Advance Your Career In Data Science
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Advance Your Career In Data Science
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Author : Henry Harvin
language : en
Publisher: Henry Harvin
Release Date : 2023-10-04
Advance Your Career In Data Science written by Henry Harvin and has been published by Henry Harvin this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-04 with Computers categories.
Data science is the study of data to derive useful business insights. In order to analyze massive volumes of data, this multidisciplinary approach incorporates ideas and methods from the domains of mathematics, statistics, artificial intelligence, and computer engineering. You must be introduced to the many components to "Advance Your Career With Data Science" first. You will learn about the statistics that are applied in the area and how to use them practically from this book. Also, this book will assist you in concentrating on the most fundamental aspects of data science for a better grasp of the field.
Build A Career In Data Science
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Author : Emily Robinson
language : en
Publisher: Simon and Schuster
Release Date : 2020-03-06
Build A Career In Data Science written by Emily Robinson and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-06 with Computers categories.
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
How To Lead In Data Science
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Author : Jike Chong
language : en
Publisher: Simon and Schuster
Release Date : 2021-12-28
How To Lead In Data Science written by Jike Chong and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-28 with Computers categories.
A field guide for the unique challenges of data science leadership, filled with transformative insights, personal experiences, and industry examples. In How To Lead in Data Science you will learn: Best practices for leading projects while balancing complex trade-offs Specifying, prioritizing, and planning projects from vague requirements Navigating structural challenges in your organization Working through project failures with positivity and tenacity Growing your team with coaching, mentoring, and advising Crafting technology roadmaps and championing successful projects Driving diversity, inclusion, and belonging within teams Architecting a long-term business strategy and data roadmap as an executive Delivering a data-driven culture and structuring productive data science organizations How to Lead in Data Science is full of techniques for leading data science at every seniority level—from heading up a single project to overseeing a whole company's data strategy. Authors Jike Chong and Yue Cathy Chang share hard-won advice that they've developed building data teams for LinkedIn, Acorns, Yiren Digital, large asset-management firms, Fortune 50 companies, and more. You'll find advice on plotting your long-term career advancement, as well as quick wins you can put into practice right away. Carefully crafted assessments and interview scenarios encourage introspection, reveal personal blind spots, and highlight development areas. About the technology Lead your data science teams and projects to success! To make a consistent, meaningful impact as a data science leader, you must articulate technology roadmaps, plan effective project strategies, support diversity, and create a positive environment for professional growth. This book delivers the wisdom and practical skills you need to thrive as a data science leader at all levels, from team member to the C-suite. About the book How to Lead in Data Science shares unique leadership techniques from high-performance data teams. It’s filled with best practices for balancing project trade-offs and producing exceptional results, even when beginning with vague requirements or unclear expectations. You’ll find a clearly presented modern leadership framework based on current case studies, with insights reaching all the way to Aristotle and Confucius. As you read, you’ll build practical skills to grow and improve your team, your company’s data culture, and yourself. What's inside How to coach and mentor team members Navigate an organization’s structural challenges Secure commitments from other teams and partners Stay current with the technology landscape Advance your career About the reader For data science practitioners at all levels. About the author Dr. Jike Chong and Yue Cathy Chang build, lead, and grow high-performing data teams across industries in public and private companies, such as Acorns, LinkedIn, large asset-management firms, and Fortune 50 companies. Table of Contents 1 What makes a successful data scientist? PART 1 THE TECH LEAD: CULTIVATING LEADERSHIP 2 Capabilities for leading projects 3 Virtues for leading projects PART 2 THE MANAGER: NURTURING A TEAM 4 Capabilities for leading people 5 Virtues for leading people PART 3 THE DIRECTOR: GOVERNING A FUNCTION 6 Capabilities for leading a function 7 Virtues for leading a function PART 4 THE EXECUTIVE: INSPIRING AN INDUSTRY 8 Capabilities for leading a company 9 Virtues for leading a company PART 5 THE LOOP AND THE FUTURE 10 Landscape, organization, opportunity, and practice 11 Leading in data science and a future outlook
Advanced Mathematical Applications In Data Science
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Author : Biswadip Basu Mallik
language : en
Publisher: Bentham Science Publishers
Release Date : 2023-08-24
Advanced Mathematical Applications In Data Science written by Biswadip Basu Mallik and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-24 with Computers categories.
Advanced Mathematical Applications in Data Science comprehensively explores the crucial role mathematics plays in the field of data science. Each chapter is contributed by scientists, researchers, and academicians. The 13 chapters cover a range of mathematical concepts utilized in data science, enabling readers to understand the intricate connection between mathematics and data analysis. The book covers diverse topics, including, machine learning models, the Kalman filter, data modeling, artificial neural networks, clustering techniques, and more, showcasing the application of advanced mathematical tools for effective data processing and analysis. With a strong emphasis on real-world applications, the book offers a deeper understanding of the foundational principles behind data analysis and its numerous interdisciplinary applications. This reference is an invaluable resource for graduate students, researchers, academicians, and learners pursuing a research career in mathematical computing or completing advanced data science courses. Key Features: Comprehensive coverage of advanced mathematical concepts and techniques in data science Contributions from established scientists, researchers, and academicians Real-world case studies and practical applications of mathematical methods Focus on diverse areas, such as image classification, carbon emission assessment, customer churn prediction, and healthcare data analysis In-depth exploration of data science's connection with mathematics, computer science, and artificial intelligence Scholarly references for each chapter Suitable for readers with high school-level mathematical knowledge, making it accessible to a broad audience in academia and industry.
Data Science And Analytics
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Author : Dr.Venkateswara Rao Gera
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-09-07
Data Science And Analytics written by Dr.Venkateswara Rao Gera and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-07 with Language Arts & Disciplines categories.
Dr.Venkateswara Rao Gera, Professor, Department of Computer Science and Engineering, Kallam Haranadhareddy Institute of Technology, NH-16, Chowdavaram, Guntur, (D.T), Andhra Pradesh, India. Dr.Padamata Ramesh Babu, Associate Professor, Department of Computer Science and Engineering – Data Science, Bapatla Engineering College, Bapatla (D.T), Andhra Pradesh, India. Dr.Kalyankumar Dasari, Associate Professor & Head, Department of Computer Science and Engineering - Cyber Security, Chalapathi Institute of Technology, A.R.Nagar, Mothadaka, Guntur (D.T), Andhra Pradesh, India. Dr.Shaik Mohammed Jany, Associate Professor, Department of Information Technology and CSE (AI), Narasaraopeta Engineering College, Narasaraopeta, Palnadu (D.T), Andhra Pradesh, India.
Data Science Algorithms In A Week
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Author : Dávid Natingga
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-10-31
Data Science Algorithms In A Week written by Dávid Natingga and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-31 with Computers categories.
Build a strong foundation of machine learning algorithms in 7 days Key FeaturesUse Python and its wide array of machine learning libraries to build predictive models Learn the basics of the 7 most widely used machine learning algorithms within a weekKnow when and where to apply data science algorithms using this guideBook Description Machine learning applications are highly automated and self-modifying, and continue to improve over time with minimal human intervention, as they learn from the trained data. To address the complex nature of various real-world data problems, specialized machine learning algorithms have been developed. Through algorithmic and statistical analysis, these models can be leveraged to gain new knowledge from existing data as well. Data Science Algorithms in a Week addresses all problems related to accurate and efficient data classification and prediction. Over the course of seven days, you will be introduced to seven algorithms, along with exercises that will help you understand different aspects of machine learning. You will see how to pre-cluster your data to optimize and classify it for large datasets. This book also guides you in predicting data based on existing trends in your dataset. This book covers algorithms such as k-nearest neighbors, Naive Bayes, decision trees, random forest, k-means, regression, and time-series analysis. By the end of this book, you will understand how to choose machine learning algorithms for clustering, classification, and regression and know which is best suited for your problem What you will learnUnderstand how to identify a data science problem correctlyImplement well-known machine learning algorithms efficiently using PythonClassify your datasets using Naive Bayes, decision trees, and random forest with accuracyDevise an appropriate prediction solution using regressionWork with time series data to identify relevant data events and trendsCluster your data using the k-means algorithmWho this book is for This book is for aspiring data science professionals who are familiar with Python and have a little background in statistics. You’ll also find this book useful if you’re currently working with data science algorithms in some capacity and want to expand your skill set
Advanced Data Analytics With Aws
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Author : Joseph Conley
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2024-04-17
Advanced Data Analytics With Aws written by Joseph Conley and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-17 with Computers categories.
Master the Fundamentals of Data Analytics at Scale KEY FEATURES ● Comprehensive guide to constructing data engineering workflows spanning diverse data sources ● Expert techniques for transforming and visualizing data to extract actionable insights ● Advanced methodologies for analyzing data and employing machine learning to uncover intricate patterns DESCRIPTION Embark on a transformative journey into the realm of data analytics with AWS with this practical and incisive handbook. Begin your exploration with an insightful introduction to the fundamentals of data analytics, setting the stage for your AWS adventure. The book then covers collecting data efficiently and effectively on AWS, laying the groundwork for insightful analysis. It will dive deep into processing data, uncovering invaluable techniques to harness the full potential of your datasets. The book will equip you with advanced data analysis skills, unlocking the ability to discern complex patterns and insights. It covers additional use cases for data analysis on AWS, from predictive modeling to sentiment analysis, expanding your analytical horizons. The final section of the book will utilize the power of data virtualization and interaction, revolutionizing the way you engage with and derive value from your data. Gain valuable insights into emerging trends and technologies shaping the future of data analytics, and conclude your journey with actionable next steps, empowering you to continue your data analytics odyssey with confidence. WHAT WILL YOU LEARN ● Construct streamlined data engineering workflows capable of ingesting data from diverse sources and formats. ● Employ data transformation tools to efficiently cleanse and reshape data, priming it for analysis. ● Perform ad-hoc queries for preliminary data exploration, uncovering initial insights. ● Utilize prepared datasets to craft compelling, interactive data visualizations that communicate actionable insights. ● Develop advanced machine learning and Generative AI workflows to delve into intricate aspects of complex datasets, uncovering deeper insights. WHO IS THIS BOOK FOR? This book is ideal for aspiring data engineers, analysts, and data scientists seeking to deepen their understanding and practical skills in data engineering, data transformation, visualization, and advanced analytics. It is also beneficial for professionals and students looking to leverage AWS services for their data-related tasks. TABLE OF CONTENTS 1. Introduction to Data Analytics and AWS 2. Getting Started with AWS 3. Collecting Data with AWS 4. Processing Data on AWS 5. Descriptive Analytics on AWS 6. Advanced Data Analysis on AWS 7. Additional Use Cases for Data Analysis 8. Data Visualization and Interaction on AWS 9. The Future of Data Analytics 10. Conclusion and Next Steps Index
The Data Science Toolset
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Author : Barrett Williams
language : en
Publisher: Barrett Williams
Release Date : 2025-03-01
The Data Science Toolset written by Barrett Williams and has been published by Barrett Williams this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-01 with Computers categories.
Unlock the ultimate guide to mastering the expansive world of data science with "The Data Science Toolset." Whether you're a curious beginner or a seasoned analyst, this eBook is your gateway to an arsenal of powerful tools and techniques designed to elevate your data analysis skills and transform the way you work with data. Dive into the essential aspects of data tool selection, from understanding your data requirements to conducting thorough cost-benefit analyses. Unleash the potential of Python with in-depth guidance on libraries like Pandas and NumPy, ensuring you can manipulate data with ease. Elevate your visualization game with advanced techniques using Matplotlib, Seaborn, and interactive Plotly plots. Learn to clean, wrangle, and transform data efficiently and explore R's robust ecosystem, from data manipulation and visualization with ggplot2 to sophisticated statistical modeling. Discover how SQL can be your ally in writing efficient queries and handling complex data operations. Automation awaits you as you delve into workflow tools and pipeline building with Apache Airflow and Luigi. Excel doesn't get left behind; unlock its potential with advanced functions, pivot tables, and powerful data transformation using Power Query. Venture into the world of machine learning, understanding algorithms and model deployment with practical tools like Flask and Docker. Time series analysis and NLP techniques open doors to predictive and text data analysis, while big data frameworks like Hadoop and Spark redefine what you can achieve with vast datasets. With a focus on ethics and privacy, this eBook ensures you maintain integrity and compliance throughout your data journey. Finally, sustain your growth by exploring ways to stay current in the field and expand your professional network. "The Data Science Toolset" is more than a book—it's your companion for navigating the ever-evolving landscape of data science, empowering you with the knowledge to succeed in this dynamic domain. Get ready to transform your data insights into impactful decisions.
10 Tips And Stories For New Data Analytics Leader
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Author : Jacob So
language : en
Publisher: Jacob So
Release Date : 2023-02-22
10 Tips And Stories For New Data Analytics Leader written by Jacob So and has been published by Jacob So this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-22 with Computers categories.
What are you likely to face as a new Analytics Leader? What should you consider before joining a company as their Head of Analytics? What are the expectations from your key stakeholders? "10 Tips for New Data Analytics Leader" is a guide that offers practical advice for individuals who are starting out as data analytics leaders. Whether you are a newly appointed manager, a team lead or a seasoned analyst transitioning into a leadership role, this ebook provides you with essential tips and strategies that will help you succeed.
Web Development Career Master Plan
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Author : Frank W. Zammetti
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-06-07
Web Development Career Master Plan written by Frank W. Zammetti and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-07 with Computers categories.
Gain a comprehensive understanding of web development, from foundational technologies to advanced topics, along with interview tactics, growth opportunities, and strategies to kickstart a successful career in this field Key Features Gain insights into the role, responsibilities, and qualities that define a good web developer Uncover steps to establish a solid technical foundation for finding employment in the field of web development Explore tools and techniques you’ll work with and understand how they all fit together Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe world of web development can seem daunting when you’re a beginner and don’t know where to get started. If you’re passionate about web development and want to learn the art of creating captivating websites, then this book is for you. Web Development Career Master Plan will take you on a learning journey, starting from the foundations and progressing through advanced concepts and career development strategies. You'll learn the core pillars of web development, including HTML, CSS, and JavaScript. As you go deeper, you'll explore the landscape of frameworks, libraries, and toolkits. This book also provides valuable insights into containerization, version control, Linux, and IDEs. Additionally, you’ll find expert advice on interview tactics and career growth strategies to secure your first job in web development. But the journey doesn’t end there. While you navigate the twists and turns of web development, you’ll also get a glimpse of what it means to be a web developer, the day-to-day aspects of the job, and the technologies you'll be working with. By the end of this web development book, you'll be well-equipped with the knowledge and tools you need to kick-start your journey and succeed in this dynamic field.What you will learn Understand the fundamentals of HTML, CSS, and JavaScript to build web pages Understand the different types of web development jobs and their requirements Explore the qualifications and attributes that make a candidate employable and adaptable in a dynamic job market Analyze the modern web development landscape to predict emerging trends Discover effective strategies to secure your first job opportunity Cultivate the essential skills needed for career development Who this book is for If you're an aspiring web developer with a passion for problem-solving and innovation, then this book is for you. Whether you're a dedicated learner, a tech enthusiast, or someone interested in building a career in the field, this book covers the web development essentials you need for a great start. Individuals without any prior technical or software development knowledge can also use this book to gain a high-level overview and a foundational introduction to the world of web development.