Development100% OFF

AI Browser Agents with Python & Playwright

Udemy Instructor

0(782 students)

Self-paced

All Levels

About this course

AI browser agents are one of the most practical use cases of agentic AI. Instead of only chatting with an AI model, you will learn how to build agents that can open a browser, read web pages, click buttons, type into forms, extract data, and complete multi-step workflows. In this course, we will build everything from scratch using Python, Playwright, LLMs, Streamlit, Docker, and AWS.

You will begin with the fundamentals of browser automation, including how web pages are structured, how DOM selectors work, how to interact with buttons and forms, and how to extract useful information from websites. Then we will add LLM intelligence so the agent can understand user instructions, plan browser actions, make decisions, and continue working through an automation flow. You will build practical projects including an AI shopping research agent, a fully autonomous browser agent loop, and a human-in-the-loop approval workflow.

You will also learn how to upload files, process records, create approval requests, track statuses, handle errors, and build a simple Streamlit interface for managing the agent system. In the deployment section, we will move the project to the cloud using AWS services such as S3, SQS, Lambda, DynamoDB, Docker, and Lightsail Containers. We will also cover important safety and ethics topics such as CAPTCHA handling, prompt injection, terms of service, rate limits, and responsible browser automation.

No prior experience with Playwright, browser agents, Streamlit, Docker, or AWS is required. We will build the project step by step from the ground up. By the end, you will have a complete project you can show in your portfolio, extend for your own workflows, and use as a foundation for building more advanced AI automation systems.

Skills you'll gain

Software EngineeringEnglish

Available Coupons

Course Information

Level: All Levels

Suitable for learners at this level

Duration: Self-paced

Total course content

Instructor: Udemy Instructor

Expert course creator

This course includes:

📹Video lectures
📄Downloadable resources
📱Mobile & desktop access
🎓Certificate of completion
♾️Lifetime access

$0$99.99

Save $99.99 today!

Enroll Now - Free

Redirects to Udemy • Limited free enrollments

Share this course

https://freecourse.io/courses/ai-browser-agents-with-python-playwright

This course contains the use of artificial intelligence.Step into the future of technology with 100 Days of Quantum Computing Coding, a practical, project-based course designed to take you from complete beginner to confident quantum computing developer. Through 100 days of structured lessons, coding exercises, quantum circuits, algorithms, simulations, and real-world projects, you will develop the skills needed to understand and build quantum applications.This course makes quantum computing for beginners approachable by combining essential theory with hands-on coding. You will begin by setting up your quantum development environment, refreshing the Python skills needed for quantum programming, and writing your first quantum program. You will then explore foundational concepts such as qubits, quantum states, vectors, basis states, superposition, measurement, probability amplitudes, and circuit visualization.As you progress, you will learn how important quantum gates such as the X, Z, H, S, T, rotation, and controlled gates transform quantum states. You will build and analyze single-qubit and multi-qubit circuits while gaining practical experience with entanglement, Bell states, tensor products, CNOT gates, quantum correlations, and measurement outcomes.The course also introduces the design and organization of complete quantum circuits. You will learn how to create reusable circuit blocks, parameterized circuits, modular workflows, and efficient quantum logic patterns. You will practice debugging circuits, comparing outputs, analyzing circuit depth, and improving the structure of your quantum programs.A major part of the course focuses on quantum algorithms. You will implement and explore the Deutsch algorithm, Deutsch-Jozsa algorithm, Grover’s search algorithm, oracle design, quantum phase estimation, and other important computational techniques. You will compare quantum approaches with classical methods and build an intuitive understanding of when quantum algorithms may provide an advantage.You will also explore advanced topics including quantum teleportation, superdense coding, variational quantum circuits, parameter optimization, quantum machine learning, circuit ansatz design, and hybrid quantum-classical workflows. These lessons will show you how quantum processors and classical computers can work together to solve complex problems.Because real quantum computers are affected by noise, you will study quantum error handling, decoherence, relaxation, readout errors, noise models, error mitigation, and noise-aware circuit design. You will compare simulator results with real quantum hardware and learn how to evaluate circuit reliability using shot counts, histograms, and experimental data.Later in the course, you will access real quantum hardware, select suitable backends, manage execution queues, understand hardware limitations, and run quantum circuits on real devices. You will also explore practical applications in quantum cryptography, optimization, quantum chemistry, random number generation, and emerging quantum technologies.Every ten days, you will complete a practical mini project, including a quantum coin flip, gate playground, quantum random number generator, Bell state simulator, quantum logic lab, Grover search challenge, hybrid quantum model, noisy circuit study, and real-device experiment.The final ten days guide you through building a complete quantum computing capstone project. You will choose a use case, design the circuit workflow, build and test the solution, create visualizations, document your findings, and package the project for your professional portfolio.By the end of this course, you will have completed 100 days of quantum coding, built multiple hands-on projects, worked with simulators and real quantum devices, and created a portfolio demonstrating practical skills in Python quantum programming, quantum circuits, algorithms, hardware, and real-world quantum application development.

AI Agents, RAG & MCP: 7-Day Builder Bootcamp

Udemy Instructor

Artificial Intelligence is rapidly evolving beyond simple chatbots and prompt engineering. Modern organizations are building intelligent systems that can reason, plan, retrieve knowledge, use tools, automate workflows, browse websites, collaborate with other agents, and operate as autonomous digital workers. The demand for engineers who understand how to build these advanced systems has never been higher.AI Agents, RAG & MCP: 7-Day Builder Bootcamp is an intensive, hands-on course designed for developers, AI engineers, architects, and technical professionals who already have experience with Python and basic AI development and want to master the next generation of AI systems.Unlike courses that focus only on prompting or individual AI tools, this bootcamp teaches how to engineer complete AI applications from the ground up. Throughout seven action-packed days, you will build real-world projects using modern frameworks, architectures, and design patterns used by leading AI teams today.You will begin by learning how to create Autonomous AI Agents capable of planning tasks, executing tools, storing memory, reflecting on results, and generating structured outputs. Next, you'll dive into Advanced Retrieval-Augmented Generation (RAG), learning how to build enterprise-grade knowledge systems using Hybrid Retrieval, Knowledge Graphs, Agentic RAG, and source-grounded responses.The course then explores the rapidly growing ecosystem around the Model Context Protocol (MCP). You will build reusable MCP servers, connect AI systems to databases and APIs, and learn how modern agents interact with external tools and resources.You'll also learn how to build Browser Agents that navigate websites, extract information, automate workflows, and operate as AI-powered digital workers. From there, you'll move into Multi-Agent Systems, where specialized agents collaborate through orchestration frameworks such as LangGraph to solve complex business problems.In the second half of the bootcamp, you'll explore Multimodal AI, combining Text, Images, Documents, and Voice into intelligent applications capable of understanding and reasoning across multiple data types.Finally, you'll learn how professional AI teams evaluate, monitor, govern, and deploy AI systems using AI Evaluation Frameworks, Observability, Guardrails, FastAPI, and production engineering practices.By the end of this course, you will have built seven portfolio-ready projects:Autonomous Research AgentEnterprise Knowledge AgentProduction MCP ServerAutonomous Browser AgentMulti-Agent Business Intelligence SystemMultimodal Operations CopilotProduction AI PlatformWhether your goal is to become an AI Engineer, Agent Engineer, Generative AI Developer, Solutions Architect, or technical leader, this course will provide practical experience building the kinds of systems organizations are actively deploying today.If you're ready to move beyond prompts and start building real AI Agents, RAG Systems, MCP Integrations, Multi-Agent Workflows, and Production AI Applications, this bootcamp is for you.

12-Week AI Certification Program

Udemy Instructor

This course contains the use of artificial intelligence.12-Week AI Certification Program is a complete, hands-on learning journey designed to help you build practical skills across Artificial Intelligence, Python, Data Science, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Large Language Models, AI Agents, Deployment, and Responsible AI.This program starts with the foundations of AI and computing, helping you understand how intelligent systems work, how software has evolved from rule-based logic to learning-based systems, and how data, algorithms, and models power modern AI applications. You will set up your AI development environment and build your first intelligent system through a beginner-friendly rule-based AI lab.As the course progresses, you will learn Python for AI development, including data structures, functions, modules, NumPy, and Pandas. These skills will prepare you to work confidently with real-world data. You will then explore data fundamentals, including data types, data sources, cleaning, preprocessing, exploratory data analysis, visualization, and pipeline development. Through hands-on labs, you will build practical data processing scripts and an end-to-end data pipeline.The middle section of the program focuses on Machine Learning and Advanced Machine Learning. You will learn supervised learning, regression, classification, model evaluation, feature engineering, clustering, dimensionality reduction, hyperparameter tuning, and production-style ML workflows. These lessons will help you understand how to build, train, evaluate, and improve real ML models.You will also explore Deep Learning, where you will learn neural networks, activation functions, backpropagation, model training, and framework-based development. From there, the course moves into Natural Language Processing, covering text processing, tokenization, embeddings, transformers, text classification, and chatbot-style applications. You will then study Computer Vision, including image processing, convolutional neural networks, object detection, transfer learning, and image classification apps.In the advanced weeks, you will work with Large Language Models and Prompt Engineering, learning how to design effective prompts, use advanced prompting techniques, and build practical LLM applications. You will then move into AI Agents and Automation, where you will learn tool usage, function calling, memory systems, vector databases, multi-agent design, and autonomous workflows.The final part of the program prepares you for real-world implementation through AI deployment, FastAPI, cloud deployment concepts, monitoring, logging, optimization, and production readiness. You will also learn AI governance, ethics, bias, security, privacy, and risk management, giving you the knowledge needed to build AI responsibly.By the end of this 12-week AI certification, you will have completed 12 hands-on labs and a portfolio-ready capstone project. This course is ideal for beginners, professionals, developers, analysts, managers, and anyone who wants to gain practical, job-ready skills in Artificial Intelligence and build real AI systems from start to finish.

0.0•994•Self-paced

FREE$94.99

Enroll

AI Browser Agents with Python & Playwright

About this course

Skills you'll gain

Available Coupons