AI Security & Governance (2026)

Dive into the most popular methods of Feature Engineering! Create additional features for a model that determines whether or not somebody will sign up for our product. We’ll look at four popular types of feature engineering - constructing features using data living in our SQL database, manipulating our data in pandas dataframes, using third party data vendors and ingesting data from public APIs. We'll work through the code for each of these techniques and build out the corresponding features. Lastly, we'll check out our new features' correlations to our target variable - what we are trying to predict.These techniques can be applied to a variety of models and feature stores. They will bolster model performance, as more informative data increases model performance. You'll also enhance your company's data assets. You will be able to apply the concepts learned here to many models throughout your organization!This course is best for those with beginner to senior level Python and Data Science understanding. For more beginner levels, feel free to dive in and ask questions along the way. For more advanced levels, this can be a good refresher on Feature Engineering, especially if you haven't worked with the techniques described. Hopefully you all enjoy this course and have fun with this project!

With 23 years of real time software development experience(at PayPal, CSC, Aricent, Philips, Sasken, etc...), Author has designed in such a way that Learners get very good insight working experience in managing and deploying applications to AWS Cloud. AWS Cloud is one of the Cutting edge Technology and is needed by Techies of any Stream, irrespective of Technology.This AWS Practice Test Interview Questions covers Practice questions on below AWS FeaturesEC2(Elastic Cloud Computing)S3(Simple Storage Service)RDS, DynamoDBMessaging Services such as SQS(Simple Queuing Service), SNS(Simple Notification Service), Amazon MQElastic BeanstalkAWS Step FunctionAWS CognitoCloudWatchAWS Java, .NET, Python SDKsEnroll once, and you can take Test any number of times, and you will get Future updates FREE of Cost.This Practice Test(with about 225 questions) helps you to check where you are and also enhances your knowledge on AWS Cloud Features, and whether your current skills are matching Industry standards.These also helps you in interview preparation and boosts your confidence and Career.These questions makes you to analyze the concepts, which will help you to get more insight on the AWS Cloud Concepts.As a Learner, you will keep getting future updates to this Practice Test, at no additional cost.Hence enroll for this course, however you will have Money back guarantee for 30 days.For any clarifications, during the course, we will be glad to assist you in understanding the gaps, if any.

Businesses are now relying on geolocation data more than ever in history. with Geolocation data and business logic getting complex every day, it is important to understand how to analyze such data to make predictions or to find faults. Sometimes we might also need to automate some tasks so that human interactions and efforts can be reduced, for which python is a wise choice. Python is trending as one of the top programming languages from a job perspective with an average salary of more than $100k. Python is one of the base skills for many career paths including data science, Machine learning, and AI expert, etc. python has a large number of community followers and developers, thus there are pretty good chances that for every doubt you have, there might be an answer available. Geospatial analysis is one of the important steps in a GIS career as this allows us to read and manipulate large chunks of data easily. This includes data creation, reading, updating, visualizing, and saving the data either back to the file or to the database. Databases are an integral part of development, most of the time instead of having a single data file, we'll have a connection to databases, which will allow us to fetch the latest data and to analyze it.This course will covers Python programming GIS ConceptsGeospatial analysis Concepts Vector data analysisRaster data analysisSpatial Database analysis

Whether you're a tech enthusiast or a total beginner, fear not! No prior knowledge or coding experience is required. We'll start from scratch and progress at your pace, ensuring everyone gains a comprehensive understanding.What You'll Learn:Game Hacking Essentials: Discover the techniques used by expert game hackers and dive into the minds of game developers to unlock secret mechanics and hidden treasures.Hands-On Learning: Throughout the course, we'll provide exercises at every step, allowing you to apply your knowledge immediately and reinforce your understanding.No Coding Required: Worried about coding? No need! Everything will be explained in a user-friendly manner, ensuring that you grasp the concepts without any programming background.Advanced Computer Knowledge: By the end of this course, you'll have gained advanced knowledge of computer hardware and software empowering you for future endeavors.Confident Hacking Ventures: Our ultimate goal is to arm you with enough knowledge and confidence to venture into the hacking world independently.Join Now and Unveil the World of Game Hacking!Are you ready to unlock your full hacking potential? Enroll now, and let's embark on this thrilling adventure together. By the end, you'll not only be a skilled game hacker but also possess the confidence to explore the hacking world with proficiency.Get set to embrace the challenges!No previous experience needed. Are you ready to level up? Enroll now! MUSIC CREDITS:Song: 'The Dead' by John TasoulasMusic promoted by BreakingCopyright

Spring Boot and Microservices are the latest buzz words in the IT industry. Anyone having these skills are like hot selling cakes in the Market.Spring Cloud provides us the ability to quickly build Microservices with Spring Boot.In this course, we will build simple Java Microservices using Spring Boot and Spring Cloud.We will use the below technology stack.Spring Cloud Netflix Eureka ServerSpring Cloud Netflix Eureka ClientSpring Cloud Netflix ZuulSpring Cloud OpenFeignSpring Boot Data JPASpring Boot WebH2 Embedded Database Lombok FrameworkCourse ObjectivesMonoliths vs MicroservicesUnderstand Microservices Application ComponentsBuild Eureka Server Build Student Application - Microservices 1Build Teacher Application - Microservices 2Build Gateway Application - School GatewayWe will create the Microservice Ecosystem by building the following components:Eureka Server - This will be the Service Discovery Registry where the Microservices needs to register. We will use Student Microservice - This will be the first Microservice for our School Application.Teacher Microservice - This will be the second Microservice for our School Application.School Gateway - This will use Netflix Zuul to enable Routing Logic for the School Application.This will be the entry point to Microservice ecosystem and it will route the request to the relevant Microservice based on the configured routing paths.We will hit the different endpoints using curl for testing the Microservices.

This in-depth course is tailored for individuals aiming to become Machine Learning and AI Engineers. It encompasses the full ML pipeline, from basic principles to sophisticated deployment techniques. Participants will engage in hands-on projects and study real-world scenarios to acquire practical skills in creating, refining, and implementing AI technologies.The Udemy course for Machine Learning and AI Engineering is structured around the roles and responsibilities within the field. It provides a thorough exploration of all essential aspects, such as ML algorithms, the ML pipeline, deep learning frameworks, model training, deployment, and best practices for operations.Organized into 11 comprehensive sections, the course begins with the basics and gradually tackles more complex subjects. Each section is comprised of several lessons, practical projects, and quizzes to solidify the concepts learned.Here are some key features of the course:Comprehensive coverage: The course covers everything from basic math and Python skills to advanced topics like MLOps and large language models.Hands-on projects: Each major section includes a practical project to apply the learned concepts.Industry relevance: The course includes sections on MLOps, deployment, and current trends in AI, preparing students for real-world scenarios.Practical skills: There's a strong focus on practical skills like hyperparameter optimization, model deployment, and performance monitoring.Ethical considerations: The course includes a discussion on AI ethics, an important topic for AI engineers.Capstone project: The course concludes with a multi-week capstone project, allowing students to demonstrate their skills in a comprehensive manner.