NulledCodeSolutions.online

Manufacturer : Udemy
Manufacturer’s website : Code:Copy to clipboard

https://www.udemy.com/course/practical-encryption/

Author : Paul Mahon
Duration : ~2h5m
Type of material distributed : Video lesson
Language : En
Описание: Encryption is a very simple concept. You scramble information so that it cannot be read by other people. The math or algorithm that you use to scramble the information just needs to be good enough so that other people can’t decipher your encrypted data. What could be simpler? If all you wanted to do was hide information from everyone else.this would be pretty much it.
The application of encryption in the real world, however, is a bit more involved. It is true that you don’t need to understand the complex math behind encryption to deploy it or use it. However, you do need to understand the various types of encryption and the implications and applications of using them.
My name is Paul Mahon and welcome to my hands-on course on encryption. I’ll teach you about symmetric encryption, public key encryption, digital signatures, hashing and digital certificates with SSL/TLS
We’ll use some basic python code and other open source applications to implement what we have learned. No worries if you’re not familiar with python – it’s a few simple lines of code. However, this will be a good application of python if you are.
At the end of this course you should have a thorough understanding of encryption and the importance of things like key lengths, ciphers, hashing algorithms and certificate authorities.
This course is designed for anyone that wants to tinker around with encryption to understand how it actually works in the real world. It’s also helpful for professionals that need to know about encryption for their job or students of information security.
Content
02:12
03:17
04:56
Setting Up Python Environment
02:47
Ubuntu Instance
03:39
Introduction to Symmetric Encryption
05:13
Working with Symmetric Encryption
07:15
Introduction to Asymmetric Encryption
03:14
Working with Public Key Encryption
03:48
Public Key Encryption with Symmetric Encryption
08:16
Hashing & Digital Signatures
01:25
Hashing algorithms
04:37
Signing Documents
06:43
Course Summary
02:14
Module Overview
05:37
Creating Your Own Certs
13:58
Creating Self-signed Certs with Python
10:26
Local Certificate Authority Overview
03:43
Configuring a Local CA
11:32
Revoke a Certificate
06:19
Introduction to GnuPG
01:56
Encryption and Digital Signatures with GPG
11:16
Module Overview
01:30
Example files : present
Video format : MP4
Video : AVC, 1280×720, 16:9, 30fps, ~500kbps
Audio : AAC, 44.1kHz, 128kbps, stereo

Udemy – Practical Encryption (894.96 MB)
RapidGator Link(s)
Code:Copy to clipboard

https://rapidgator.net/file/6d53cfa621e80b43370524f09f4a6d8b/Udemy.-.Practical.Encryption.rar

UsersDrive Link(s)
Code:Copy to clipboard

https://usersdrive.com/z6lglj43vtml.html

Last updated 4/2024 Created by Timotius Pamungkas MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + srt | Duration: 117 Lectures ( 11h 10m ) | Size: 5 GB​

Devops / SRE technology: docker, kubernetes, istio, grafana, prometheus, gitops, google kubernetes engine, argocd, kiali

What you’ll learn:
Learn about container and container orchestration using kubernetes
Operate kubernetes for microservice architecture
Use and configure nginx as ingress controller for kubernetes cluster
How to use argocd for gitops implementation
Kubernetes concept from the very beginning : pod, deployment, volume, service, ingress, horizontal pod autoscaling
What is istio and how it relates with kubernetes
Simplify, or eliminate application code by using istio & envoy proxy
Create kubernetes analytics using prometheus & grafana for metrics visualization
How to use helm on kubernetes, including create helm and helm repository with chartmuseum
Istio traffic management, circuit breaker, canary release, dark launching, and security using mutual TLS (mTLS)
Kubernetes & istio implementation using GCP (Google Cloud Platform) / GKE (Google Kubernetes Engine)

Requirements:
Just some familiarity with basic linux command (e.g. navigate to folder, run shell command). But other than that, you don’t need anything, we will learn from the very beginning
A laptop (Windows / Mac / Linux) with at least 4 CPU core and 8 GB memory (16 GB reccomended)
No programming experience required

Description:
OverviewThis devops bootcamp is the first among several series (coming soon!) to start -or advance- your career as DevOPs or SRE (Site Reliability Engineer).In this course, you will learn about container technology (docker) and container orchestration (kubernetes). Those are a-must-have knowledge for DevOps engineeer, as docker and kubernetes are popular technology and well sought by many companies. You will also learn about GitOps using ArgoCD, and how to use Istio Service Mesh with Envoy proxy to ease the application management.What We Will LearnWe will learn how to manage application written on microservice architecture. You don’t need to know any programming language to works with this course. In fact, this course is not about programming language, and mostly we will works with text files, terminal, or even graphical user interface.Learn how to reach infrastructure agility, and easier maintenance compared to traditional infrastrucutre (virtual machine, bare metal). With the help of kubernetes, along with other tools that integrates well, maintaining reliable infrasturcture become a skill that everybody can learn (by using this course, for example).But kubernetes and docker is not the only technology required for DevOps engineer journey. In this course, we will learn real-life infrastructure architecture that leverages several technologies, integrated to kubernetes. They are:Nginx : very popular reverse proxy,http load balancer, which is used as traffic gateway, or kubernetes ingress controllerSealed secret : secure your username, password, and any other "secret" things on kubernetes. Update and share them safely, since the kubernetes will "seal" them and encrypt them in secure wayGrafana, Prometheus : for kubernetes & infrastructure data gathering, analytics, and visualizationHelm : a package manager for kubernetes. Think of zip archive, but kubernetes-style, that can customizedChartmuseum : a repository for helmArgoCD : learn GitOps, a subset of DevOps that focusing on automatic infrastructure based on git repository. Works well since most software engineering team will already familiar with git, so they can also leverage the kubernetes power without knowing the kubernetes itself. Collaborate together, and achieve automated application deployment through GitOps with ArgoCDIstio & Envoy Proxy : One of the most important item to works with kubernetes. Manage, secure, and monitor your traffic. Add application functionalities without even writing single line of codeKiali : Istio user interface to visualize your traffic that runs on kubernetes cluster,and manage them! Jaeger : distributed tracing to know how your microservices performs, which node that has problemLens : hate to see the black screen on terminal? Then use this tools to navigate your kubernetes clusterPre-requisiteslaptop with at least 8 GB memory free (so you need at least 16 GB memory)or you can use any laptop, since we will learn to use Google Kubernetes Engine (it might has limited free quota if you are new user, but it depends on google)Course CurricullumThese are the things that you will learn, in more than 100 lectures!what is container and why it so popularkubernetes from zerodeclarative kubernetesresource monitoring & limitingvolume bindingkubernetes secret & configuration mapintegrate and secure nginx on your kubernetes clusterautomatic horizontal scaling to maintain performancehow to use and create helm chartshow to host your own helm repository (for free)gitops automatic application synchronizationautomatic configuration synchronizationprovision and manage tls certificate distributed tracingservice mesh (using istio and envoy proxy)traffic management on service mesh myths / fallacies of distributed systemopentracing opentelemetryservice mesh visualizationload balancercanary releasedark launchingautomatic timeout / retry without even writing codemutual TLS for security

Who this course is for:
Anyone who wants to learn about devops, especially kubernetes and istio
Those who find a career path as devops engineer or SRE (Site Reliability Engineer)
Cloud infrastructure engineer who wants to leverage modern technology (kubernetes, istio) especially on google cloud platform (GCP)
Technical manager who wants to know how to automate microservice infrastructure using kubernetes, istio, and gitops

Welcome to – Check it Every Days
If you have any troubles with downloading, PM me

Happy Learning!! Click to expand…

Year of issue : 6/2025
Manufacturer : Udemy
Manufacturer’s website : Code:Copy to clipboard

https://www.udemy.com/course/computer-vision-mastery-real-time-projects-opencv-python-ai-yolo/

Author : Muhammad Yaqoob G
Duration : 16h 14m 23s
Type of distributed material : Video lesson
Language : En
Subtitles : En

Description:
Master Computer Vision Course in 2025 with Deep Learning, Python, OpenCV, YOLO, OCR & GUI through 20+ handson projects
What you’ll learn
Understand the origins, evolution, and real-world impact of AI, with a focus on computer vision’s role in modern applications.

Install and configure Python and VS Code for seamless development of vision-based projects on any platform.

Apply OpenCV fundamentals-reading, writing, displaying, resizing, cropping, and color-space conversion of images and videos.

Implement image processing techniques such as thresholding, morphological transforms, bitwise operations, and histogram equalization.

Detect edges, corners, contours, and keypoints; match features across images to enable object recognition and scene analysis.

Leverage advanced methods-Canny edge detection, texture analysis, optical flow, object tracking, segmentation, and OCR with Tesseract.

Build a smart face‐attendance system: enroll faces, extract embeddings, train a model, and launch a Tkinter GUI for live recognition.

Create a driver-drowsiness detector using EAR/MAR metrics, integrate it into a Tkinter dashboard, and run real-time video inference.
Requirements
Basic Python programming knowledge

Windows PC or Laptop with 4GB+ RAM is recommended. A GPU is optional but helpful for faster model training and processing large datasets or real-time tasks.
Description
Unlock the power of image- and video-based AI in 2025 with 20+ real-time projects that guide you from foundational theory to fully functional applications. Designed for engineering and science students, STEM graduates, and professionals switching into AI, this hands-on course equips you with end-to-end computer vision skills to build a standout portfolio.
Key Highlights:
Environment Setup & Basics: Install Python, configure VS Code, and master OpenCV operations-image I/O, color spaces, resizing, thresholding, filters, morphology, bitwise ops, and histogram equalization.

Core & Advanced Techniques: Implement edge detection (Sobel, Canny), contour/corner/keypoint detection, texture analysis, optical flow, object tracking, segmentation, and OCR with Tesseract.

Deep Learning Integration: Train and deploy TensorFlow/Keras models (EfficientNet-B0) alongside YOLOv7-tiny and YOLOv8 for robust detection tasks.

GUI Development: Build interactive Tkinter interfaces to visualize live video feeds, detection results, and system dashboards.
20+ Hands-On Projects Include:
Smart Face Attendance with face enrollment, embedding extraction, model training, and GUI integration.

Driver Drowsiness Detection using EAR/MAR algorithms and real-time alert dashboards.

YOLO Object & Weapon Detection pipelines for live inference and visualization.

People Counting & Entry/Exit Tracking with configurable line-coordinate logic.

License-Plate & Traffic Sign Recognition leveraging Roboflow annotations and custom model training.

Intrusion & PPE Detection for workplace safety monitoring.

Accident & Fall Detection with MQTT alert systems.

Mask, Emotion, Age/Gender & Hand-Gesture Recognition using custom-trained vision models.

Wildlife Identification with EfficientNet-based classification in live streams.

Vehicle Speed Tracking using calibration and object motion analysis.
By course end, you’ll be able to:
Develop, train, and fine-tune deep-learning vision models for diverse real-world tasks.

Integrate CV pipelines into intuitive GUIs for live video applications.

Execute industry-standard workflows: data annotation, training, evaluation, and deployment.

Showcase a portfolio of 20+ complete projects to launch or advance your AI career.
Enroll today and start building your first real-time computer vision app!
Who this course is for:
Undergraduate and Graduate Students in engineering, computer science, electronics or related fields seeking hands-on CV projects to complement their studies.

Recent Graduates with STEM degrees who want to build practical AI skills and showcase real-world projects on their résumé.

Working Professionals in software, electronics, robotics or data roles aiming to pivot into AI/ML and leverage vision applications in industry.

Career-Switchers from STEM Fields (e.g., physics, mathematics, biotech) looking for a structured path into computer vision without starting from scratch.

R&D Engineers & IoT Developers who need to integrate vision analytics on edge devices like Jetson, Raspberry Pi or in cloud pipelines.

Self-Learners & Hobbyists with a science/engineering mindset who want to master end-to-end CV workflows-from algorithm basics to GUI deployment and model inference.
Video format : MKV
Video : avc, 1920×1080, 16:9, 29.845 fps, 1978 kbps
Audio : aac lc sbr, 44.1 kHz, 62.8 kbps, 2 audio

Udemy – Practical Computer Vision Mastery 20+ Python & AI Projects (6.2025) (12.63 GB)
UsersDrive Link(s)
Code:Copy to clipboard

https://usersdrive.com/y210lorryhrs.html
https://usersdrive.com/wvy5q24r3pua.html
https://usersdrive.com/21fb2mrcv9ir.html
https://usersdrive.com/cnejhh3ez5b5.html
https://usersdrive.com/6xkecanwpddj.html

RapidGator Link(s)
Code:Copy to clipboard

https://rapidgator.net/file/2d63e1c1c4728eece06d5c729d0c899a/Udemy.-.Practical.Computer.Vision.Mastery.20.Python..AI.Projects.6.2025.part1.rar
https://rapidgator.net/file/3560101e28163475cb8c74435e8c81ca/Udemy.-.Practical.Computer.Vision.Mastery.20.Python..AI.Projects.6.2025.part2.rar
https://rapidgator.net/file/efd22434ed9d43248d307ba4e4844035/Udemy.-.Practical.Computer.Vision.Mastery.20.Python..AI.Projects.6.2025.part3.rar
https://rapidgator.net/file/d7d49a74d323e7a7fa4b31f2ea475f14/Udemy.-.Practical.Computer.Vision.Mastery.20.Python..AI.Projects.6.2025.part4.rar
https://rapidgator.net/file/4b026aec5f72f05901eeef0c9fb4302a/Udemy.-.Practical.Computer.Vision.Mastery.20.Python..AI.Projects.6.2025.part5.rar

PostgreSQL: Advanced Queries
.MKV, AVC, 1280×720, 30 fps | English, AAC, 2 Ch | 2h 50m | 416 MB
Instructor: Adam Wilbert​

In this course, database expert Adam Wilbert introduces you to a number of advanced query techniques that you can use to better understand your data. Statistical analyses involve understanding the shape and size of the full data set, and deeper insights can be gained by grouping data together to obtain some very useful metrics.

Adam shows you how to create basic groups and apply aggregate calculations, then moves into window functions that create subgroups for more granular analysis. He goes over statistics that are based on sorted data within groups, such as the median value, the first and third quartiles of a dataset, the most frequent value, and more. Adam also covers ranking, hypothetical sets, percentile functions, and conditional expressions for further manipulating query result sets. He concludes with some additional querying techniques that you may find useful in solving common problems.

More Info