Practical Data Science

Ever wonder how professional sports teams get their edge? How analysts track player performance with pinpoint accuracy, visualizing every movement to uncover winning strategies? The answer is Computer Vision.From the Premier League to the NBA, AI-driven analytics has revolutionized the world of sports. The ability to automatically track players, detect the ball, and analyze game-flow from video footage is one of the most exciting and in-demand skills in the AI industry today.But while many tutorials show you how to detect an object in a single image, they stop there. The real magic happens when you track that object, understand its context on the field of play, and visualize its movement in a way that provides powerful insights. This is the gap between a simple script and a professional-grade sports analytics system.This course is designed to bridge that gap.In this comprehensive, hands-on project, you will build a complete, end-to-end tennis analytics system from scratch. We won't just learn theory; we will implement a full pipeline using a state-of-the-art technology stack, including Python, Ultralytics YOLOv8, DeepSORT, Grounding DINO, and OpenCV. You will learn how to combine multiple advanced AI models to create a single, cohesive application that turns raw video into actionable data.By the end of this course, you will not only have a deep understanding of modern computer vision techniques, but you will also have a stunning, portfolio-worthy project that demonstrates your ability to build real-world AI solutions.What you'll learn:Real-Time Ball Detection: Train and implement the state-of-the-art YOLOv8 model to accurately detect a tennis ball in video footage.Zero-Shot Player Detection: Use the powerful Grounding DINO model to detect players using te

Leadership 4.0: Meeting for High Productivity in the AI EraTurn Every Meeting Into a Power Engine That Drives Results, Influence, and GrowthThe Silent Career Killer Nobody Talks About: Poor Meeting SkillsEvery day, professionals step into meetings hoping to make progress —and instead, walk out with confusion, conflict, and wasted time.Bad meetings silently destroy productivity, relationships, and opportunities.Research shows:→ 65% of managers say meetings keep them from completing real work (Harvard Business Review)→ 71% of professionals admit their meetings are unproductive (Atlassian)→ Poor meeting practices cost companies over 37 billion USD each year in lost productivity (Inc. Magazine)Now imagine what that means for your career or business.Without the Right Meeting Skills→ You struggle to get buy-in from your team or leaders even when your ideas are strong→ Projects stall or fail because meetings end without clear decisions or ownership→ You lose influence with peers, clients, and vendors who find you unfocused or unclear→ Promotions and leadership roles pass you by because you appear inefficient→ Freelancers and entrepreneurs lose clients because of confusing, energy-draining meetingsWhat You’ll Master — and Why It MattersEach skill in this course directly removes a pain point that holds professionals back in today’s fast-moving, AI-driven workplace.1. The Pain: Endless, Unproductive MeetingsThe average professional spends 31 hours per month in meetings that achieve noth

In this course we take a look at the various ways we can use photos and other 2D images to create seamless Substance Designer materials. By creating a linked workflow between Photoshop and Substance we'll take advantage of the tools both these programs have to offer to create procedural hand-painted materials. We start by creating a seamless hand-painted color map from images off the Internet. Once our color map is complete, we use it as a guide for creating all the other maps and masks we'll need for our material. After finishing the basics in Photoshop, we set up a linked workflow with Substance Designer that will allow us to view our progress in the Substance 3D view, and easily adjust our maps in Photoshop. Here we'll further refine our 2D maps by using some of the nodes available in Substance Designer. We'll also add procedural qualities to our material. First we'll add some metal veins that can fade in and out and then an animated lava that can be toggled on and off.

Managing your application state in a Blazor application can be tedious. If you want to do it with native way, you'd need to (ab)use of parameters and callbacks to communicate between components.Redux is a powerful and widely used library in the JavaScript community that helps you organize your front-end data the best way it can be. In this course, we are going to learn FROM SCRATCH how you can implement a Redux store pattern in your Blazor app !In the first module, we'll start from a classic Blazor app that communicates with an API. We'll quickly see what are the main issues with this way of creating Blazor. In this module, we will:Create our first state from a blank C# class fileCreate our first action from a blank C# class fileCreate our first reducer from a blank C# class fileCreate the service that will be used in our Blazor components Modify the list component to use our Redux implementationExercise : try to update the list component for the delete action by using our Redux implementationAt the end of this first module, you'll understand the basics of a Redux implementation and how it can enhance your application performance.The second module will be focused on using an open-source rock-solid library to enhance our implementation. You'll learn:How to install and configure this libraryHow to mutate our state and reducer to be compatible with this libraryExercise : try to update the list component to use the open-source libraryAdding effects, a special kind of reducer, to handle asynchronous needsExercise : try to update the list component to use effect and respect the first SOLID principle (Single Responsibility)Enable ReduxDevTools

Welcome to "Isha Training Solutions"First of all, I would like to thank all Udemy Students for making my first 2 courses highly successful Performance testing Using LoadRunner (Basics + advanced)SAP Performance Testing Using Loadrunner (SAP GUI Scripting)We, at Isha, continue to strive hard to create new courses for Performance Testers. As part of this efforts, we have come up with a new course " WebServices Performance Testing Using Loadrunner 12.50 (SOAP &REST)". At the end of this course, you not only can confidently handle interviews but also handle Performance Testing projects pertaining to SOAP and RESTful Web services .Learn all the basics and advanced concepts with Hands-on examples. All the intricacies and challenges typically faced by performance testers, while scripting, is covered as part of this course. This course focuses on scripting part using VuGen.****************************************************************************************My other courses on UdemyApache Jmeter - Basics to Intermediate levelAdvance LoadRunner Scripting for HTTP/HTML ProtocolLoadrunner 12.50 SAPGUI Protocol scriptingPerformance Testing using LoadRunner 12.50****************************************************************************************I am able to Record, Replay back, Add transactions & Add Check Points, then why should I take this course?This course is much deeper than just record and playback. Students reported that they were able to troubleshoot the issues by themselves after attending the course. Also, reported that the course helped them to break the interviews confidently. Lots of C functions, LR functions, conversions etc...will be discussed.

Machine learning is a branch of artificial intelligence (AI) focused on building applications that learn from data and improve their accuracy over time without being programmed to do so.In data science, an algorithm is a sequence of statistical processing steps. In machine learning, algorithms are 'trained' to find patterns and features in massive amounts of data in order to make decisions and predictions based on new data. The better the algorithm, the more accurate the decisions and predictions will become as it processes more data.Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts.Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning.Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever. Imagine a world with drastically reduced car accidents, simply by removing the element of human error.Topics covered in this course:1. Lecture on Information Gain and GINI impurity [decision trees]2. Numerical problem related to Decision Tree will be solved in tutorial sessions3. Implementing Decision Tree Classifier in workshop session [coding]4. Regression Trees 5. Implement Decision Tree Regressor 6. Simple Linear Regression 7. Tutorial on cost function and numerical implementing Ordinary Least Squares Algorithm8. Multiple Linear Regression9. Polynomial Linear Regression 10. Implement Simple, Multiple, Polynomial Linear Regression [[coding session]]11. Write code of Multivariate Linear Regression from Scratch12. Learn about gradient Descent algorithm13. Lecture on Logi