7 Days Selenium Java Automation Workshop

Learn R Programming for Data Science, Data Analysis, Statistics Visualization. R Programming is one of the most popular tools used in Data Science, Data Analysis, and Statistics.This course provides a beginner-friendly and practical introduction to R for Data Science, designed for students, professionals, and data science enthusiasts.If you want to start a career in Data Science using R, or strengthen your foundation in R programming and statistical analysis, this course is for you.You will learn R from scratch, focusing on the concepts that are most commonly used in real-world data science and analytics projects. The course uses simple explanations, hands-on examples, and practical demonstrations to make learning easy and effective.What this course covers:Introduction to R Programming and R environmentData types and data structures in RData manipulation and data management in RFlow control (if-else, loops, functions)Data visualization and basic graphs using RBasic statistics for Data ScienceLinear Regression using RYou only need basic programming knowledge no advanced coding experience is required.By the end of this course, you will have a strong foundation in R for Data Science, enabling you to confidently move on to advanced topics such as machine learning, predictive analytics, and advanced data visualization.

DescriptionThis is a no holds barred, action packed course, titled ASP.NET CORE 3.1 and C# REST API with Real World Projects. The course takes you through the complete process of building a production ready REST API using the latest version ASP.NET CORE. To demonstrate My Confidence About This Course, I have created a CV that contains all the Concepts that I covered, and the Projects I have executed in this course. You can Take This Course and Start Looking for Job Immediately using the CV I have prepared.Your prospective employer wants you to come onboard and start building applications for them straight away. That is what I did in this course. To provide the knowledge that will allow you go straight into the industry and start working immediately. With over 120 Lectures, I did not leave any stone unturned!!Basically, the whole course can be grouped into Two Main Themes:Introduction to Web APIWhere I introduced how Web APIs work and how Asp.Net Core implements Web APIsThe Real World ProjectsWhere I built Two SOLID Real-World REST API Projects. The type of Projects that you will be working on when you get into the industry.

Designing production-ready Machine Learning systems requires far more than building accurate models. Today's ML Engineers are expected to architect scalable pipelines, deploy reliable inference services, optimize infrastructure, monitor production systems, integrate Large Language Models (LLMs), and design enterprise-grade AI platforms capable of serving millions of users.This practice exam course is designed to help you evaluate your ML System Design knowledge through 435 carefully crafted certification-style questions distributed across six full-length practice exams. Instead of teaching concepts through video lectures, these assessments measure your ability to make engineering decisions similar to those encountered in technical interviews and real production environments.The practice exams cover the complete lifecycle of machine learning systems, including data engineering, feature stores, model training, experiment tracking, MLOps, deployment strategies, inference optimization, monitoring, observability, drift detection, recommendation systems, search architectures, vector databases, Retrieval-Augmented Generation (RAG), Large Language Models, AI agents, enterprise infrastructure, security, cost optimization, and production troubleshooting.Each question emphasizes practical engineering scenarios, architectural trade-offs, scalability decisions, system reliability, and production best practices. Detailed explanations accompany every answer, helping you strengthen your understanding while identifying areas for improvement.Whether you're preparing for Machine Learning Engineer interviews, MLOps certifications, AI architect roles, or enterprise system design assessments, these practice exams provide a comprehensive benchmark of your readiness for designing modern production AI systems.

desde la creacion de tu primer email (correo electronico) hasta el despliegue a produccion.el curso te lleva de la mano paso a paso , explicando detalle a detalle , extremadamente miticulosoes el enfoque para que tambien personas sin nada de experiencia con las computadoras salganteniendo la habilidad de crear software rentable, asi como el sistema de renta que fabricaremosdesde cero. iniciando por los conceptos basicos como variables , clases , estructuras de control y constanteshasta funciones , sesiones , bases de datos y consultas sql. asi mismo aplicaremos las mejores practicas de seguridad y desarrollo webimplementaremos un framework interno el cual sera nuestra herramienta de trabajo del dia al dia mas poderosa y en constante desarrollo con la cual construiremoscualquier cosa que se nos ocurra que pueda correr en el navegador.Recuerda que si bien no es necesario tener conocimiento previo , creo que antes de entrar a este curso porque es un curso al que se necesita seriedad y constanciamucha diciplina e infinita practica. para obtener ese mindset y no te frustes demasiadotermina los primeros 4 cursos para que obtengas una base solida en fundamentos de programaciony practica bastante con los proyectos base que obtengas en cada curso para que complementes y pulas tus habilidades en programacion y desarrollo asistido por inteligencia artificial (IA)

Agentic AI with Functions and Storage: Core Concepts is a comprehensive online course designed to help learners understand the essential building blocks of modern AI agents. As AI systems become increasingly autonomous, mastering how agents interact with functions, external tools, and persistent storage is crucial for developing intelligent, context-aware applications.This course introduces the core concepts behind Agentic AI, including function calling, tool integration, memory management, structured data handling, and persistent storage techniques. You will learn how AI agents make decisions, execute tasks through external functions, retain information across conversations, and manage long-term memory using databases and vector stores. Through practical examples and hands-on exercises, you will gain the knowledge needed to build reliable, scalable, and production-ready AI applications.The curriculum covers topics such as AI agent architecture, function calling workflows, structured outputs, prompt engineering for tool usage, short-term and long-term memory, vector databases, embeddings, retrieval mechanisms, state management, and storage strategies for autonomous agents. You will also explore best practices for designing efficient AI workflows, improving agent reliability, and integrating storage solutions into real-world applications.By the end of this course, you will have a solid understanding of the core principles that power modern Agentic AI systems. Whether you are a software developer, AI engineer, machine learning practitioner, or technology enthusiast, this course provides the foundational knowledge required to build intelligent AI agents capable of reasoning, remembering, and interacting with external systems effectively.

Unlock the power of Claude AI and learn how to use one of the world's leading AI assistants to improve productivity, creativity, and problem-solving. This beginner-friendly course is designed for students, professionals, content creators, entrepreneurs, and anyone interested in artificial intelligence. No prior AI or programming experience is required.Throughout the course, you will explore the fundamentals of Claude AI, learn how to write effective prompts, generate high-quality content, summarize documents, analyze data, brainstorm ideas, and automate everyday tasks. You'll also discover best practices for interacting with Claude AI to achieve accurate, reliable, and efficient results.Through hands-on examples and guided exercises, you'll gain confidence in using Claude AI for content creation, email drafting, report generation, educational support, programming assistance, and workflow automation. The course also covers prompt engineering fundamentals, helping you write better prompts that produce accurate and useful results consistently. Start your AI journey today and discover how Claude AI can transform the way you work, learn, and create.By the end of this course, you will have the confidence to use Claude AI for personal, academic, and professional projects. Whether you're creating content, conducting research, improving productivity, or learning new skills, this course provides practical, hands-on lessons that help you make the most of Claude AI in real-world scenarios.