from across the nation to discuss various topics under this charge. The meetings centered on four central themes: foundations of data science; data science across the postsecondary curriculum; data science across society; and ethics and data science. This publication highlights the presentations and discussions of each meeting. |
| coding dojo data science: Handbook of Research on Immersive Digital Games in Educational Environments Krassmann, Aliane Loureiro, Amaral, Érico Marcelo Hoff do, Nunes, Felipe Becker, Voss, Gleizer Bierhalz, Zunguze, Manuel Constantino, 2018-08-31 Education is increasingly being involved with technological resources in order to meet the needs of emerging generations, consequently changing the way people teach and learn. Game-based learning is a growing aspect of pedagogical practice, and it is important to disseminate research trends and innovations in this field. The Handbook of Research on Immersive Digital Games in Educational Environments provides emerging research exploring the theoretical and practical aspects of digital games and technological resources and applications within contemporary education. Featuring coverage on a broad range of topics such as digital integration, educational simulation, and learning theories, this book is ideally designed for teachers, pre-service teachers, students, educational researchers, and education software developers seeking current research on diverse immersive platforms and three-dimensional environments that support the creation of digital games and other applications to improve teaching and learning processes. |
| coding dojo data science: Python Tricks Dan Bader, 2017 I don't even feel like I've scratched the surface of what I can do with Python With Python Tricks: The Book you'll discover Python's best practices and the power of beautiful & Pythonic code with simple examples and a step-by-step narrative. You'll get one step closer to mastering Python, so you can write beautiful and idiomatic code that comes to you naturally. Learning the ins and outs of Python is difficult-and with this book you'll be able to focus on the practical skills that really matter. Discover the hidden gold in Python's standard library and start writing clean and Pythonic code today. Who Should Read This Book: If you're wondering which lesser known parts in Python you should know about, you'll get a roadmap with this book. Discover cool (yet practical!) Python tricks and blow your coworkers' minds in your next code review. If you've got experience with legacy versions of Python, the book will get you up to speed with modern patterns and features introduced in Python 3 and backported to Python 2. If you've worked with other programming languages and you want to get up to speed with Python, you'll pick up the idioms and practical tips you need to become a confident and effective Pythonista. If you want to make Python your own and learn how to write clean and Pythonic code, you'll discover best practices and little-known tricks to round out your knowledge. What Python Developers Say About The Book: I kept thinking that I wished I had access to a book like this when I started learning Python many years ago. - Mariatta Wijaya, Python Core Developer This book makes you write better Python code! - Bob Belderbos, Software Developer at Oracle Far from being just a shallow collection of snippets, this book will leave the attentive reader with a deeper understanding of the inner workings of Python as well as an appreciation for its beauty. - Ben Felder, Pythonista It's like having a seasoned tutor explaining, well, tricks! - Daniel Meyer, Sr. Desktop Administrator at Tesla Inc. |
| coding dojo data science: Make Your Own Game Jurie Horneman, CoderDojo, 2017-09-07 CoderDojo Nano: Make Your Own Game teaches the fundamentals of the Javascript coding language in a simple, logical way to help kids reach their goal of creating their very own PC game. Children will learn everything from creating a game world, animating characters and determining the physics of movement within the game. Each concept is illustrated with a screenshot to make checking easy, and incredible pixel art from Army of Trolls makes this look like no other coding book. Coder Dojo Nano: Make Your Own Game is the perfect first step that kids can take towards game development. Look out for other titles in the CoderDojo Nano series: CoderDojo Nano: Build Your Own Website. |
| coding dojo data science: Clean Code Robert C. Martin, 2008-08-01 Even bad code can function. But if code isn’t clean, it can bring a development organization to its knees. Every year, countless hours and significant resources are lost because of poorly written code. But it doesn’t have to be that way. Noted software expert Robert C. Martin presents a revolutionary paradigm with Clean Code: A Handbook of Agile Software Craftsmanship. Martin has teamed up with his colleagues from Object Mentor to distill their best agile practice of cleaning code “on the fly” into a book that will instill within you the values of a software craftsman and make you a better programmer–but only if you work at it. What kind of work will you be doing? You’ll be reading code–lots of code. And you will be challenged to think about what’s right about that code, and what’s wrong with it. More importantly, you will be challenged to reassess your professional values and your commitment to your craft. Clean Code is divided into three parts. The first describes the principles, patterns, and practices of writing clean code. The second part consists of several case studies of increasing complexity. Each case study is an exercise in cleaning up code–of transforming a code base that has some problems into one that is sound and efficient. The third part is the payoff: a single chapter containing a list of heuristics and “smells” gathered while creating the case studies. The result is a knowledge base that describes the way we think when we write, read, and clean code. Readers will come away from this book understanding How to tell the difference between good and bad code How to write good code and how to transform bad code into good code How to create good names, good functions, good objects, and good classes How to format code for maximum readability How to implement complete error handling without obscuring code logic How to unit test and practice test-driven development This book is a must for any developer, software engineer, project manager, team lead, or systems analyst with an interest in producing better code. |
| coding dojo data science: The Art of Agile Development James Shore, Shane Warden, 2008 For those considering Extreme Programming, this book provides no-nonsense advice on agile planning, development, delivery, and management taken from the authors' many years of experience. While plenty of books address the what and why of agile development, very few offer the information users can apply directly. |
| coding dojo data science: Refactoring Martin Fowler, Kent Beck, 1999 Refactoring is gaining momentum amongst the object oriented programming community. It can transform the internal dynamics of applications and has the capacity to transform bad code into good code. This book offers an introduction to refactoring. |
| coding dojo data science: Coders at Work Peter Seibel, 2009-12-21 Peter Seibel interviews 15 of the most interesting computer programmers alive today in Coders at Work, offering a companion volume to Apress’s highly acclaimed best-seller Founders at Work by Jessica Livingston. As the words “at work” suggest, Peter Seibel focuses on how his interviewees tackle the day-to-day work of programming, while revealing much more, like how they became great programmers, how they recognize programming talent in others, and what kinds of problems they find most interesting. Hundreds of people have suggested names of programmers to interview on the Coders at Work web site: www.codersatwork.com. The complete list was 284 names. Having digested everyone’s feedback, we selected 15 folks who’ve been kind enough to agree to be interviewed: Frances Allen: Pioneer in optimizing compilers, first woman to win the Turing Award (2006) and first female IBM fellow Joe Armstrong: Inventor of Erlang Joshua Bloch: Author of the Java collections framework, now at Google Bernie Cosell: One of the main software guys behind the original ARPANET IMPs and a master debugger Douglas Crockford: JSON founder, JavaScript architect at Yahoo! L. Peter Deutsch: Author of Ghostscript, implementer of Smalltalk-80 at Xerox PARC and Lisp 1.5 on PDP-1 Brendan Eich: Inventor of JavaScript, CTO of the Mozilla Corporation Brad Fitzpatrick: Writer of LiveJournal, OpenID, memcached, and Perlbal Dan Ingalls: Smalltalk implementor and designer Simon Peyton Jones: Coinventor of Haskell and lead designer of Glasgow Haskell Compiler Donald Knuth: Author of The Art of Computer Programming and creator of TeX Peter Norvig: Director of Research at Google and author of the standard text on AI Guy Steele: Coinventor of Scheme and part of the Common Lisp Gang of Five, currently working on Fortress Ken Thompson: Inventor of UNIX Jamie Zawinski: Author of XEmacs and early Netscape/Mozilla hacker |
| coding dojo data science: Web Information Systems and Applications Guojun Wang, Xuemin Lin, James Hendler, Wei Song, Zhuoming Xu, Genggeng Liu, 2020-09-22 This book constitutes the proceedings of the 17th International Conference on Web Information Systems and Applications, WISA 2020, held in Guangzhou, China, in September 2020. The 42 full papers and 16 short papers presented were carefully reviewed and selected from 165 submissions. The papers are grouped in topical sections on world wide web, recommendation, query processing and algorithm, natural language processing, machine learning, graph query, edge computing and data mining, data privacy and security, and blockchain. |
| coding dojo data science: Dojo James E. Harmon, 2008-06-11 Dojo offers Web developers and designers a powerful JavaScript toolkit for rapidly developing robust Ajax applications. Now, for the first time, there’s a complete, example-rich developer’s guide to Dojo and its growing library of prepackaged widgets. Reviewed and endorsed by the Dojo Foundation, the creators of Dojo, this book brings together all the hands-on guidance and tested code samples you need to succeed. Expert Web developer James E. Harmon begins by demonstrating how to “Ajax-ify” existing applications and pages with Dojo, adding Ajax features such as client- and server-side validation as quickly and nondisruptively as possible. Next, he presents in-depth coverage of Dojo’s user interface, form, layout, and specialized Widgets, showing how they work and how to use them most effectively. Among the Widgets, he covers in detail: Date Pickers, Rich Text Editors, Combo Boxes, Expandable Outlines, and many others. In conclusion, Harmon introduces the Dojo toolkit’s powerful capabilities for simplifying Ajax development. He thoroughly explains Dojo’s helper functions, shortcuts, and special methods, illuminating each feature with examples of the JavaScript problems it can solve. This section’s far-ranging coverage includes strings, JSON support, event handling, Ajax remoting, Dojo and the DOM, testing, debugging, and much more. All source code examples are provided on a companion Web site, including source code for a complete tutorial case study application. |
| coding dojo data science: Analyzing Baseball Data with R Max Marchi, Jim Albert, 2016-04-05 With its flexible capabilities and open-source platform, R has become a major tool for analyzing detailed, high-quality baseball data. Analyzing Baseball Data with R provides an introduction to R for sabermetricians, baseball enthusiasts, and students interested in exploring the rich sources of baseball data. It equips readers with the necessary skills and software tools to perform all of the analysis steps, from gathering the datasets and entering them in a convenient format to visualizing the data via graphs to performing a statistical analysis. The authors first present an overview of publicly available baseball datasets and a gentle introduction to the type of data structures and exploratory and data management capabilities of R. They also cover the traditional graphics functions in the base package and introduce more sophisticated graphical displays available through the lattice and ggplot2 packages. Much of the book illustrates the use of R through popular sabermetrics topics, including the Pythagorean formula, runs expectancy, career trajectories, simulation of games and seasons, patterns of streaky behavior of players, and fielding measures. Each chapter contains exercises that encourage readers to perform their own analyses using R. All of the datasets and R code used in the text are available online. This book helps readers answer questions about baseball teams, players, and strategy using large, publically available datasets. It offers detailed instructions on downloading the datasets and putting them into formats that simplify data exploration and analysis. Through the book’s various examples, readers will learn about modern sabermetrics and be able to conduct their own baseball analyses. |
| coding dojo data science: The Pragmatic Programmer Andrew Hunt, David Thomas, 1999-10-20 What others in the trenches say about The Pragmatic Programmer... “The cool thing about this book is that it’s great for keeping the programming process fresh. The book helps you to continue to grow and clearly comes from people who have been there.” — Kent Beck, author of Extreme Programming Explained: Embrace Change “I found this book to be a great mix of solid advice and wonderful analogies!” — Martin Fowler, author of Refactoring and UML Distilled “I would buy a copy, read it twice, then tell all my colleagues to run out and grab a copy. This is a book I would never loan because I would worry about it being lost.” — Kevin Ruland, Management Science, MSG-Logistics “The wisdom and practical experience of the authors is obvious. The topics presented are relevant and useful.... By far its greatest strength for me has been the outstanding analogies—tracer bullets, broken windows, and the fabulous helicopter-based explanation of the need for orthogonality, especially in a crisis situation. I have little doubt that this book will eventually become an excellent source of useful information for journeymen programmers and expert mentors alike.” — John Lakos, author of Large-Scale C++ Software Design “This is the sort of book I will buy a dozen copies of when it comes out so I can give it to my clients.” — Eric Vought, Software Engineer “Most modern books on software development fail to cover the basics of what makes a great software developer, instead spending their time on syntax or technology where in reality the greatest leverage possible for any software team is in having talented developers who really know their craft well. An excellent book.” — Pete McBreen, Independent Consultant “Since reading this book, I have implemented many of the practical suggestions and tips it contains. Across the board, they have saved my company time and money while helping me get my job done quicker! This should be a desktop reference for everyone who works with code for a living.” — Jared Richardson, Senior Software Developer, iRenaissance, Inc. “I would like to see this issued to every new employee at my company....” — Chris Cleeland, Senior Software Engineer, Object Computing, Inc. “If I’m putting together a project, it’s the authors of this book that I want. . . . And failing that I’d settle for people who’ve read their book.” — Ward Cunningham Straight from the programming trenches, The Pragmatic Programmer cuts through the increasing specialization and technicalities of modern software development to examine the core process--taking a requirement and producing working, maintainable code that delights its users. It covers topics ranging from personal responsibility and career development to architectural techniques for keeping your code flexible and easy to adapt and reuse. Read this book, and you'll learn how to Fight software rot; Avoid the trap of duplicating knowledge; Write flexible, dynamic, and adaptable code; Avoid programming by coincidence; Bullet-proof your code with contracts, assertions, and exceptions; Capture real requirements; Test ruthlessly and effectively; Delight your users; Build teams of pragmatic programmers; and Make your developments more precise with automation. Written as a series of self-contained sections and filled with entertaining anecdotes, thoughtful examples, and interesting analogies, The Pragmatic Programmer illustrates the best practices and major pitfalls of many different aspects of software development. Whether you're a new coder, an experienced programmer, or a manager responsible for software projects, use these lessons daily, and you'll quickly see improvements in personal productivity, accuracy, and job satisfaction. You'll learn skills and develop habits and attitudes that form the foundation for long-term success in your career. You'll become a Pragmatic Programmer. |
| coding dojo data science: Research Challenges in Information Science Fabiano Dalpiaz, Jelena Zdravkovic, Pericles Loucopoulos, 2020-06-24 This book constitutes the proceedings of the 14th International Conference on Research Challenges in Information Sciences, RCIS 2020, held in Limassol, Cyprus, during September 23-25, 2020. The conference was originally scheduled for May 2020, but the organizing committee was forced to postpone the conference due to the outbreak of the COVID-19 pandemic. The scope of RCIS 2020 is summarized by the thematic areas of information systems and their engineering; user-oriented approaches; data and information management; business process management; domain-specific information systems engineering; data science; information infrastructures, and reflective research and practice. The 26 full papers and 3 work in progress papers presented in this volume were carefully reviewed and selected from 106 submissions. They were organized in topical sections named: Data Analytics and Business Intelligence; Digital Enterprise and Technologies; Human Factors in Information Systems; Information Systems Development and Testing; Machine Learning and Text Processing; and Security and Privacy. The volume also contains 12 poster and demo-papers, and 4 Doctoral Consortium papers. |
| coding dojo data science: Tiny Python Projects Ken Youens-Clark, 2020-09-01 ”Tiny Python Projects is a gentle and amusing introduction to Python that will firm up key programming concepts while also making you giggle.”—Amanda Debler, Schaeffler Key Features Learn new programming concepts through 21-bitesize programs Build an insult generator, a Tic-Tac-Toe AI, a talk-like-a-pirate program, and more Discover testing techniques that will make you a better programmer Code-along with free accompanying videos on YouTube Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About The Book The 21 fun-but-powerful activities in Tiny Python Projects teach Python fundamentals through puzzles and games. You’ll be engaged and entertained with every exercise, as you learn about text manipulation, basic algorithms, and lists and dictionaries, and other foundational programming skills. Gain confidence and experience while you create each satisfying project. Instead of going quickly through a wide range of concepts, this book concentrates on the most useful skills, like text manipulation, data structures, collections, and program logic with projects that include a password creator, a word rhymer, and a Shakespearean insult generator. Author Ken Youens-Clark also teaches you good programming practice, including writing tests for your code as you go. What You Will Learn Write command-line Python programs Manipulate Python data structures Use and control randomness Write and run tests for programs and functions Download testing suites for each project This Book Is Written For For readers familiar with the basics of Python programming. About The Author Ken Youens-Clark is a Senior Scientific Programmer at the University of Arizona. He has an MS in Biosystems Engineering and has been programming for over 20 years. Table of Contents 1 How to write and test a Python program 2 The crow’s nest: Working with strings 3 Going on a picnic: Working with lists 4 Jump the Five: Working with dictionaries 5 Howler: Working with files and STDOUT 6 Words count: Reading files and STDIN, iterating lists, formatting strings 7 Gashlycrumb: Looking items up in a dictionary 8 Apples and Bananas: Find and replace 9 Dial-a-Curse: Generating random insults from lists of words 10 Telephone: Randomly mutating strings 11 Bottles of Beer Song: Writing and testing functions 12 Ransom: Randomly capitalizing text 13 Twelve Days of Christmas: Algorithm design 14 Rhymer: Using regular expressions to create rhyming words 15 The Kentucky Friar: More regular expressions 16 The Scrambler: Randomly reordering the middles of words 17 Mad Libs: Using regular expressions 18 Gematria: Numeric encoding of text using ASCII values 19 Workout of the Day: Parsing CSV files, creating text table output 20 Password strength: Generating a secure and memorable password 21 Tic-Tac-Toe: Exploring state 22 Tic-Tac-Toe redux: An interactive version with type hints |
| coding dojo data science: Practical Object-Oriented Design in Ruby Sandi Metz, 2012-09-05 The Complete Guide to Writing More Maintainable, Manageable, Pleasing, and Powerful Ruby Applications Ruby’s widely admired ease of use has a downside: Too many Ruby and Rails applications have been created without concern for their long-term maintenance or evolution. The Web is awash in Ruby code that is now virtually impossible to change or extend. This text helps you solve that problem by using powerful real-world object-oriented design techniques, which it thoroughly explains using simple and practical Ruby examples. Sandi Metz has distilled a lifetime of conversations and presentations about object-oriented design into a set of Ruby-focused practices for crafting manageable, extensible, and pleasing code. She shows you how to build new applications that can survive success and repair existing applications that have become impossible to change. Each technique is illustrated with extended examples, all downloadable from the companion Web site, poodr.info. The first title to focus squarely on object-oriented Ruby application design, Practical Object-Oriented Design in Ruby will guide you to superior outcomes, whatever your previous Ruby experience. Novice Ruby programmers will find specific rules to live by; intermediate Ruby programmers will find valuable principles they can flexibly interpret and apply; and advanced Ruby programmers will find a common language they can use to lead development and guide their colleagues. This guide will help you Understand how object-oriented programming can help you craft Ruby code that is easier to maintain and upgrade Decide what belongs in a single Ruby class Avoid entangling objects that should be kept separate Define flexible interfaces among objects Reduce programming overhead costs with duck typing Successfully apply inheritance Build objects via composition Design cost-effective tests Solve common problems associated with poorly designed Ruby code |
| coding dojo data science: Deep Learning Applications, Volume 2 M. Arif Wani, Taghi Khoshgoftaar, Vasile Palade, 2020-12-14 This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers. |
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Computer science and artificial intelligence curriculum for K-12 ...
Code.org provides free computer science and AI curriculum, plus professional development to support any teacher—no coding experience needed!
Computer Science for Students | Learn, Explore, and Create with …
Start with an Hour of Code, then explore self-paced coding courses on apps, games, and animations. Try App Lab, Game Lab, or Web Lab—and learn about AI, real-world careers, and …
Code.org for Parents | At-Home Computer Science Resources
Learn the fundamentals of computer science with free Hour of Code activities, featuring basic drag-and-drop coding blocks. There are tons of fun, hour-long options to choose from!
Hour of Code | Code.org
This movement helps to highlight how coding is behind everything from your favorite shoes to the music you listen to. By jumping into fun activities and starting your own projects, you can learn …
Unit: Course 2 - Code.org
Anyone can learn computer science. Make games, apps and art with code.
Minecraft | Code.org
Find the missing star, unlock hidden gags, and interact with a cast of mobs. Help the Agent overcome stage fright as you solve fun coding puzzles. Watch your coding skills shine in an …
Web Lab | Build Websites with HTML & CSS - Code.org
Web Lab lets students create and publish real websites using HTML and CSS. A hands-on way to learn web design and coding in middle and high school.
Online Computer Science Courses for Students | Code.org
Discover free and paid online courses that help students build CS skills, explore coding, and learn at their own pace with flexible learning options.
Code.org
Want to try coding without signing in? Dance Party Code a Dance Party to share with friends and family. Featuring Beyoncé, Harry Styles, Lizzo, Lil Nas X, Selena Gomez, music from Disney's …
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Code Club World: Make cool stuff with free coding games and activities
