Product Owner Certification

Product Owner Certification

Unlock your potential in Product Owner Certification in just self-paced. Led by Vipesh Singla , MBA, Certified SAFe Agile Coach. Whether you're looking to change careers or enhance your existing skills, this Product Owner Certification course delivers valuable content. The course includes practical exercises that reinforce your learning experience. No prior experience required - this course guides you from the basics to advanced Product Owner Certification concepts.

★4.9
3822 students
Created by Vipesh Singla , MBA, Certified SAFe Agile Coach
Self-paced
English
0 enrolled
Product Owner Certification (POC)
This is an exam for certification / assessment and Its not a course with theory or videos
Product Owner Validation, Assessment and Certification.
Preparing for exams at other leading Scrum institute like Scrum dot org (unofficial assessment)
Exam readiness for PSPO 1 exam by Scrum dot Org (unofficial)

Student Reviews

Login to write a review and rate this course.

No reviews yet.

❓

Frequently Asked Questions

Click the 'Enroll Now' button. You will be redirected to the course page on Udemy (or another platform). The coupon code is usually automatically applied. If not, look for a code in the description or the 'Apply Coupon' section on the checkout page.

Yes, for most Udemy courses, once you enroll using the 100% off coupon, you get lifetime access and a certificate of completion upon finishing the course, just like a paid student.

Coupons have a limited number of redemptions or expire after a certain time (often 5 days or less). If a coupon is not working, it likely means it has expired or reached its maximum usage limit. We recommend checking our latest posts for fresh coupons.

Yes! Once you successfully enroll in the course while the coupon is active, you will have lifetime access to the course content, including future updates.

The courses are hosted on reputable platforms like Udemy. When you enroll with a 100% off coupon, the price should be $0.00, and you generally do NOT need to enter credit card information for free transactions on Udemy.

💡

You Might Also Like

6 courses
Mastering AI on AWS: Training AWS Certified AI-Practitioner

Mastering AI on AWS: Training AWS Certified AI-Practitioner

💡 Expert Insight: 🚀 **Career Boost:** This course uniquely positions you at the critical intersection of cutting-edge AI, dominant cloud infrastructure (AWS), and industry-recognized certification. It transforms theoretical AI knowledge into deployable, real-world solutions, making you an indispensable asset in a market desperate for skilled practitioners who can build and manage AI on a production-ready platform.This comprehensive course, "Mastering AI on AWS: Training AWS Certified AI Practitioner" is designed to equip you with the knowledge and skills to excel in AI and machine learning using AWS services. Whether you're a cloud professional, developer, or AI enthusiast, this course will guide you through the fundamentals of AI and machine learning while providing hands-on experience with cutting-edge AWS AI services like Amazon SageMaker, Rekognition, Comprehend, Polly, and more.Starting with foundational concepts of AI and machine learning, you’ll progress through practical labs, working with real-world applications such as image and video recognition, natural language processing, and recommendation systems. The course will also cover security best practices, responsible AI, and preparing for the AWS Certified AI Practitioner exam. By the end, you’ll be ready to build, deploy, and monitor AI applications on AWS and confidently pass the certification exam.Through engaging lessons, hands-on projects, and practical exercises, this course ensures you develop both theoretical knowledge and practical skills to succeed in the growing field of AI and machine learning.What you'll learn:Fundamental concepts of AI, machine learning, and AWS AI services.How to build and deploy AI applications using Amazon SageMaker, Rekognition, Comprehend, Polly, and more.Best practices for securing AI and machine learning workflows on AWS.How to prepare for and pass the AWS Certified AI Practitioner exam.  Who this course is for:Cloud professionals wanting to expand into AI/ML.AI/ML enthusiasts looking to gain practical skills using AWS services.Aspiring data scientists and developers seeking to implement real-world AI solutions.Students and professionals preparing for the AWS Certified AI Practitioner exam.Who this course is for:Cloud Professionals Seeking to Expand into AI/ML: Cloud engineers, architects, and developers who are familiar with AWS and want to build a foundation in AI and machine learning technologies using AWS services.AI and Machine Learning Enthusiasts: Individuals interested in learning the fundamentals of AI and machine learning, and how to apply these technologies in real-world scenarios using AWS.Aspiring Data Scientists and ML Engineers: Beginner data scientists and machine learning engineers looking to gain hands-on experience with AWS AI services, such as Amazon SageMaker, and learn how to build, deploy, and manage AI models on the cloud.Business Analysts and Decision Makers: Professionals who want to understand the capabilities of AI and ML on AWS in order to make informed decisions, manage AI projects, and leverage AI technologies to solve business problems.Students Preparing for AWS AI Certification: Anyone preparing for the AWS Certified AI Practitioner exam who needs structured learning materials, practice labs, and exam preparation resources to ensure success.Tech Professionals Looking to Upskill: IT professionals, developers, and cloud practitioners who want to enhance their career prospects by gaining AI and machine learning skills in a cloud environment.

4.3
School of AI
Mastering Context Design for Intelligent AI Agents

Mastering Context Design for Intelligent AI Agents

Are you ready to build intelligent AI agents that go beyond simple prompts and one-off answers? In today’s fast-evolving AI landscape, it’s not just about Large Language Models (LLMs)—it’s about giving them the right context to think, reason, and act. This course will teach you how to master the art and science of context design so your agents can perform complex tasks, sustain multi-turn conversations, and integrate with real-world tools and memory systems.In Mastering Context Design for Intelligent AI Agents, you’ll learn how to design agents that are context-aware, adaptive, and highly capable. You’ll discover how to work with six foundational context types: instructional context, example-based context, knowledge context, memory context, tool context, and tool result chaining. These aren’t just theory—they’re the building blocks behind real-world agent frameworks like LangChain, CrewAI, LangGraph, and OpenAI’s function calling systems.We’ll show you how to move beyond static prompting into modular, orchestrated systems that automatically manage and update context over time. Whether you’re building a Document Q&A bot, a multi-agent workflow, or a self-reflective planner agent, this course will guide you step by step.You'll learn how to:Use prompt engineering effectively with role, goal, and requirement structuresImplement few-shot prompting using positive and negative examplesLeverage semantic search and vector databases for dynamic retrievalArchitect short-term and long-term memory using modern toolsIntegrate tools through function calling, with clear parameter design and output handlingOptimize token usage with prompt compression and memory pruningCreate self-improving agents through reflection and autonomous context refreshBuild multi-context pipelines using agent orchestration frameworksThis course is perfect for developers, AI engineers, technical product managers, and prompt engineers who want to move beyond beginner prompt patterns and develop real-world, production-grade AI agents.By the end of the course, you’ll be able to:- Design context-rich prompts for advanced use cases- Build modular agent workflows with dynamic context injection- Implement agents using LangChain, CrewAI, or OpenAI Assistants API- Apply token-efficient strategies to keep costs low and performance high- Debug, reflect, and improve agent behavior in autonomous systemsNo prior deep learning experience is required—just a working knowledge of prompts, tools, and a curiosity for how autonomous agents really work under the hood.If you're aiming to lead the way in AI automation, agentic systems, or LLM-powered workflows, this course is your blueprint.Who this course is for:A Prompt Engineer who wants to move beyond templates into modular, agentic designA Software Developer or AI Engineer building multi-step LLM-based applicationsA Technical Product Manager designing features powered by agents or assistantsA Data Scientist experimenting with autonomous decision-making systemsAn AI Enthusiast curious about how tools like LangChain, OpenAI Assistants, and CrewAI really workA Researcher or Educator looking for deeper insight into contextual design principles for agents

4.1
Vivian Aranha
AI-Powered Microservices with Vibe Coding & Software 3.0

AI-Powered Microservices with Vibe Coding & Software 3.0

Welcome to Vibe Coding and Software 3.0, a cutting-edge course that will redefine how you build, scale, and maintain intelligent systems in the age of AI. This isn’t just another programming tutorial—it’s a deep dive into the future of software engineering, where AI-assisted development, specification-driven architecture, and microservices come together to form the foundation of Software 3.0.In a world where AI tools like ChatGPT, Copilot, and Claude are reshaping how developers write code, manage APIs, and design infrastructure, it’s no longer enough to just “know how to code.” Today’s top engineers must understand how to collaborate with AI, generate code from prompts, build autonomous systems, and orchestrate microservice architectures that are scalable, secure, and observable.This course introduces you to the Vibe Coding paradigm—a developer workflow that begins with human intent, uses natural language specifications, and leverages AI to scaffold everything from API contracts to documentation. Whether you’re designing a RESTful service, building a GraphQL backend, or deploying to Kubernetes, Vibe Coding enables you to move faster while maintaining clarity, control, and code quality.You’ll learn how to:Use AI prompts to generate and test APIs using OpenAPI and GraphQL schemasBuild secure, scalable microservices with AI-guided code generationImplement best practices in authentication, including API Keys, OAuth2, and JWTsLeverage AI to auto-document your services with Swagger and context-aware chatbotsApply Specification-Driven Development (SDD) in embedded, edge, and cloud systemsMonitor performance, detect anomalies, and visualize observability data with OpenTelemetryUse distributed tracing, root cause analysis, and explainable dashboards powered by AIBuild your own prompt libraries, knowledge graphs, and developer chatbots for ongoing productivityDeploy production-grade systems across diverse domains like e-commerce, IoT, healthcare, and gamingBy the end of the course, you’ll complete a Capstone Project where you select a real-world use case, define its spec, prompt AI to generate code, build a full-stack system, and present it with documentation and an architecture map. You’ll not only gain technical skills, but also the ability to communicate your systems like a modern software architect.This course is perfect for software engineers, DevOps professionals, tech leads, and product-minded developers who want to stay ahead of the curve. Whether you're transitioning into AI-powered development or leveling up your microservice architecture game, this course will equip you with the mindset, tools, and hands-on skills to thrive in the AI-first software era.Are you ready to code with intent, not syntax? To lead in the age of intelligent systems and developer-AI collaboration?Then welcome to Vibe Coding and Software 3.0—where your specs become software, and your ideas scale with AI.Who this course is for:Product-minded engineers who want to combine speed with scalabilityDevelopers exploring tools like OpenAPI, GraphQL, Kubernetes, and OpenTelemetryProfessionals aiming to build secure, scalable systems powered by AI-generated codeEarly-career developers eager to learn the mindset and tooling behind Software 3.0

4
Vivian Aranha
Certified Generative AI Architect with Knowledge Graphs

Certified Generative AI Architect with Knowledge Graphs

💡 Expert Insight: 🚀 **Career Boost:** In an era where basic GenAI prompts are commoditized, this course positions you as an indispensable architect capable of solving enterprise-level challenges. By mastering the integration of Knowledge Graphs, RAG, and multi-agent systems, you'll unlock the ability to design GenAI solutions that are not just intelligent, but also factual, auditable, and truly scalable for complex business applications.The Certified Generative AI Architect with Knowledge Graphs program is a comprehensive, advanced-level certification designed to equip professionals with the tools, frameworks, and hands-on experience to architect cutting-edge Generative AI (GenAI) systems that are intelligent, explainable, and scalable. This course combines the power of Large Language Models (LLMs), Knowledge Graphs, Retrieval-Augmented Generation (RAG), and agent-based orchestration to help you build production-grade AI solutions that go beyond simple prompt engineering.You’ll begin by mastering the foundations of GenAI architecture, including the capabilities of modern LLMs, the rise of agentic AI systems, and how memory, context, and reasoning enhance performance. You'll explore the anatomy of RAG pipelines, dive into context-aware generation, and set the stage for knowledge-enhanced AI applications.From there, we’ll delve deep into semantic technologies. You’ll learn to design and build ontologies using tools like ProtĂ©gĂ© and TopBraid Composer, construct and query graph databases using RDF, OWL, SPARQL, and Cypher, and manage the lifecycle of enterprise-grade knowledge systems. This enables you to drive semantic search, entity disambiguation, and structured reasoning in real-world deployments.The course also covers how to build hybrid retrieval systems by integrating vector databases like FAISS, Weaviate, and Pinecone with graph-based reasoning. You'll implement advanced RAG pipelines that combine semantic filtering, graph traversal, and vector similarity to improve contextual relevance and reduce hallucinations in LLM outputs.In the advanced sections, you’ll orchestrate multi-agent GenAI systems using frameworks like LangGraph, CrewAI, and AutoGen. These agents will collaborate across planning, retrieval, reasoning, and summarization tasks—enabling intelligent workflows that are modular, traceable, and extensible.You’ll also learn cloud-native deployment strategies across AWS, Azure, and GCP, mastering containerization, Kubernetes, and serverless architectures for scalable GenAI APIs. Monitoring, observability, and secure rollout patterns are all covered, ensuring your solutions are enterprise-ready.To bring it all together, you’ll engage in a capstone project where you define a business problem, create an ontology, build a knowledge graph-enabled RAG pipeline, deploy a multi-agent application to the cloud, and present your solution with full documentation and executive-ready architecture blueprints.This course is ideal for AI architects, ML engineers, semantic web practitioners, and cloud-native developers seeking to lead the next wave of intelligent, knowledge-aware AI systems.Whether you’re building AI for healthcare, legal tech, finance, or retail—this certification will help you deliver impactful, explainable, and future-proof GenAI systems powered by knowledge graphs.Who this course is for:AI/ML Engineers looking to deepen their understanding of LLMs, RAG pipelines, and knowledge-aware AI applications.Solution and Cloud Architects who want to design scalable, secure, and context-aware GenAI systems using modern deployment patterns and cloud-native tooling.Data Engineers and Knowledge Graph Practitioners who are expanding into Generative AI and want to leverage RDF, OWL, SPARQL, and graph models in AI workflows.Technical Product Managers and Tech Leads who need to understand how to structure multi-agent systems, integrate LLMs with enterprise data, and align technical architectures with business goals.Semantic Web or Ontology Engineers aiming to apply their expertise in the fast-evolving world of LLMs, agentic workflows, and context-driven GenAI applications.

3.7
Vivian Aranha
100 AI Agents in 100 Days 2026

100 AI Agents in 100 Days 2026

💡 Expert Insight: 💡 **Expert Insight:** This course transcends traditional learning by demanding the daily development of practical AI agents, forging an invaluable "delivery muscle" crucial for today's rapid-paced tech industry. Students emerge not just with theoretical knowledge, but with a formidable, demonstrable portfolio and the proven ability to rapidly prototype, problem-solve, and consistently ship real-world AI solutions.Disclaimer: This course contains the use of artificial intelligence(AI).100 AI Agents in 100 Days is a deeply practical, project-driven course designed to take you from basic AI concepts to building production-ready autonomous AI systems—one agent at a time. Instead of focusing on abstract theory or one large capstone, this course is built around 100 independent, real-world AI agent projects, each designed to solve a specific problem you’ll actually encounter in work and business.Every single day introduces a new, standalone AI agent. That means there are no dependencies between lessons—you can start anywhere, move at your own pace, and revisit projects whenever you want. Whether you’re interested in productivity, content creation, business operations, marketing, finance, engineering, governance, or advanced autonomous systems, this course gives you hands-on experience across the full spectrum of modern agentic AI.You’ll begin by building practical personal productivity agents such as task prioritizers, email summarizers, habit trackers, and time-blocking planners. From there, you’ll move into writing, research, and analysis agents that generate content, summarize complex information, and extract insights from data. As the course progresses, you’ll build business-focused agents for operations, marketing, HR, legal, finance, and automation—exactly the kinds of systems organizations are actively adopting.What truly sets this course apart is its focus on real-world readiness. You won’t just learn how to prompt a model. You’ll learn how to design agents with clear decision logic, memory, monitoring, error recovery, human-in-the-loop approvals, ethical guardrails, and governance. By the final days, you’ll be building advanced systems such as multi-agent collaboration frameworks, autonomous decision agents, self-improving agents, and a fully production-ready autonomous AI agent that brings everything together.This course is intentionally designed to be beginner-friendly while still going deep. No prior AI or machine learning experience is required. Concepts are introduced clearly, step by step, with an emphasis on building and understanding rather than memorization. At the same time, experienced developers, founders, and technical professionals will find strong architectural patterns, system design principles, and real deployment considerations throughout.By the end of the course, you won’t just have knowledge—you’ll have 100 completed AI agent projects, a strong agentic mindset, and the confidence to design, customize, and deploy AI agents independently. Whether your goal is to advance your career, build AI products, automate workflows, consult for clients, or simply understand where AI is truly headed, this course equips you with skills that are practical, modern, and immediately usable.This is not a course about AI hype. It’s a course about building AI that actually works.Who this course is for:Aspiring AI engineers and developers who want hands-on experience building real AI agents.Software engineers and technical professionals looking to move beyond prompts into agentic AI systems.Founders and startup builders who want to automate workflows and build AI-powered products.Product managers and tech leaders seeking practical understanding of autonomous AI systems.Data, operations, and automation professionals who want to apply AI to real business processes.Career switchers and self-learners looking for a structured, project-based path into AI agents.Consultants and freelancers who want to deliver AI agent solutions to clients.Students and lifelong learners interested in building production-ready AI systems, not just theory.

4.2
Vivian Aranha
Crear una tienda virtual con Boostrap  JavaScript PHP MySQL

Crear una tienda virtual con Boostrap JavaScript PHP MySQL

Una aplicaciĂłn que es muy recurrente en Internet es el desarrollo de una Tienda Virtual. Nos sirve para utilizar lenguajes del lado del cliente, como JavaScript y lenguajes del lado del servidor como PHP, asĂ­ como conectarlo con bases de datos, en este caso como MySQL, herramientas que son las mĂĄs utilizadas en la Web. En este curso construiremos las pĂĄginas web por medio de Bootstrap. lo cual nos permitirĂĄ tener una aplicaciĂłn responsiva. Partiremos desde una pĂĄgina completamente en blanco hasta concluir la parte del usuario (front-end) y la parte del administrador (back-end). Los objetivos del presente curso son:Desarrollar la maqueta responsiva de la tienda virtual con BootstrapConectar la maqueta con una base de datosCrear el registro del usuarios, su firma en el sistema y el cambio de la clave de accesoConstruir el carrito de compras y el ciclo de la ventaCrear la parte administrativa o back-end de la aplicaciĂłn Este curso intermedio, por lo que usted debe tener las bases de programaciĂłn en Bootstrap, PHP, JavaScript y MySQL, aunque no debe de ser experto en ellos. Es una buena oportunidad para poner en prĂĄctica sus conocimientos. Usted debe de contar con una instalaciĂłn de Apache-PHP-MySQL, como XAMPP, MAMP p WAMP.Al final del curso contarĂĄs con todos los archivos del curso y los esquemas de la base de datos.Who this course is for:Desarrolladores web con conocimientos previos de PHP y MySQL

4.3
Francisco Javier Arce Anguiano
đŸ€–

Related AI Tools

📚

Premium Course Collection

Get access to 115+ premium paid courses collection with 8000+ videos and 3500+ files on Telegram

8000+ Videos & 3500+ Files
Web Dev, DSA, AI/ML & More
Top Instructors (Apna College, PW Skills)
Instructor:Vipesh Singla , MBA, Certified SAFe Agile Coach
Duration:Self-paced
Language:English
Code:
Expires:Oct 3, 2026