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"Welcome to Learn Python Like a Pro: Beginner to Advanced Course 2025! Whether you're a newcomer or already have some Python experience, this course is your gateway to mastering Python at an advanced level. Dive into a structured learning journey designed to strengthen your foundational skills and introduce you to more intricate Python concepts. Join us as we guide you towards Python proficiency and empower you to excel in programming!"What You'll Cover:Foundational Concepts: Gain a deeper understanding of Python's foundational elements, including input processing, type conversion, and string manipulation techniques.Arithmetic Operations: Explore in-depth arithmetic operations, operator precedence, and built-in mathematical functions to solve complex problems.Conditional Statements and Loops: Learn the fundamentals of decision-making using conditional statements, logical and comparison operators, and iteration with loops.Practical Applications: Apply your knowledge to real-world scenarios through projects like a Weight Converter, Guessing Game, and Car Game, reinforcing your learning with practical programming exercises.Data Structures: Explore essential data structures such as lists, tuples, sets, dictionaries, and 2D lists, uncovering their utility in Python programming. Course Evolution:This course is akin to a living creature, constantly evolving and improving. Our commitment doesn't stop here! I've planned a roadmap to incorporate additional topics, including Object-Oriented Programming (OOP), Functions, Working with Files in Python, List Comprehension, Dictionary Comprehension, and much more.Future-Proof Learning:Rest assured, your investment will not go in vain. As this course continues to grow, you'll gain access to new modules and materials without any additional cost. Our goal is to ensure you're equipped

Do You Want To Know How Machine Learning Algorithms Are Being Implemented In Python?In this course, you'll learn about machine learning and how to utilize python for building reliable and efficient machine learning models to find solutions for real-life problems. We will be covering aspects like preparing data sets to train the machine learning models and setting up a python environment on your desktops and laptops. Also, you'll learn how to utilize these libraries to evaluate and fine-tune your machine learning models.This beginner program will help anyone who wants to quickly start working on machine learning solutions. This program will teach the concepts using real-world problems. Let's Have A Look At The Major Topics We'll Be Covering In This Course!Introduction to Machine Learning with PythonData PreparationEvaluation and tuning of Classification ModelsSupervised Learning - Regression and Classification In this course, we'll take you through the topics of supervised learning and unsupervised learning. Also, you'll learn about the different algorithms like regression, naive Bayes, decision trees, logistic regression, random forest, KNN, and Support Vector Machines (SVM).You'll be learning how to implement the following steps to successfully build machine learning models using PythonInstalling the Python and librariesLoading the datasetSummarizing the datasetVisualizing the datasetEvaluating some algorithmsMaking some predictionsEnroll today and learn the most in-demand skills of Python and machine learningSee You In The Class!

SQL Server is a relational database management system -RDBMS developed and owned by Microsoft.Thousands of companies all over the world use SQL Server for their data solution . SQL -Structured Query Language is an internationally recognised language used to communicate and manipulate various database systems.T-SQL - Transact SQL is Microsoft's implementation of SQL. There are a lot of similarities between them but also proprietary parts that are specific to SQL Server. SQL can be used for Data Analysis to transform data already present in the database to valuable useful information that help companies and organisations make key business and management decisions. This course is a beginners guide to performing data analysis using SQL to interrogate SQL Server to provide answers to data related questions. You will learn to write useful SQL queries that is applicable to the Real World production environment. Everywhere data is being collected, every transaction, every web page visit,every payment—all these and much, much more are filling relational databases with raw data that can be analysed to provide useful information. There is a demand for people who can use data to perform reporting and analysis thus helping businesses and organizations make important and critical decisions. Skills You will learn include: • How to design and write simple SQL queries for data analysis. • How to merge data from multiple tables• How to use aggregate functions • How to use wild cards with SQL queries• How to group related data• How to Filter Data search with SQL WHERE clause• How to Use Alias • How to retrieve all the data from a table In this course we will use SQL to provide answers to questions like:How many customers or employees doe a company has?How many sales reps does a company have?When was the first order placed? This course is packed with real world examples that will help you build your SQL

Welcome to this course!Here, you will go through a "journey" of the Top 50 Dynamic Programming Java Algorithm questions that are asked in coding interviews as well as competitive programming. So let's start by answering the most fundamental questions:What is Dynamic Programming Algorithm?Dynamic programming is a powerful optimization technique for plain recursion problems. If you can break down a problem into simpler sub-problems (optimal substructure) and these sub-problems are repetitive in nature, then you can convert this problem into a Dynamic Programming Solution.In this course, we will start with a basic introduction to Dynamic Programming. We will understand what Dynamic Programming is and how to find out whether a recursive problem can be solved using Dynamic Programming.Can Dynamic Programming solve all problems?Dynamic Programming cannot solve all problems. The dynamic programming algorithm is meant to solve only those problems that have optimal substructure and overlapping subproblem properties.Why is Dynamic Programming faster?Dynamic Programming is faster because we break down a problem into various smaller subproblems. Then, we store the solutions of these subproblems in a table or cache whenever we encounter them first. Hence, if we get the same subproblem later on, instead of recomputing it, we fetch it from the storage and return it. This saves us a lot of time.Moreover, since a Dynamic Programming algorithm required optimal substructure property. It means that the best solution to the initial subproblem can be constructed from the optimal solutions of its subproblems. Hence, we can easily eliminate the need to consider all the possible subproblem solutions. This reduces the time complexity of the algorithm.What will be our approach when you take this course?

Python is one of the most popular and beginner-friendly programming languages in the world. From web development and data analysis to artificial intelligence and automation, Python is everywhere — and learning it opens the door to endless career opportunities.This course is designed as a complete Python learning path for absolute beginners. You don’t need any prior programming experience — we start from scratch and build up step by step until you’re confident in writing Python code on your own.Already know Java? Then mastering Python will be a breeze.In just one week, you can confidently learn Python programming and key libraries—perfect for boosting your resume and unlocking new career opportunities.What is Python?Python is an interpreted, object-oriented, high-level programming language known for its readability and simplicity.It allows you to write code quickly and efficiently, making it ideal for beginners and experienced programmers.Python supports multiple programming paradigms, including procedural, object-oriented, and functional programming.Python was created by Guido van Rossum and first released in 1991.Programmers can easily read and understand a Python program because it has basic, English-like syntax.Python makes programmers more productive because they can write a Python program using fewer lines of code compared to many other languages.What You’ll Learn in This CourseInstall Python and set up your development environment.Understand Python syntax, indentation, variables, and commentsWork with operators, data types, and type casting.Write dynamic programs using control statements and loopsMaster Python strings and their built-in methodsAccept and process user input with interactive programsCreate

Are you a QA engineer, automation tester, or manual tester ready to future-proof your career? This is a practical, tool-first guide to AI testing, built specifically for the software testing profession.Whether you're exploring AI-powered testing for the first time or looking to level up with tools like GitHub Copilot and Claude Code, this course gets you productive with GenAI for QA — working with the same tools you'll use on Monday morning.This is a build-along course. Every section has you working in your own editor — there are no slide decks to sit through. You get 30 downloadable resources: prompt libraries, MCP server configs, CLAUDE md templates and working Playwright projects you can drop straight into your own repo. Three Role Play exercises let you practice prompting against realistic testing scenarios rather than toy examples.What you will learnUse GitHub Copilot for test automation — generate test cases, review code, and build a full Playwright project with AI assistanceUse Claude Code for QA automation — create test plans, write AI-powered tests, and configure your workflow with CLAUDE mdMaster Playwright MCP — the most powerful combination of Agentic AI and test automation available todayLearn Prompt Engineering for QA — principles, patterns, and mistakes that define expert promptingConnect AI agents to real tools with MCP servers: Chrome DevTools, AWS documentation, and databasesRun local LLMs privately with Ollama inside GitHub Copilot and Claude CodeWho this is forQA engineers and automation testers who want to work smarter with AIManual testers moving into AI-assisted or automated testingTest leads evaluating GenAI tools for their teams<