Ciencia de datos y Machine Learning con Python

You are a programmer. You already know many languages, but Python isn't one of them. Today, you need to get up-to-speed with Python in a short period of time, but your search has so far come up with disconnected, unrelated tutorials or guides. Learn Python in 3 hours is a fast-paced, action-packed course that maximizes your time; it's designed from the ground up to bring you from zero to hero in the shortest time. The course is based on many years of Python development experience in both large enterprises and nimble startups. In particular, the course's hands-on and practical approach comes from the author's experience in rapidly iterating and shipping products in a startup setting, where responsiveness and speed are key. With Learn Python in 3 hours, you will be up-and-running with Python like you are with your other languages, proving your value and expertise to your team today, and building your CV and skillset for tomorrow. About The Author Colibri is a technology consultancy company founded in 2015 by James Cross and Ingrid Funie. The company works to help its clients navigate the rapidly changing and complex world of emerging technologies, with deep expertise in areas like big data, data science, Machine Learning, and Cloud Computing. Over the past few years, they have worked with some of the world's largest and most prestigious companies, including a tier 1 investment bank, a leading management consultancy group, and one of the world's most popular soft drinks companies, helping all of them to better make sense of their data, and process it in more intelligent ways. The company lives by its motto: Data - Intelligence - Action. Rudy Lai is the founder of QuantCopy, a sales acceleration startup using AI to write sales emails to prospects. By taking in leads from your pipelines, QuantCopy researches them online and generates sales emails from that data. It also has a suite of email automation tools to schedul

JIRA Software is an agile project management tool that supports any agile methodology, be it scrum, Kanban, or your own unique flavor. From agile boards to reports, you can plan, track, and manage all your agile software development projects from a single tool. JIRA Software brings the power of the agile methodology to Atlassian's JIRA Software.With this course, you will dive straight into the action, exploring critical agile terminologies and concepts in the context of JIRA Software. You will learn how to plan, track, and release great software. This course will teach you how to choose a workflow, set issue types and assign permissions.You will learn to stay connected with your team from anywhere to ensure great development.You will also be able to use JIRA Dashboards to broadcast your project results to all stakeholders so everyone is aligned.By the end of this course, you will have developed a great working knowledge of JIRA Software, thus making your project management much more efficient.This course uses JIRA 7, while not the latest version available, it provides relevant and informative content for legacy users of JIRA.About the AuthorDavid Harned is a PMO Director for Monotype and is a motivated and inspired leader of Agile thinkers, driving adoption within enterprises that have numerous parallel-distributed, highly autonomous, and self-organized teams. He is a design, usability, and customer experience advocate. He has managed developer group building in the e-commerce retail business. David is an Agile believer and uses Scrum, Kanban, and Lean as well as hybrid approaches for project management. David is an expert in the implementation of Scrum at scale using standards and tools for process and visibility across the enterprise.David holds many certifications in the project management and Agile domains including: PMI Project Management Professional, Digital Project Manager, Certified ScrumMaster, Certified Scrum Product Owner,

ML.NET enables developers utilize their .NET skills to easily integrate machine learning into virtually any .NET application. This course will teach you how to implement machine learning and build models using Microsoft's new Machine Learning library, ML.NET. You will learn how to leverage the library effectively to build and integrate machine learning into your .NET applications.By taking this course, you will learn how to implement various machine learning tasks and algorithms using the ML.NET library, and use the Model Builder and CLI to build custom models using AutoML.You will load and prepare data to train and evaluate a model; make predictions with a trained model; and, crucially, retrain it. You will cover image classification, sentiment analysis, recommendation engines, and more! You'll also work through techniques to improve model performance and accuracy, and extend ML.NET by leveraging pre-trained TensorFlow models using transfer learning in your ML.NET application and some advanced techniques.By the end of the course, even if you previously lacked existing machine learning knowledge, you will be confident enough to perform machine learning tasks and build custom ML models using the ML.NET library.About the AuthorKarl Tillström has been passionate about making computers do amazing things ever since childhood and is strongly driven by the magic possibilities you can create using programming. This makes advances in machine learning and AI his holy grail; since he took his first class in artificial neural networks in 2007, he has experimented with machine learning by building all sorts of things, ranging from Bitcoin price prediction to self-learning Gomoku playing AI.Karl is a software engineer and systems architect with over 15 years' professional experience in .Net, building a wide variety of systems ranging from airline mobile check-ins to online payment systems.Driven by his passion, he took a Master's degree in Co

PySpark helps you perform data analysis at-scale; it enables you to build more scalable analyses and pipelines. This course starts by introducing you to PySpark's potential for performing effective analyses of large datasets. You'll learn how to interact with Spark from Python and connect Jupyter to Spark to provide rich data visualizations. After that, you'll delve into various Spark components and its architecture.You'll learn to work with Apache Spark and perform ML tasks more smoothly than before. Gathering and querying data using Spark SQL, to overcome challenges involved in reading it. You'll use the DataFrame API to operate with Spark MLlib and learn about the Pipeline API. Finally, we provide tips and tricks for deploying your code and performance tuning.By the end of this course, you will not only be able to perform efficient data analytics but will have also learned to use PySpark to easily analyze large datasets at-scale in your organization.About the AuthorDanny Meijer works as the Lead Data Engineer in the Netherlands for the Data and Analytics department of a leading sporting goods retailer. He is a Business Process Expert, big data scientist and additionally a data engineer, which gives him a unique mix of skills—the foremost of which is his business-first approach to data science and data engineering.He has over 13-years' IT experience across various domains and skills ranging from (big) data modeling, architecture, design, and development as well as project and process management; he also has extensive experience with process mining, data engineering on big data, and process improvement.As a certified data scientist and big data professional, he knows his way around data and analytics, and is proficient in various types of programming language. He has extensive experience with various big data technologies and is fluent in everything: NoSQL, Hadoop, Python, and of course Spark.Danny is a driven person, motivated

PostgreSQL is one of the most powerful, secure, and enterprise-ready open-source databases used by modern applications, startups, and Fortune-500 companies alike. This course is designed to take you from a complete beginner to an advanced PostgreSQL professional by building a rock-solid foundation and then moving into real-world database design, performance tuning, and production-level best practices.You will start by learning what databases are, how PostgreSQL works, and how to install and configure PostgreSQL on your system. Step-by-step, you will master SQL fundamentals including tables, keys, constraints, joins, subqueries, views, and transactions. As you progress, you will dive deep into advanced topics like indexing strategies, query optimization, execution plans, normalization, and data modeling — skills that are critical for building high-performance applications.This course also covers real-world PostgreSQL usage including handling large datasets, implementing security, managing users and roles, backups and restoration strategies, and connecting PostgreSQL with applications. You will gain hands-on experience with real datasets and practical exercises so you don’t just learn PostgreSQL — you actually use it like a professional.By the end of the course, you will be confident in designing efficient databases, writing complex SQL queries, tuning slow queries, and maintaining PostgreSQL systems in production environments. Whether you want to become a backend developer, data engineer, analyst, or database administrator, this course prepares you with job-ready PostgreSQL skills.

Have you ever wanted to build a real, production-ready AI SaaS application from scratch, one that uses ChatGPT to generate intelligent book summaries, converts them into audio, and handles user subscriptions with a complete admin panel?That's exactly what you'll build in this course.Welcome to the most comprehensive, hands-on course on building an AI-Powered Book Summary SaaS Platform using Next.js 16, TypeScript, Prisma, OpenAI API, and Tailwind CSS. This isn't a basic to-do app or a simple CRUD tutorial. You're going to build a full-stack, feature-rich SaaS product the kind of application that companies charge thousands of dollars to develop.By the end of this course, you'll have a fully functional platform where users can browse books, read AI-generated summaries, listen to audio versions, save favorites, leave reviews, and subscribe to premium plans all powered by ChatGPT and RAG (Retrieval-Augmented Generation) technology.Here's what you'll build step by step:You'll start by setting up your development environment and initializing a Next.js 16 project with TypeScript and Tailwind CSS. From there, you'll design your database schema using Prisma ORM and build a beautiful, responsive homepage.Next, you'll implement a complete authentication system with NextAuth.js including user registration, login, logout, and protected route middleware. You'll also build a separate admin authentication flow with a dedicated admin login page.Then comes the powerful admin dashboard where administrators can manage categories, add and edit books, moderate user reviews, manage users, and handle subscription approvals and rejections. This is real-world admin panel development that goes far beyond tutorials.The AI integratio