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Advanced SQL & Database Design: Practice Exams

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Data is the lifeblood of the modern enterprise, and Structured Query Language (SQL) is the universal language used to harness it. However, there is a massive difference between writing a basic query to pull a few rows of data and architecting a complex analytical pipeline that processes millions of records without crashing the server. Welcome to the Advanced SQL & Database Design practice assessments!

Top-tier tech companies are desperately searching for engineers and analysts who understand how database engines actually work under the hood. They need professionals who know how to optimize indexing strategies, traverse hierarchical data using recursive CTEs, and guarantee data integrity through strict normalization rules.This comprehensive practice test course provides you with 200 realistic, highly technical questions modeled directly after the grueling database architecture interviews conducted by leading tech firms. Across these four rigorous practice exams, you will face direct, scenario-based challenges spanning a massive array of global industries.

You will be tested on your ability to manage concurrent transactions in high-frequency fintech trading applications, optimize read-heavy e-commerce inventory databases using B-Tree indexes, and extract complex trend analytics from multi-year healthcare patient records using Window Functions.The questions in this course cut through the beginner-level syntax tutorials and dive straight into advanced relational theory. You will be challenged on the exact mathematical differences between RANK and DENSE_RANK, the operational mechanics of the HAVING clause versus the WHERE clause, and the security benefits of utilizing Stored Procedures against SQL injection attacks. If you are preparing for a rigorous data engineering technical screen, aiming to optimize your company's slow-running legacy reports, or simply wanting to prove you can handle massive relational datasets with precision, this is your ultimate testing ground.

Enroll today and start querying like a senior engineer!Course locale: English (US) Course instructional level: Advanced Level Course category: Development Course subcategory: Database Design & Development

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Master the art of database management and development with this comprehensive course that covers SQL, MySQL, PostgreSQL, and MongoDB. Whether you're a beginner looking to understand the basics or an experienced developer aiming to expand your database expertise, this course provides everything you need to manage, optimize, and secure databases across multiple platforms.Starting with SQL, you’ll learn the fundamentals of database querying and data manipulation. You’ll then dive into MySQL and PostgreSQL, exploring advanced features, performance optimization, and complex data structures. Finally, you’ll explore MongoDB, the leading NoSQL database, to understand how to manage unstructured data and create flexible, scalable applications.This all-in-one course is packed with hands-on exercises, real-world projects, and expert guidance, ensuring you gain practical experience and the confidence to work with databases in any environment. By the end, you'll have a strong command of both relational and non-relational databases, making you a versatile and in-demand professional in the field of data management.What You'll Learn:SQL Fundamentals: Master the basics of SQL, including data querying, manipulation, and complex joins.MySQL: Learn to design, implement, and optimize databases using one of the most popular relational database management systems.PostgreSQL: Dive into advanced features like indexing, triggers, and stored procedures, and learn to manage large-scale databases efficiently.MongoDB: Explore NoSQL concepts, work with JSON-like documents, and develop scalable, flexible database solutions.Real-World Projects: Apply your skills in practical scenarios, including database design, optimization, and migration across different platforms.Best Practices: Understand industry standards for database security, backup, and recovery.Who This Course is For:Aspiring database administrators and developers looking to gain a strong foundation in both relational and NoSQL databases.Software developers who want to enhance their database management skills across multiple platforms.Data analysts and engineers seeking to understand database architectures and improve data handling efficiency.Anyone interested in mastering a versatile set of tools for database management, from SQL to modern NoSQL technologies.By enrolling in this course, you’ll gain the skills to manage and optimize databases across different platforms, making you a valuable asset in any data-driven environment. Whether you're looking to start a new career or upgrade your existing skills, this course offers everything you need to become a database expert. Start your journey to mastering databases today!

AI Browser Agents with Python & Playwright

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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.

Machine Learning & AI Fundamentals: Practice Exams

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We are living in the golden age of Artificial Intelligence. However, simply knowing how to import a library and call .fit() and .predict() is no longer enough to secure a high-paying job in data science. Companies are looking for engineers who understand the underlying mathematics of their models. They need professionals who know exactly why a neural network is overfitting, how to optimize a learning rate during gradient descent, and when to prioritize Recall over Precision in life-or-death classification models. Welcome to the Machine Learning & AI Fundamentals practice assessments!This comprehensive practice test course provides you with 200 realistic, highly technical questions modeled directly after the grueling data science interviews conducted by FAANG companies and top-tier research institutions. Across these four rigorous practice exams, you will face direct, scenario-based challenges spanning a massive array of industries. You will be tested on your ability to deploy Keras-based house price regression models, build fraud detection pipelines for major banking clients, and architect transformer models for real-time social media sentiment analysis.The questions in this course cut through the theoretical fluff and dive straight into practical application. You will be challenged on the nuances of categorical cross-entropy, the mathematical logic behind Gini Impurity in Decision Trees, and the architectural differences between CNNs and RNNs. If you are preparing to defend an academic submission, pivot your career into machine learning engineering, or prove that you can build models that actually scale in production environments, this is your ultimate testing ground. Enroll today and start optimizing your algorithms!Course locale: English (US) Course instructional level: Advanced Level Course category: Development Course subcategory: Data Science

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Advanced SQL & Database Design: Practice Exams

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