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Docker Kubernetes MasterClass: DevOps from Scratch - 2024 Last updated 1/2024 Duration: 25h46m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 14.3 GB Genre: eLearning | Language: English Implement Kubernetes Build Test Execute Docker App in Kubernetes Cluster, 100% hands-on in Docker Kubernetes for DevOps What you'll learn How to use Docker, Compose and Kubernetes on your/cloud machine using DevOps practices. Create a multi-node highly-available Kubernetes cluster on Linux. Hand's-on with best Devops practices for making Docker Dockerfiles and Compose files like a Pro! Build, publish your own custom Docker images & Execute on Docker on Kubernetes as DevOps. Install and configure Kubernetes on Premise & Cloud. Kubernetes Package applications with Helm and write your own Helm charts for your applications. Add users, set quotas/limits, do node maintenance, setup monitoring on Kubernetes Cluster. Requirements No paid software required - Just install your favorite text editor and browser! Have a GitHub and Docker Hub account. Knowledge of Git and Linux will be preferred but NOT required. No prior Knowledge of Kubernetes Required. Description Complete Docker Kubernetes Certification Course on Udemy. Course Focus on building efficient computing DevOps infrastructures using Kubernetes and Docker. Help you to be Pro in Docker Kubernetes and Achieving Carrer Changing Goals. Help you to get Docker Kubernetes Certified Engineer and Pay Hike. After taking this course, you'll be able to: Use Docker in your daily developer and/or sysadmin roles Make Dockerfiles and Docker Compose files Build multi-node Docker Swarm clusters and deploying H/A containers Build a workflow of using Docker in dev, then test/CI, then production with YAML Protect your keys, TLS certificates, and passwords with encrypted secrets in Docker Kubernetes Keep your Dockerfiles and images small, efficient, and fast Develop locally while your code runs in a Docker container Protect important persistent data in volumes and bind mounts in Docker Lead your team into the future with the latest Docker container skills! Docker Kubernetes Training: Become Job Ready in Docker Containerization by learning Docker Ecosystem, creating Docker images using Dockerfiles, Installing Ubuntu Linux and CentOS Linux, Granting Docker Control to Non-root Users, Security, Orchestration, Network Configuration Files, etc. You will also get an exposure to industry based real-time projects in various verticals. This course will help you to gain an understanding of how to deploy, use, and maintain your applications on Kubernetes. If you are into DevOps, this is a technology you need to master. Kubernetes has gained a lot of popularity lately and it is a well-sought skill by companies. This course is updated frequently to include the features of the latest releases! Be ready for the Dockerized future , where nearly all software is developed and deployed in containers. Welcome to the most complete and up-to-date course for learning and using Docker end-to-end, from development and testing to deployment and production. Just starting out with Docker? Perfect. This course starts out assuming you're new to containers. This is a living course and will be updated as Docker features and workflows change. Why DevOps skills? Nowadays DevOps engineers are in great demand in the IT industry. Companies are looking for developers who can both develop and deploy the applications. The average salary of a DevOps engineer is about $145,000 per year in the Silicon Valley area which is 20% higher than the salary of a software engineer. Master DevOps Skills means you will be staying ahead in the competitive job market! Some of the many cool things you'll do in this course: Edit web code on your machine while it's served up in a container Lockdown your apps in private networks that only expose necessary ports Create a 3-node Swarm cluster in the cloud Use Virtual IP's for built-in load balancing in your cluster Optimize your Dockerfiles for faster building and tiny deploys Build/Publish your own custom application images Create your own image registry Use Swarm Secrets to encrypt your environment configs, even on disk Deploy container updates in a rolling always-up design Create the config utopia of a single set of YAML files for local dev, CI testing, and prod cluster deploys And so much more. 30-day money-back guarantee! You will get a 30-day money-back guarantee from Udemy for this course. If not satisfied simply ask for a refund within 30 days. Are you ready to take your DevOps skills and career to the next level, take this course now! Who this course is for: Software developers, sysadmins, IT pros, and operators at any skill level. Anyone who makes, deploys, or operates software on servers. Who want to learn DevOps technologies. 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Windows Server 2025: Installation and Configuration Released: 4/3/2025 Duration: 2h 16m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 228 MB Genre: eLearning | Language: English In this detailed course, networking consultant Robert McMillen presents key skills for installing and configuring Windows Server 2025. Dive deep into the technical aspects, starting with the installation and configuration of Windows Server 2025, including both Desktop Experience and Server Core options. Gain hands-on experience in configuring TCP/IP, managing Active Directory, and creating various types of volumes such as simple, spanned, striped, mirrored, and RAID 5. When you complete this course, you will have a thorough understanding of how to install and configure server roles and features, as well as run upgrades from Windows Server 2022. More Info Please check out others courses in your favourite language and bookmark them - - - - AusFile https://ausfile.com/ubnhl1kf5i3o/yxusj.Windows.Server.2025.Installation.and.Configuration.rar RapidGator https://rapidgator.net/file/c2c8b01347b90dddb515bea220285d3a/yxusj.Windows.Server.2025.Installation.and.Configuration.rar

Tech Career Skills: Moving from Developer to Engineering Manager Released: 2/19/2020 Duration: 52m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 410 MB Genre: eLearning | Language: English The skills that made you stand out as an individual contributor won't necessarily help you transition to management. As an engineering manager, you'll be charged with a host of brand-new new responsibilities-from hosting 1:1 meetings to conducting annual reviews-that necessitate the development of brand-new soft skills. This course outlines those skills, as well as the practical steps to take to successfully transition from an individual contributor developer on a team to an engineering manager. Instructor Jessica Rose details the fundamental tasks you'll need to tackle as a manager, as well as how to switch your focus from hands-on coding to coaching. Plus, she shares how to best advocate for your direct reports, as well as continue to grow your technical skills while in a leadership role. More Info AusFile https://ausfile.com/lz5zkencmi1y/yxusj.Tech.Career.Skills.Moving.from.Developer.to.Engineering.Manager.rar RapidGator https://rapidgator.net/file/7cb4a9a2d1000d80d7fd72a290d813d8/yxusj.Tech.Career.Skills.Moving.from.Developer.to.Engineering.Manager.rar

The AI-Driven Software Developer: Optimize, Innovate, Transform Released: 04/2025 Duration: 1h 5m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 122 MB Level: Beginner | Genre: eLearning | Language: English AI is revolutionizing software development-are you ready? In this course, join instructor Ronnie Sheer as he outlines how AI has transformed the world of software development, and shows you how to stay informed about future trends. Find out how generative AI, which got started in coding as autofill and chat conversations, has been rapidly expanding into more advanced and intricate practices integrated with development environments. Along the way, learn how retrieval-augmented generation (RAG) can help focus your code generation, and how to build complete lifecycles of development practice with AI tools. This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time-all while using a tool that you'll likely encounter in the workplace. Check out "Using GitHub Codespaces" with this course to learn how to get started. Homepage https://www.linkedin.com/learning/the-ai-driven-software-developer-optimize-innovate-transform AusFile https://ausfile.com/zebj3nhbyj1p/yxusj.The.AI-Driven.Software.Developer.Optimize.Innovate.Transform.rar RapidGator https://rapidgator.net/file/83c3507e1b16c7cee73bf35b2fe20765/yxusj.The.AI-Driven.Software.Developer.Optimize.Innovate.Transform.rar

Personality vs. Potential: How to Create and Achieve Meaningful Goals Released: 04/2025 Duration: 49m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 133 MB Level: General | Genre: eLearning | Language: English In this course, psychologist Maja Djikic explores the five dimensions of creating and achieving meaningful goals. Maja first explains how to unearth goals that have true meaning to you based on your core wants. She then helps you better understand the way that your willpower operates and ways you can refill or restore your personal willpower. Then, examine the ways that emotions and thought patterns influence what we can achieve, and learn exercises to process your emotions and understand thought patterns that may be inhibiting your goals. Finally, Maja helps you identify obstacles that may get in the way of your goal achievement and shows you how to develop a blueprint for how you want to grow in order to achieve your goals. Homepage https://www.linkedin.com/learning/personality-vs-potential-how-to-create-and-achieve-meaningful-goals AusFile https://ausfile.com/dz1n68eongp6/yxusj.Personality.vs..Potential.How.to.Create.and.Achieve.Meaningful.Goals.rar RapidGator https://rapidgator.net/file/77050bf44631d319d59dbac395ec5e4d/yxusj.Personality.vs..Potential.How.to.Create.and.Achieve.Meaningful.Goals.rar

Migrating COBOL Apps Updated: 04/2025 Duration: 2h 48m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 388 MB Level: Advanced | Genre: eLearning | Language: English Despite the arrival of myriad new and modern languages, COBOL still rules many government and legacy computing systems. Many of these systems are due to be retired, and the organization's applications must be migrated to a modern environment. In this course, learn about the ways in which developers can migrate legacy COBOL applications, the challenges in doing so, and techniques and tips for succeeding in a smooth transition. Discover various techniques and tools you can use to analyze legacy COBOL source code. Explore how to use visualization to better understand legacy code; how to extract code into a subprogram; how to effectively refactor code; and more. Get insight into some automated migration tools that streamline the process. Plus, instructor Malcolm Shore steps through the process of migrating some legacy-style COBOL application demonstrating key tools and processes along the way. Homepage https://www.linkedin.com/learning/migrating-cobol-apps AusFile https://ausfile.com/32hzf6xz6ygf/yxusj.Migrating.COBOL.Apps.rar RapidGator https://rapidgator.net/file/b70859fde485c4770b29dcf4567a95e6/yxusj.Migrating.COBOL.Apps.rar

Logo Design Techniques in Adobe Illustrator - 7 Projects MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hours | 313 MB Genre: eLearning | Language: English Learn seven logo design techniques in Adobe Illustrator, to either learn the software in a practical way or to get ideas for logo shapes and text! Learn from case studies of negative space in Illustrator and then learn techniques to create negative space using Illustrator. Learn how to use custom shapes from Adobe Photoshop to customize and use for logos in Illustrator. Apply freeform drawing techniques to design shapes in Illustrator. Apply best practices for drawing over a photo and how to simplify and stylize the shapes for a logo in Illustrator. Produce custom brushes and then adjust their attributes to use for logo design in Illustrator. Use letters as symbols in logo design. Learn and apply the Shape Builder and Live Paint Bucket tools in logo design. AusFile https://ausfile.com/fqixggq1y4tk/yxusj.Logo.Design.Techniques.rar RapidGator https://rapidgator.net/file/05530a0107cba0b6749739fbf03302c2/yxusj.Logo.Design.Techniques.rar

Introduction to Career Skills in Software Development Updated: 04/2025 Duration: 2h 2m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 650 MB Level: Beginner | Genre: eLearning | Language: English Are you ready to take the first step on your journey as a computer programmer? Maybe you want to land a new job or change careers to a different industry. Whatever your goals, you don't need a tech background to get started with programming today. In this course, instructor Annyce Davis gives you a comprehensive, behind-the-scenes look at what it's really like to be a programmer, from basic concepts and core professional skills, to landing your first role and advancing your career.Discover the power of computing in projects and technical roles, as you prepare for the Microsoft GSI Programming Foundations certificate exam. Learn about a week in the life of a programmer working in software development. Explore tools of the trade and various programming languages with a crash course in Python, the object-oriented programming language that's beginner-friendly and easy to use. Upon completing this course, you'll be ready to rewrite your resume and kick off your job hunt today. Homepage https://www.linkedin.com/learning/introduction-to-career-skills-in-software-development AusFile https://ausfile.com/8aw7zdp3tnzp/yxusj.Introduction.to.Career.Skills.in.Software.Development.rar RapidGator https://rapidgator.net/file/be4e75c91ab96c208f07b2b2703a451f/yxusj.Introduction.to.Career.Skills.in.Software.Development.rar

Python Numpy: Machine Learning & Data Science Course MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | 8 hours 58 minutes | 66 lectures | 1.89 GB Genre: eLearning | Language: English Learn Numpy Python and get comfortable with Python Numpy in order to start into Data Science and Machine Learning. Hello there, Welcome to Python Numpy: Machine Learning & Data Science Course Python numpy, Numpy python, python numpy: machine learning & data science, python numpy, machine learning data science course, machine learning python, data science, python, oak academy, machine learning, python machine learning, python data science, numpy course, data science course Learn Numpy and get comfortable with Python Numpy in order to start into Data Science and Machine Learning OAK Academy offers highly-rated data science courses that will help you learn how to visualize and respond to new data, as well as develop innovative new technologies Whether you're interested in machine learning, data mining, or data analysis, Udemy has a course for you Data science is everywhere Better data science practices are allowing corporations to cut unnecessary costs, automate computing, and analyze markets Essentially, data science is the key to getting ahead in a competitive global climate Python Numpy, Python instructors on OAK Academy specialize in everything from software development to data analysis, and are known for their effective, friendly instruction for students of all levels Whether you work in machine learning or finance, or are pursuing a career in web development or data science, Python is one of the most important skills you can learn Python's simple syntax is especially suited for desktop, web, and business applications Python's design philosophy emphasizes readability and usability Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization The core programming language is quite small and the standard library is also large In fact, Python's large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasks Are you ready for a Data Science career? Do you want to learn the Python Numpy from Scratch? or Are you an experienced Data scientist and looking to improve your skills with Numpy! In both cases, you are at the right place! The number of companies and enterprises using Python is day by day The world we are in is experiencing the age of informatics Python and its Numpy library will be the right choice for you to take part in this world and create your own opportunities, Numpy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays Moreover, Numpy forms the foundation of the Machine Learning stack NumPy aims to provide an array object that is up to 50x faster than traditional Python lists The array object in NumPy is called ndarray , it provides a lot of supporting functions that make working with ndarray very easy Arrays are very frequently used in data science, where speed and resources are very important In this course, we will open the door of the Data Science world and will move deeper You will learn the fundamentals of Python and its beautiful library Numpy step by step with hands-on examples Most importantly in Data Science, you should know how to use effectively the Numpy library Because this library is limitless Throughout the course, we will teach you how to use Python in Linear Algebra, and Neural Network concept , and use powerful machine learning algorithms and we will also do a variety of exercises to reinforce what we have learned in this Machine Learning with NumPy and Python Data Science course In this course you will learn; How to use Anaconda and Jupyter notebook, Fundamentals of Python Datatypes in Python, Lots of datatype operators, methods and how to use them, Conditional concept, if statements The logic of Loops and control statements Functions and how to use them How to use modules and create your own modules Data science and Data literacy concepts Fundamentals of Numpy for Data manipulation such as Numpy arrays and their features Numpy functions Numexpr module How to do indexing and slicing on Arrays Linear Algebra Using numpy in Neural Network Numpy python data science Python Numpy Python data science python numpy: machine learning & data science machine learning python python And we will do some exercises Finally, we will also do a neural network project with Numpy What is data science? We have more data than ever before But data alone cannot tell us much about the world around us We need to interpret the information and discover hidden patterns This is where data science comes in Data science python uses algorithms to understand raw data The main difference between data science and traditional data analysis is its focus on prediction Python data science seeks to find patterns in data and use those patterns to predict future data It draws on machine learning to process large amounts of data, discover patterns, and predict trends Data science using python includes preparing, analyzing, and processing data It draws from many scientific fields, and as a python for data science , it progresses by creating new algorithms to analyze data and validate current methods What does a data scientist do? Data Scientists use machine learning to discover hidden patterns in large amounts of raw data to shed light on real problems This requires several steps First, they must identify a suitable problem Next, they determine what data are needed to solve such a situation and figure out how to get the data Once they obtain the data, they need to clean the data The data may not be formatted correctly, it might have additional unnecessary data, it might be missing entries, or some data might be incorrect Data Scientists must, therefore, make sure the data is clean before they analyze the data To analyze the data, they use machine learning techniques to build models Once they create a model, they test, refine, and finally put it into production What are the most popular coding languagws for data science? Python for data science is the most popular programming language for data science It is a universal language that has a lot of libraries available It is also a good beginner language R is also popular; however, it is more complex and designed for statistical analysis It might be a good choice if you want to specialize in statistical analysis You will want to know either Python or R and SQL SQL is a query language designed for relational databases Data scientists deal with large amounts of data, and they store a lot of that data in relational databases Those are the three most-used programming languages Other languages such as Java, C++, JavaScript, and Scala are also used, albeit less so If you already have a background in those languages, you can explore the tools available in those languages However, if you already know another programming language, you will likely be able to pick up How long does it take to become a data scientist? This answer, of course, varies The more time you devote to learning new skills, the faster you will learn It will also depend on your starting place If you already have a strong base in mathematics and statistics, you will have less to learn If you have no background in statistics or advanced mathematics, you can still become a data scientist; it will just take a bit longer Data science requires lifelong learning, so you will never really finish learning A better question might be, "How can I gauge whether I know enough to become a data scientist?" Challenge yourself to complete data science projects using open data The more you practice, the more you will learn, and the more confident you will become Once you have several projects that you can point to as good examples of your skillset as a data scientist, you are ready to enter the field How can I learn data science on my own? It is possible to learn data science projects on your own, as long as you stay focused and motivated Luckily, there are a lot of online courses and boot camps available Start by determining what interests you about data science If you gravitate to visualizations, begin learning about them Starting with something that excites you will motivate you to take that first step If you are not sure where you want to start, try starting with learning Python It is an excellent introduction to programming languages and will be useful as a data scientist Begin by working through tutorials or Udemy courses on the topic of your choice Once you have developed a base in the skills that interest you, it can help to talk with someone in the field Find out what skills employers are looking for and continue to learn those skills When learning on your own, setting practical learning goals can keep you motivated Does data science require coding? The jury is still out on this one Some people believe that it is possible to become a data scientist without knowing how to code, but others disagree A lot of algorithms have been developed and optimized in the field You could argue that it is more important to understand how to use the algorithms than how to code them yourself As the field grows, more platforms are available that automate much of the process However, as it stands now, employers are primarily looking for people who can code, and you need basic programming skills The data scientist role is continuing to evolve, so that might not be true in the future The best advice would be to find the path that fits your skillset What skills should a data scientist know? A data scientist requires many skills They need a strong understanding of statistical analysis and mathematics, which are essential pillars of data science A good understanding of these concepts will help you understand the basic premises of data science Familiarity with machine learning is also important Machine learning is a valuable tool to find patterns in large data sets To manage large data sets, data scientists must be familiar with databases Structured query language (SQL) is a must-have skill for data scientists However, nonrelational databases (NoSQL) are growing in popularity, so a greater understanding of database structures is beneficial The dominant programming language in Data Science is Python - although R is also popular A basis in at least one of these languages is a good starting point Finally, to communicate findings Is data science a good career? The demand for data scientists is growing We do not just have data scientists; we have data engineers, data administrators, and analytics managers The jobs also generally pay well This might make you wonder if it would be a promising career for you A better understanding of the type of work a data scientist does can help you understand if it might be the path for you First and foremost, you must think analytically Data science from scratch is about gaining a more in-depth understanding of info through data Do you fact-check information and enjoy diving into the statistics? Although the actual work may be quite technical, the findings still need to be communicated Can you explain complex findings to someone who does not have a technical background? Many data scientists work in cross-functional teams and must share their results with people with very different backgrounds What is python? Machine learning python is a general-purpose, object-oriented, high-level programming language Whether you work in artificial intelligence or finance or are pursuing a career in web development or data science, Python bootcamp is one of the most important skills you can learn Python's simple syntax is especially suited for desktop, web, and business applications Python's design philosophy emphasizes readability and usability Python was developed on the premise that there should be only one way (and preferably, one obvious way) to do things, a philosophy that resulted in a strict level of code standardization The core programming language is quite small and the standard library is also large In fact, Python's large library is one of its greatest benefits, providing different tools for programmers suited for a variety of tasks Python vs R: What is the Difference? Python and R are two of today's most popular programming tools When deciding between Python and R in data science , you need to think about your specific needs On one hand, Python is relatively easy for beginners to learn, is applicable across many disciplines, has a strict syntax that will help you become a better coder, and is fast to process large datasets On the other hand, R has over 10,000 packages for data manipulation, is capable of easily making publication-quality graphics, boasts superior capability for statistical modeling, and is more widely used in academia, healthcare, and finance What does it mean that Python is object-oriented? Python is a multi-paradigm language, which means that it supports many data analysis programming approaches Along with procedural and functional programming styles, Python also supports the object-oriented style of programming In object-oriented programming, a developer completes a programming project by creating Python objects in code that represent objects in the actual world These objects can contain both the data and functionality of the real-world object To generate an object in Python you need a class You can think of a class as a template You create the template once, and then use the template to create as many objects as you need Python classes have attributes to represent data and methods that add functionality A class representing a car may have attributes like color, speed, and seats and methods like driving, steering, and stopping What are the limitations of Python? Python is a widely used, general-purpose programming language, but it has some limitations Because Python in machine learning is an interpreted, dynamically typed language, it is slow compared to a compiled, statically typed language like C Therefore, Python is useful when speed is not that important Python's dynamic type system also makes it use more memory than some other programming languages, so it is not suited to memory-intensive applications The Python virtual engine that runs Python code runs single-threaded, making concurrency another limitation of the programming language Though Python is popular for some types of game development, its higher memory and CPU usage limits its usage for high-quality 3D game development That being said, computer hardware is getting better and better, and the speed and memory limitations of Python are getting less and less relevant How is Python used? Python is a general programming language used widely across many industries and platforms One common use of Python is scripting, which means automating tasks in the background Many of the scripts that ship with Linux operating systems are Python scripts Python is also a popular language for machine learning, data analytics, data visualization, and data science because its simple syntax makes it easy to quickly build real applications You can use Python to create desktop applications Many developers use it to write Linux desktop applications, and it is also an excellent choice for web and game development Python web frameworks like Flask and Django are a popular choice for developing web applications Recently, Python is also being used as a language for mobile development via the Kivy third-party library What jobs use Python? Python is a popular language that is used across many industries and in many programming disciplines DevOps engineers use Python to script website and server deployments Web developers use Python to build web applications, usually with one of Python's popular web frameworks like Flask or Django Data scientists and data analysts use Python to build machine learning models, generate data visualizations, and analyze big data Financial advisors and quants (quantitative analysts) use Python to predict the market and manage money Data journalists use Python to sort through information and create stories Machine learning engineers use Python to develop neural networks and artificial intelligent systems How do I learn Python on my own? Python has a simple syntax that makes it an excellent programming language for a beginner to learn To learn Python on your own, you first must become familiar with the syntax But you only need to know a little bit about Python syntax to get started writing real code; you will pick up the rest as you go Depending on the purpose of using it, you can then find a good Python tutorial, book, or course that will teach you the programming language by building a complete application that fits your goals If you want to develop games, then learn Python game development If you're going to build web applications, you can find many courses that can teach you that, too Udemy's online courses are a great place to start if you want to learn Python on your own What is machine learning? Machine learning describes systems that make predictions using a model trained on real-world data For example, let's say we want to build a system that can identify if a cat is in a picture We first assemble many pictures to train our machine learning model During this training phase, we feed pictures into the model, along with information around whether they contain a cat While training, the model learns patterns in the images that are the most closely associated with cats This model can then use the patterns learned during training to predict whether the new images that it's fed contain a cat In this particular example, we might use a neural network to learn these patterns, but machine learning can be much simpler than that Even fitting a line to a set of observed data points, and using that line to make new predictions, counts as a machine learning model What is machine learning used for? Machine learning is being applied to virtually every field today That includes medical diagnoses, facial recognition, weather forecasts, image processing, and more In any situation in which pattern recognition, prediction, and analysis are critical, machine learning can be of use Machine learning is often a disruptive technology when applied to new industries and niches Machine learning engineers can find new ways to apply machine learning technology to optimize and automate existing processes With the right data, you can use machine learning technology to identify extremely complex patterns and yield highly accurate predictions Does machine learning require coding? It's possible to use machine learning without coding, but building new systems generally requires code For example, Amazon's Rekognition service allows you to upload an image via a web browser, which then identifies objects in the image This uses a pre-trained model, with no coding required However, developing machine learning systems involves writing some Python code to train, tune, and deploy your models It's hard to avoid writing code to pre-process the data feeding into your model Most of the work done by a machine learning practitioner involves cleaning the data used to train the machine They also perform "feature engineering" to find what data to use and how to prepare it for use in a machine learning model Tools like AutoML and SageMaker automate the tuning of models Often only a few lines of code can train a model and make predictions from it An introductory understanding of Python will make you more effective in using machine learning systems Why would you want to take this course? We have prepared this course in the simplest way for beginners and have prepared many different exercises to help them understand better No prior knowledge is needed! In this course, you need no previous knowledge about Python or Numpy This course will take you from a beginner to a more experienced level If you are new to data science or have no idea about what data science is, no problem, you will learn anything from scratch you need to start data science If you are a software developer or familiar with other programming languages and you want to start a new world, you are also in the right place You will learn step by step with hands-on examples You'll also get: · Lifetime Access to The Course · Fast & Friendly Support in the Q&A section · Udemy Certificate of Completion Ready for Download Dive in now Python Numpy: Machine Learning & Data Science Course We offer full support , answering any questions See you in the course! 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Data Science Foundations: Fundamentals .MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 5h 17m | 977 MB Instructor: Barton Poulson Data science is driving a world-wide revolution that touches everything from business automation to social interaction. It's also one of the fastest growing, most rewarding careers, employing analysts and engineers around the globe. This course provides an accessible, nontechnical overview of the field, covering the vocabulary, skills, jobs, tools, and techniques of data science. Instructor Barton Poulson defines the relationships to other data-saturated fields such as machine learning and artificial intelligence. He reviews the primary practices: gathering and analyzing data, formulating rules for classification and decision-making, and drawing actionable insights. He also discusses ethics and accountability and provides direction to learn more. By the end, you'll see how data science can help you make better decisions, gain deeper insights, and make your work more effective and efficient. Learning objectives Assess the skills required for a career in data science. Evaluate different sources of data, including metrics and APIs. Explore data through graphs and statistics. Discover how data scientists use programming languages such as R, Python, and SQL. Assess the role of mathematics, such as algebra, in data science. Assess the role of applied statistics, such as confidence intervals, in data science. Assess the role of machine learning, such as artificial neural networks, in data science. Define the components of effective data visualization. More Info AusFile https://ausfile.com/4lgcqutdcd80/yxusj.Data.Science.Foundations.Fundamentals.rar RapidGator https://rapidgator.net/file/da18c9bc3a88faf96eea6c82c551c4fe/yxusj.Data.Science.Foundations.Fundamentals.rar

Video Editing Techniques for Impactful Content Released: 04/2025 Duration: 2h 18m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 551 MB Level: Beginner + Intermediate | Genre: eLearning | Language: English Transform your video editing skills and captivate your audience. This course is perfect for filmmakers, YouTubers, and content creators who want to go beyond basic editing and master the art of video storytelling. Find out how to use essential editing techniques like J-Cuts, L-Cuts, Jump Cuts, and Match Cuts to create smooth transitions and maintain viewer engagement. Learn how to use music, ambient sounds, and sound effects to enhance the emotional impact of your videos. Explore ways you can use Slow Zooms and Fast Zooms to focus attention and build intensity, as well as how Slow-Motion Shots can emphasize dramatic moments and create a visual appeal. Plus, discover how to pace your videos, use contrast editing, and integrate transition clips to keep your narrative flowing. When you complete this course, you will be equipped to start boosting viewer retention, creating emotionally engaging videos, and standing out in a crowded market. This course was created by Skillshare. We are pleased to host this training in our library. Homepage https://www.linkedin.com/learning/video-editing-techniques-for-impactful-content AusFile https://ausfile.com/kmlda6sk2nli/yxusj.Video.Editing.Techniques.for.Impactful.Content.rar RapidGator https://rapidgator.net/file/fd6b112405fd8211f6b76b1d38d7dc09/yxusj.Video.Editing.Techniques.for.Impactful.Content.rar

Windows Server 2025: Installation and Configuration Released: 4/3/2025 Duration: 2h 16m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 228 MB Genre: eLearning | Language: English In this detailed course, networking consultant Robert McMillen presents key skills for installing and configuring Windows Server 2025. Dive deep into the technical aspects, starting with the installation and configuration of Windows Server 2025, including both Desktop Experience and Server Core options. Gain hands-on experience in configuring TCP/IP, managing Active Directory, and creating various types of volumes such as simple, spanned, striped, mirrored, and RAID 5. When you complete this course, you will have a thorough understanding of how to install and configure server roles and features, as well as run upgrades from Windows Server 2022. More Info Please check out others courses in your favourite language and bookmark them - - - - AusFile https://ausfile.com/hjnyms02whbz/yxusj.Windows.Server.2025.Installation.and.Configuration.rar RapidGator https://rapidgator.net/file/e6dcf0cd38de9a44304d7e47fcca5ea8/yxusj.Windows.Server.2025.Installation.and.Configuration.rar

The Manager's Guide to Integrating and Managing AI Agents Released: 04/2025 Duration: 27m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 77.7 MB Level: Intermediate | Genre: eLearning | Language: English As AI reshapes the workplace, people managers must evolve to lead and manage human employees and AI agents simultaneously. In this course, instructor Charlene Li teaches you how to manage AI agents as autonomous entities alongside human employees in preparation for the future of business shaped by agentic AI. Managing AI is new territory-check out this course to find out how you can thrive in uncertainty and lead with confidence in an AI-powered world. Homepage https://www.linkedin.com/learning/the-manager-s-guide-to-integrating-and-managing-ai-agents AusFile https://ausfile.com/c6g5mk5v8ur2/yxusj.The.Managers.Guide.to.Integrating.and.Managing.AI.Agents.rar RapidGator https://rapidgator.net/file/487b2d9890dc225a0cdf71f66c37809d/yxusj.The.Managers.Guide.to.Integrating.and.Managing.AI.Agents.rar

The AI-Driven Software Developer: Optimize, Innovate, Transform Released: 04/2025 Duration: 1h 5m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 122 MB Level: Beginner | Genre: eLearning | Language: English AI is revolutionizing software development-are you ready? In this course, join instructor Ronnie Sheer as he outlines how AI has transformed the world of software development, and shows you how to stay informed about future trends. Find out how generative AI, which got started in coding as autofill and chat conversations, has been rapidly expanding into more advanced and intricate practices integrated with development environments. Along the way, learn how retrieval-augmented generation (RAG) can help focus your code generation, and how to build complete lifecycles of development practice with AI tools. This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time-all while using a tool that you'll likely encounter in the workplace. Check out "Using GitHub Codespaces" with this course to learn how to get started. Homepage https://www.linkedin.com/learning/the-ai-driven-software-developer-optimize-innovate-transform AusFile https://ausfile.com/32usn9uq0l13/yxusj.The.AI-Driven.Software.Developer.Optimize.Innovate.Transform.rar RapidGator https://rapidgator.net/file/a09ccae209f1e733d333c57c2ab66f95/yxusj.The.AI-Driven.Software.Developer.Optimize.Innovate.Transform.rar

Tech Career Skills: Moving from Developer to Engineering Manager Released: 2/19/2020 Duration: 52m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 410 MB Genre: eLearning | Language: English The skills that made you stand out as an individual contributor won't necessarily help you transition to management. As an engineering manager, you'll be charged with a host of brand-new new responsibilities-from hosting 1:1 meetings to conducting annual reviews-that necessitate the development of brand-new soft skills. This course outlines those skills, as well as the practical steps to take to successfully transition from an individual contributor developer on a team to an engineering manager. Instructor Jessica Rose details the fundamental tasks you'll need to tackle as a manager, as well as how to switch your focus from hands-on coding to coaching. Plus, she shares how to best advocate for your direct reports, as well as continue to grow your technical skills while in a leadership role. More Info AusFile https://ausfile.com/4qtcycki96za/yxusj.Tech.Career.Skills.Moving.from.Developer.to.Engineering.Manager.rar RapidGator https://rapidgator.net/file/97108110747d6e9f1e7c67dd1b60345e/yxusj.Tech.Career.Skills.Moving.from.Developer.to.Engineering.Manager.rar

PyTorch Essential Training: Working with Images Released: 04/2025 Duration: 1h 31m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 131 MB Level: Intermediate | Genre: eLearning | Language: English Machine learning developers and data scientists can feel overwhelmed by the complexity of convolutional neural networks (CNNs) and their applications. This course provides a hands-on, project-based approach to image classification. Join instructor Terezija Semenski to gain practical experience in preprocessing data, training, and evaluating a pre-trained model. Plus, explore transfer learning, model fine-tuning, and evaluation metrics. Homepage https://www.linkedin.com/learning/pytorch-essential-training-working-with-images AusFile https://ausfile.com/iy3foketflhl/yxusj.PyTorch.Essential.Training.Working.with.Images.rar RapidGator https://rapidgator.net/file/29976cb73d4b2d2a2a0a2669aa5ed31e/yxusj.PyTorch.Essential.Training.Working.with.Images.rar

Personality vs. Potential: How to Create and Achieve Meaningful Goals Released: 04/2025 Duration: 49m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 133 MB Level: General | Genre: eLearning | Language: English In this course, psychologist Maja Djikic explores the five dimensions of creating and achieving meaningful goals. Maja first explains how to unearth goals that have true meaning to you based on your core wants. She then helps you better understand the way that your willpower operates and ways you can refill or restore your personal willpower. Then, examine the ways that emotions and thought patterns influence what we can achieve, and learn exercises to process your emotions and understand thought patterns that may be inhibiting your goals. Finally, Maja helps you identify obstacles that may get in the way of your goal achievement and shows you how to develop a blueprint for how you want to grow in order to achieve your goals. Homepage https://www.linkedin.com/learning/personality-vs-potential-how-to-create-and-achieve-meaningful-goals AusFile https://ausfile.com/e04kawj3ywh0/yxusj.Personality.vs..Potential.How.to.Create.and.Achieve.Meaningful.Goals.rar RapidGator https://rapidgator.net/file/9d0b62e0fb9cbef5d60b46f1630806cf/yxusj.Personality.vs..Potential.How.to.Create.and.Achieve.Meaningful.Goals.rar

Gaining Skills with LinkedIn Learning Updated: 04/2025 Duration: 13m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 40 MB Level: Beginner | Genre: eLearning | Language: English With LinkedIn Learning, anyone can gain new skills. We offer expert-led, anytime training that you can take at your own pace, with tools and features to fit almost any learning style. Use this course to discover how you learn best and how LinkedIn Learning can help you set and achieve your personal and professional goals. Staff author Oliver Schinkten shows how to use LinkedIn Learning alongside cutting-edge, brain-based research to pinpoint the skills you want to learn, find the training to reach your goals, and make the knowledge stick. Discover which skills are in demand and how to showcase what you've learned on LinkedIn. Homepage https://www.linkedin.com/learning/gaining-skills-with-linkedin-learning-2019 AusFile https://ausfile.com/tdo214wkft5k/yxusj.Gaining.Skills.with.LinkedIn.Learning.rar RapidGator https://rapidgator.net/file/94bf3204f4600bd478964821925194d5/yxusj.Gaining.Skills.with.LinkedIn.Learning.rar

Eclipse Essential Training [Updated Mar 15, 2021] .MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 2h 7m | 314 MB Instructor: Todd Perkins Eclipse is an industry-standard IDE and a critical tool for developers who want to build projects in multiple languages. In this course, Todd Perkins shows how to effectively use the IDE's built-in tools and extensions to create, code, test, and debug projects in Java and Python. He shows how to adapt the Eclipse workflow to the nuances of each language, and integrate with Git for version control. By the end of the course, developers will be able to wield all of the most essential features in Eclipse with confidence. More Info AusFile https://ausfile.com/1m6yf35h72nb/yxusj.Eclipse.Essential.Training.rar RapidGator https://rapidgator.net/file/23e0d6e4d09ee4530ee8a59c5ee4f535/yxusj.Eclipse.Essential.Training.rar

Curating Your Instructional Design Portfolio Released: 4/3/2025 Duration: 1h 23m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 139 MB Genre: eLearning | Language: English If you're an instructional designer, elearning pro, or former teacher transitioning into elearning, having a way to showcase what you've done and can do is essential. Your portfolio showcases your skills, proves your expertise, and highlights your value to potential clients or employers. In this course, elearning expert David Anderson shows you how to curate and prepare the key elements for a professional portfolio. Find out how to select your best work, organize projects, and present them in a way that reflects your skills and experience. Plus, learn how to craft engaging project descriptions, create impactful thumbnails, and ensure your portfolio remains adaptable as your career evolves. More Info Please check out others courses in your favourite language and bookmark them - - - - AusFile https://ausfile.com/sdjd3nwxoxd8/yxusj.Curating.Your.Instructional.Design.Portfolio.rar RapidGator https://rapidgator.net/file/c6c486ade4b76ecbc36f7a99402ef381/yxusj.Curating.Your.Instructional.Design.Portfolio.rar

Creating Binge-Worthy L&D Content Released: 04/2025 Duration: 42m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 145 MB Level: General | Genre: eLearning | Language: English In today's noisy, fast-paced world, capturing attention is harder than ever especially for busy professionals juggling work and life demands. In this workshop, Brittany Neish shows you how to steal from marketing's playbook to design binge-worthy L&D content that stands out. Learn to create engaging, interactive experiences using hooks, pop-culture storytelling, and relevant messaging. By the end, you'll have strategies to build dynamic, two-way content worthy of learners' time and attention. Homepage https://www.linkedin.com/learning/creating-binge-worthy-l-d-content AusFile https://ausfile.com/kjt46j4nm4y9/yxusj.Creating.Binge-Worthy.LD.Content.rar RapidGator https://rapidgator.net/file/cc3efca3bd19963351f9a0017d8e7a1b/yxusj.Creating.Binge-Worthy.LD.Content.rar

Cloud Architecture: Advanced Concepts Duration: 1h 23m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 231 MB Genre: eLearning | Language: English If you're an IT professional, you already know that new architectural patterns and concepts are changing the way we design for the cloud. This is especially true in today's remote and hybrid work environment, where choosing the right type of cloud platform can determine the success and functionality of your entire IT enterprise.Join instructor Lee Atchison as he shows you the business and tech-related basics of orchestrating and managing an effective cloud architecture. Learn about the various types of cloud platforms and architecture types, as well as how to determine which option will work best for you. Explore service and microservice architectures, data management tools, serverless computing, and cloud security as you build out your infrastructure. Lee shows you how to successfully incorporate automation and management practices into your architecture strategy so you can create a more efficient environment for software development. More Info AusFile https://ausfile.com/dcqvfj5g83u1/yxusj.Cloud.Architecture.Advanced.Concepts.rar RapidGator https://rapidgator.net/file/233af6c2415a981c27e9ba1e18457c42/yxusj.Cloud.Architecture.Advanced.Concepts.rar

AI Solution Design Patterns: Data, Models, Deployment, and Governance Released: 4/3/2025 Duration: 1h 8m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 153 MB Genre: eLearning | Language: English This course covers a set of established design patterns that encompass proven techniques for solving common design problems, as well as feature sets of common AI solutions. Explore how design patterns can help AI professionals work smarter, faster, and more efficiently. Along the way, instructor Thomas Erl outlines best practices when working with AI technologies, as well as how AI solutions can be broken down into individual concerns when distributing functions, integrating functions, or building AI systems from scratch. By the end of this course, you'll be prepared to work with data-centric, model-centric, and application-centric design patterns. More Info Please check out others courses in your favourite language and bookmark them - - - - AusFile https://ausfile.com/ligdsfx7928n/yxusj.AI.Solution.Design.Patterns.Data.Models.Deployment.and.Governance.rar RapidGator https://rapidgator.net/file/728c7a39d41f6423c0c854a806885e80/yxusj.AI.Solution.Design.Patterns.Data.Models.Deployment.and.Governance.rar

AI Pair Programming with GitHub Copilot X .MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 23m | 202 MB Instructor: Ronnie Sheer The future of programming is all about collaboration-humans working with machines to achieve exciting and unimagined results. AI pair programming, which integrates human- and machine-generated code, is a prime example of a tool that alleviates tedious, menial tasks to let developers focus their attention on higher-level concerns. In this course, instructor Ronnie Sheer shows you how to get the most out of GitHub Copilot X, one of the most useful and impactful new tools for streamlining software development with AI based on the most recent version of ChatGPT-4. Get a comprehensive introduction on how to use Copilot to integrate your coding with the latest AI technology. Ronnie goes over the major features of the application, focusing specifically on Pythonista and JavaScript, and using back-end and front-end Copilot tools. By the end of this course, you'll be prepared to create data models, implement REST APIs, and write tests, client-side code and templates, HTML, CSS, and more. Exercise Files on GitHub More Info AusFile https://ausfile.com/es27jbl4nvjz/yxusj.AI.Pair.Programming.with.GitHub.Copilot.rar RapidGator https://rapidgator.net/file/c9300d91c34018a266f9777cc12417a1/yxusj.AI.Pair.Programming.with.GitHub.Copilot.rar

30-Second Elevator Pitch Mastery Released: 04/2025 Duration: 10m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 48 MB Level: Beginner + Intermediate | Genre: eLearning | Language: English Interested in mastering the art of the elevator pitch? This course was designed for you. Join instructor Ronnell Richards as he covers the purpose of a pitch, identifying and defining your ideal customer profile (ICP), structuring your pitch using the 3Ws framework, and refining your delivery for clarity and confidence. Along the way, you'll also learn techniques to adapt your pitch to different audiences or scenarios, ensuring it resonates every time. By the end of this course, you'll have a polished pitch that communicates your value and starts conversations with impact. Homepage https://www.linkedin.com/learning/30-second-elevator-pitch-mastery AusFile https://ausfile.com/5qdbr7rjnjgh/yxusj.30-Second.Elevator.Pitch.Mastery.rar RapidGator https://rapidgator.net/file/b29f0effd3b4d8a12ead3a1d036d3c5b/yxusj.30-Second.Elevator.Pitch.Mastery.rar