• views: 213
• date: 16 September 2026
• posted by: AD-TEAM

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• date: 16 September 2026
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• date: 16 September 2026
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Horizontal Pod Autoscaling in Kubernetes
Released 9/2026
By Travis Thomsen
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 1h 11m 54s | Size: 287.5 MB

Managing Kubernetes workloads with static pod counts leads to wasted resources during lulls and performance degradation during peak traffic.

Managing Kubernetes workloads with static pod counts leads to wasted resources during lulls and performance degradation during peak traffic.
In this course, Horizontal Pod Autoscaling in Kubernetes, you'll gain the ability to create an HPA and add it to your deployment as well as understand how it works. First, you'll explore how HPAs work and the mechanics behind scaling out your pods. Next, you'll discover the behavior of scaling up and scaling down pods in your deployment. Finally, you'll learn how to troubleshoot common issues with your HPA. When you're finished with this course, you'll have the skills and knowledge to be able to create an HPA for your deployment and know what you will need to understand how an HPA will scale your pods.

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• date: 16 September 2026
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Nonlinear Regression Models
Released 9/2026
By Nicolae Caprarescu
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 1h 6m 52s | Size: 184.8 MB

Relationships in business and operational data do not always follow a straight line, and choosing too little or too much flexibility can weaken a regression analysis.

Relationships in business and operational data do not always follow a straight line, and choosing too little or too much flexibility can weaken a regression analysis. In this course, Nonlinear Regression Models, you'll gain the ability to recognize nonlinear structure and select regression approaches that represent it clearly. First, you'll explore visual and statistical signals of nonlinearity through an analysis of the estimated cost of generating electricity at potential offshore wind power plant sites. Next, you'll discover how predictor expansion, interactions, and polynomial regression capture complex relationships, and how cross-validation supports degree selection. Finally, you'll learn how extrapolation affects interpretation and how splines and generalized additive models represent flexible relationships. When you're finished with this course, you'll have the skills and knowledge of nonlinear regression modeling needed to choose, evaluate, and interpret models for workplace data

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• date: 16 September 2026
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OWASP MCP Top 10: Model Context Protocol AI Security Pro
Published 9/2026
Created by ACHRAF ER-RAYA
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 6 Lectures ( 1h 34m ) | Size: 1.1 GB

Master the OWASP MCP Top 10 — find, exploit, and fix Model Context Protocol vulnerabilities before attackers do.

What you'll learn
⚡ Identify and defend against the OWASP MCP Top 10 vulnerabilities in enterprise Model Context Protocol and AI agent architectures.(126 characters)
⚡ Sanitize inputs and prevent Indirect Prompt Injections from tricking LLMs into executing malicious downstream tool calls.
⚡ Implement production-ready Python wrappers to enforce authorization, schema validation, and Human-in-the-Loop controls.
⚡ Audit, threat-model, and penetration-test local and remote MCP server integrations against Tool Poisoning attacks.

Requirements
❗ Basic familiarity with Python, JSON, and general API security concepts. No prior AI security experience required.

Description

This course contains the use of artificial intelligence.

Every AI agent you connect to a tool, file system, or API through MCP is a new door into your infrastructure — and most teams haven't locked it yet.

Who this course is for
⭐ AppSec engineers, software developers, and system architects building or securing enterprise AI models, tools, and MCP integrations.

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• views: 114
• date: 16 September 2026
• posted by: mposterz

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• date: 16 September 2026
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Enterprise Architecture Decisions & Future-Ready Design 2026
Published 9/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 5h 31m | Size: 6.5 GB

Master architecture trade-offs, decision frameworks, AI governance, data products, observability, and future-ready enter

What you'll learn
Evaluate enterprise architecture trade-offs and make practical, defendable decisions.
Apply decision frameworks when requirements, constraints, and information are incomplete.
Identify architecture anti-patterns and avoid overengineering in enterprise solutions.
Compare build vs buy vs managed services and evaluate vendor lock-in strategically.
Design future-ready architectures using data products, contracts, observability, metadata, and knowledge layers.
Apply AI governance, Agentic AI security, LLMOps, AgentOps, privacy, and compliance principles.
Design self-service data platforms using platform engineering and governed delivery patterns.
Communicate architecture recommendations clearly to executives and stakeholders.

Requirements
Basic understanding of data, BI, cloud, or enterprise systems is helpful but not mandatory.
No programming experience is required.
No specific cloud platform or BI tool is required.
Prior exposure to solution architecture, data architecture, BI architecture, or cloud architecture will help learners get more value from the course.
Learners should have an interest in moving toward senior architect or enterprise architect responsibilities.

Description
Phase 5 brings the entire Enterprise Architecture Series together.
Enterprise architecture is not just about choosing technologies. It is about making the right decisions when business priorities, requirements, budgets, risks, and technologies are constantly changing.

In this course, you will learn how enterprise architects evaluate trade-offs, work with incomplete information, avoid common anti-patterns, balance practical design with overengineering, and decide between build, buy, and managed-service options.

You will also learn how to evaluate vendor lock-in, document architecture decisions, communicate effectively with executives, and develop the broader skills required to become an enterprise architect.

The second half of the course focuses on the next generation of enterprise architecture for 2026–2027. You will explore data products, data contracts, data observability, active metadata, catalogs, lineage, knowledge layers, AI governance, agentic AI security, LLMOps, AgentOps, privacy, data sovereignty, clean rooms, partner analytics, self-service data platforms, and platform engineering.

Finally, we bring everything together through a complete enterprise architecture master scenario and a future-ready architecture blueprint.

By the end of this course, you will be able to evaluate complex architecture scenarios, communicate your decisions clearly, and design enterprise platforms that are practical, governed, scalable, AI-ready, and aligned with business goals
This course used AI to create some of the content

Who this course is for
Solution Architects who want to grow into Enterprise Architect roles.
Data Architects, BI Architects, Cloud Architects, and AI Architects who want a broader enterprise perspective.
Technical Leads, Senior Developers, and Engineers involved in architecture decisions.
Consultants who need to design and communicate enterprise-scale solutions to clients.
Data and BI professionals moving toward architecture and leadership roles.
Architects who want to understand modern topics such as data products, observability, Agentic AI, AI governance, and platform engineering.
Technology leaders who need to evaluate architecture choices based on business value, risk, cost, and long-term sustainability.

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• date: 16 September 2026
• posted by: 0nelove

Kali Linux & Shell Scripting: Learn Linux for Cybersecurity
Published 9/2026
Created by SOCProfessionals Leading SOC & IR trainings
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 51 Lectures ( 7h 48m ) | Size: 4.1 GB

Learn Kali Linux, Linux commands, Bash scripting, security tools, automation, and practical command-lines from scratch

What you'll learn
⚡ Master essential Kali Linux commands for navigating, managing files, users, processes, permissions, networking, and system administration.
⚡ Learn shell scripting from the fundamentals and create practical Bash scripts to automate repetitive Linux administration and security tasks.
⚡ Work confidently with Linux files, directories, permissions, processes, environment variables, pipes, redirection, grep, awk, sed, and other powerful commands.
⚡ Build real-world automation scripts using variables, conditions, loops, functions, command-line arguments, and error handling in Bash.

Requirements
❗ No prior Kali Linux or shell scripting experience is required. Basic computer knowledge is helpful, and learners should have access to a computer where Kali Linux can be installed or run in a virtual machine.

Description

Kali Linux & Shell Scripting: Master Ethical Hacking Automation
Take your Linux and cybersecurity skills to the next level with this practicalKali Linux and Shell Scripting course.

This course is designed for beginners and aspiring cybersecurity professionals who want to understand theLinux command line, Kali Linux, security tools, and shell scripting through practical, easy-to-follow lessons.

With51 carefully structured videos, you will learn essential Linux commands, explore commonly used security tools available in Kali Linux, and build a strong foundation in shell scripting and automation.

What You'll Learn

✨33 Essential Linux Commands
Master the most important Linux commands used for file management, navigation, permissions, processes, networking, system administration, and everyday command-line tasks.

✨8 Kali Linux Security Tools
Get introduced to practical security tools available in Kali Linux and understand their purpose, basic usage, and role in cybersecurity workflows.

✨Shell Scripting & Automation
Learn how to create and execute shell scripts, work with variables, conditions, loops, functions, command-line arguments, and other scripting concepts to automate repetitive tasks.

Course Highlights

✨ 51 practical video lessons

✨ 33 essential Linux commands

✨ 8 Kali Linux security tools

✨ Hands-on shell scripting

✨ Linux command-line fundamentals

✨ Bash/Shell automation concepts

✨ Practical cybersecurity-oriented examples

✨ Beginner-friendly explanations

✨ Learn by practicing in Kali Linux

Who Is This Course For?

This course is ideal for

✨ Beginners learning Linux and Kali Linux

✨ Students interested in cybersecurity and ethical hacking

✨ Aspiring penetration testers

✨ System and network administrators

✨ IT professionals who want to improve their Linux skills

✨ Anyone interested in Shell/Bash scripting and automation

By the End of This Course

You will have a solid foundation inKali Linux, essential Linux commands, cybersecurity tools, and shell scripting. You will be able to confidently work with the Linux command line and start creating scripts to automate common tasks.

Start your journey into Kali Linux, Shell Scripting, and cybersecurity today!

Who this course is for
⭐ This course is designed for beginners and IT professionals who want to learn Kali Linux commands and Bash shell scripting from the ground up. It is ideal for aspiring cybersecurity professionals, Linux administrators, DevOps engineers, system administrators, penetration testing beginners, and anyone who wants to automate tasks using shell scripts.

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• date: 16 September 2026
• posted by: voska89

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• date: 16 September 2026
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LangChain with TypeScript: Build AI Apps, RAG & Agents
Published 9/2026
Created by Haider Malik
MP4 | Video: h264, 2560x1440 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 135 Lectures ( 6h 33m ) | Size: 4.8 GB

Learn LangChain.js, RAG, Tools, Agents, and LangGraph by building real-world AI applications with TypeScript

What you'll learn
⚡ Build AI applications with LangChain.js and TypeScript using modern LLM development patterns.
⚡ Build Retrieval-Augmented Generation (RAG) applications using embeddings, vector stores, and retrievers.
⚡ Build AI agents that use tools and understand how tools, agents, and workflows work together.
⚡ Build advanced agentic workflows with LangGraph and understand how it fits into the LangChain ecosystem.

Requirements
❗ Basic jаvascript or TypeScript programming knowledge. Familiarity with Node.js and npm is recommended. You should have a computer with internet access. No prior LangChain, RAG, or AI agent experience is required.

Description
Build real-world AI applications withLangChain.js, TypeScript, RAG, Tools, Agents, and LangGraph.

In this course, you'll learn how to use LangChain with TypeScript to build modern AI applications step by step. Instead of jumping directly into complex agents, you'll build a strong foundation and gradually move toward more advanced AI application patterns.

You'll start by understanding the core concepts of LangChain and then progress through prompts, output parsers, embeddings, memory, vector stores, retrievers, and RAG. From there, you'll learn how tools work, how agents use tools, and how LangGraph can be used to build more advanced agentic workflows.

What you'll learn

✨ Build AI applications usingLangChain.js and TypeScript

✨ Understand LangChain's core building blocks and how they fit together

✨ Work with prompts and prompt templates

✨ Parse and structure model outputs

✨ Understand embeddings and how they are used in AI applications

✨ Work with vector stores and similarity search

✨ Build retrieval-augmented generation (RAG) applications

✨ Understand retrievers and how they work with RAG

✨ Give AI applications access to external tools and functions

✨ Understand the difference between tools, agents, and workflows

✨ Build AI agents using LangChain

✨ Understand how LangGraph fits into modern AI application development

✨ Build practical AI applications instead of only learning isolated concepts

A practical, step-by-step approach

Many AI tutorials jump straight into building an agent without explaining the concepts underneath it. This course takes a different approach.

You'll progressively build your knowledge

LangChain fundamentals → Prompts → Output Parsers → Embeddings → Vector Stores → Retrievers → RAG → Tools → Agents → LangGraph
This progression helps you understand not onlyhow to use LangChain, but alsowhy these different components exist and when you should use them.

Who is this course for?

This course is for developers who want to build AI-powered applications usingTypeScript and jаvascript.

It's a good fit if you're a

✨ TypeScript or jаvascript developer

✨ Node.js developer

✨ Full-stack developer

✨ Developer interested in LLM applications

✨ Developer who wants to learn RAG and AI agents

✨ Developer who wants to use LangChain.js rather than learning only Python-based examples

You don't need to become an AI researcher to follow this course. The focus is on understanding the concepts and applying them to real software development.

What you'll build

Throughout the course, you'll work with practical examples and progressively combine the concepts you've learned to build AI application functionality.

By the end of the course, you'll have a much clearer understanding of how the pieces of a modern LLM application fit together—from calling models and structuring outputs to retrieval, RAG, tools, agents, and graph-based workflows.

If you're a TypeScript developer who wants to move beyond basic LLM API calls and learn how to build more capable AI applications withLangChain.js, this course is for you.

Who this course is for
⭐ jаvascript and TypeScript developers who want to build AI-powered applications with LangChain.js. Ideal for Node.js and full-stack developers interested in RAG, AI agents, tools, and LangGraph.

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• views: 143
• date: 16 September 2026
• posted by: 0nelove

HSK 3 Chinese Course (3.0) |Course for Intermediate Learners
Published 9/2026
Created by Joanna Li
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 36 Lectures ( 15h 49m ) | Size: 15.8 GB

HSK 3 Chinese Course (3.0)

What you'll learn
⚡ Understand and use essential HSK 3 vocabulary and grammar in everyday Chinese conversations.
⚡ Communicate more confidently in common situations, such as shopping, traveling, making plans, discussing daily routines, and expressing opinions.
⚡ Understand the main ideas and important details in HSK 3-level conversations, short texts, and everyday Chinese messages.
⚡ Construct longer and more natural Chinese sentences using key HSK 3 grammar patterns and sentence structures.

Requirements
❗ Basic knowledge of Mandarin Chinese is recommended.
❗ Learners should have a basic understanding of Mandarin Chinese, approximately at the HSK 2 level.

Description

Take your Mandarin Chinese to the next level with HSK 3.0!
Welcome to theHSK 3 Chinese Course (3.0) | Learn Mandarin Step by Step.

This course is designed for learners who have a basic foundation in Mandarin and are ready to move beyond beginner-level Chinese. Through structured, step-by-step lessons, you will build your vocabulary, strengthen your grammar, improve your listening and speaking skills, and become more confident using Chinese in everyday situations.

In this course, you will learn essential HSK 3 vocabulary and grammar through practical examples and useful conversations. You will practice how to describe experiences, express opinions, make plans, give suggestions, explain reasons, make comparisons, and communicate naturally in a variety of real-life situations.

What you will learn

✨ Essential HSK 3 vocabulary and useful everyday expressions

✨ Key HSK 3 grammar patterns and sentence structures

✨ Listening and speaking skills for everyday Chinese communication

✨ Reading and understanding HSK 3-level texts and conversations

✨ Practical ways to express ideas, experiences, opinions, and plans in Chinese

✨ More natural and confident Mandarin communication

Whether you are preparing for theHSK 3 exam or simply want to improve your practical Chinese, this course will help you develop a stronger and more complete Mandarin foundation.

Learn step by step, practice with confidence, and make your Chinese more natural!

Who this course is for
⭐ Learners who have completed HSK 1 and HSK 2 and want to continue developing their Mandarin Chinese skills.

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• views: 247
• date: 16 September 2026
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• date: 16 September 2026
• posted by: 0nelove

AWS Serverless Compute Operations
Released 9/2026
By Arpad Toth
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 1h 27m 43s | Size: 249.1 MB

Event-driven workloads depend on AWS Lambda functions that trigger correctly, are observable, and can recover when they degrade.

Event-driven workloads depend on AWS Lambda functions that trigger correctly, are observable, and can recover when they degrade. In this course, AWS Serverless Compute Operations, you'll gain the ability to implement, operate, and recover event-driven AWS Lambda functions and to judge when Lambda is the right compute choice. First, you'll explore when Lambda fits a workload and when it doesn't, and then create a function and configure its runtime, identity, and resource settings to match the workload. Next, you'll discover how to connect functions to synchronous, asynchronous, and poll-based event sources and verify each trigger produces a successful invocation end to end. Finally, you'll learn how to interpret invocation logs and metrics, distinguish cold starts from warm invocations, diagnose and recover throttled and failed invocations, and diagnose invocation-time permission errors. When you're finished with this course, you'll have the skills and knowledge of event-driven Lambda implementation, operation, and recovery needed to build and maintain production-grade serverless workloads on AWS.

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• views: 208
• date: 16 September 2026
• posted by: 0nelove

AWS Certified Security - Specialty (SCS-C03): Incident Response
Released 9/2026
By Michael Brown
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 2h 14m 31s | Size: 369.1 MB

When a security incident occurs, you may find yourself either wishing you had more information on hand or, just as bad, weighed down with information and not knowing where to find it.

When a security incident occurs, you may find yourself either wishing you had more information on hand or, just as bad, weighed down with information and not knowing where to find it. In this course, AWS Certified Security - Specialty (SCS-C03): Incident Response, you'll gain the ability to use AWS services to prepare for an incident, so you can gather relevant information and know how to use it. First, you'll explore the AWS services needed to create an incident response plan. Next, you'll discover how to work with AWS services to implement alerting and notifications to prepare and automatically respond to an incident. Finally, you'll learn how to perform root cause analysis and how to recover from an incident. When you're finished with this course, you'll have the skills and knowledge of incident response needed to be a productive member of an incident response team and the knowledge needed to attempt the incident response questions on the AWS Certified Security - Specialty (SCS-C03) exam.

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• views: 195
• date: 16 September 2026
• posted by: 0nelove

File Systems Explained: FAT32, NTFS, EXT and APFS
Published 9/2026
Created by Mustafa Mowafek
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 28 Lectures ( 5h 17m ) | Size: 2.3 GB

Read a disk at byte level: hex editor, boot sector, Master File Table and recovering deleted files

What you'll learn
⚡ Distinguish sectors, clusters, allocated and unallocated space, and slack space
⚡ Work with a hex editor and convert values between hexadecimal, decimal and binary
⚡ Tell little endian from big endian and interpret byte sequences correctly
⚡ Use offset tables to locate specific structures inside a disk image
⚡ Analyze MBR and GPT partitioning and explain the forensic differences
⚡ Take FAT32 apart: boot sector, FAT region, directory entries and data region
⚡ Read the NTFS Master File Table and analyze the most important MFT attributes
⚡ Distinguish resident from non-resident data and detect alternate data streams
⚡ Explain what happens on deletion and recover deleted files
⚡ Classify the structures of exFAT, EXT and APFS, including inodes and APFS snapshots

Requirements
❗ Basic computer skills, some familiarity with file systems is helpful
❗ No prior knowledge of hexadecimal required, it is taught in the course
❗ Recommended for hands-on practice: a free hex editor and a sample disk image

Description
This course contains the use of artificial intelligence.

All content was researched, written and structured by human forensic practitioners. AI is used for the narration voice and for parts of the course graphics

When a file is deleted, the data does not disappear. Only the pointer to it does.
Understand that, and you can recover deleted files. Miss it, and you are relying on a tool you cannot explain in court. This course goes one level deeper than any analysis software: down to the bytes themselves.

Foundations. First the vocabulary: allocated and unallocated space, sectors, clusters and blocks. Then a detail that decides many cases, slack space, where fragments of older files survive.

The hex editor. The central tool. Converting between hexadecimal, decimal and binary, little endian versus big endian, and why byte order decides between right and wrong. Then the practice: the layout of a hex view, working with offset tables, locating sub-offsets and interpreting the values you extract.

Partitioning. MBR on classic BIOS systems, GPT on modern EFI systems, and the differences that matter forensically.

The FAT family. FAT12, FAT16 and FAT32 taken apart completely: boot sector and reserved region, the FAT region with its cluster chain, root directory and the layout of a directory entry, long file names under VFAT, and the data region. Then the decisive question: what happens on deletion and how to get the file back. Plus exFAT with its own boot sector and cluster heap.

NTFS. The centerpiece: the Master File Table. Its fixed layout and fixed records, MFT records and their attributes in detail, including STANDARD INFORMATION with its timestamps, FILE NAME, and DATA with the difference between resident and non-resident content and the virtual cluster number. Plus alternate data streams, which can hide entire files, and how storing, deleting and recovering works on NTFS.

EXT and APFS. Linux with superblock, block groups and inodes. Apple with the APFS container concept and the features that matter for analysis: snapshots, clones and encryption.

After this course you no longer read a disk through a tool. You understand what the tool is showing you, and you notice when it is wrong.

What is primarily taught in your course?
The forensic analysis of file systems at byte level: working with a hex editor, offset tables and endianness, partitioning with MBR and GPT, and the complete structure of FAT12, FAT16, FAT32, exFAT, NTFS, EXT and APFS, including boot sector, Master File Table, MFT attributes, slack space, and what actually happens when a file is deleted.

Who this course is for
⭐ Digital forensic examiners who want to understand what their tools do under the hood
⭐ Investigators who need to explain and verify recovered data themselves
⭐ Incident response teams and administrators interested in data recovery
⭐ Students of information security and computer science

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• views: 227
• date: 16 September 2026
• posted by: 0nelove

Create a 2D Space Shooter in Unity: From Beginner to Creator
Published 9/2026
Created by Giorgi Luarsabishvili
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 22 Lectures ( 4h 37m ) | Size: 2.9 GB

Unity 2D Fundamentals: From Zero to Space Shooter Hero

What you'll learn
⚡ Navigate Unity & C#: Master the Unity Editor interface and write foundational C# scripts to control game objects and mechanics.
⚡ Build Core Gameplay Loops: Program player movement, shooting systems, dynamic enemy waves, and interactive obstacles.
⚡ Implement Power-Ups: Code rewarding gameplay modifiers like health bonuses and temporary immortality shields.
⚡ Design UI and Audio: Create polished main menus, HUD overlays, pause screens, and integrate immersive sound effects.

Requirements
❗ No prior coding or Unity experience: Absolute beginners are welcome. We teach everything from scratch.
❗ A computer: A PC or Mac (Windows, macOS, or Linux) capable of running the Unity Editor.
❗ Unity Hub & Unity Editor: Free software downloads

Description
Are you ready to turn your passion for gaming into real-world skills? If you have ever wanted to create your own video games but didn't know where to start,Unity 2D Fundamentals: Build Your First Space Shooter is the ultimate beginner-friendly launchpad for your game development journey.

Designed specifically for absolute beginners withno prior coding or Unity experience required, this comprehensive course takes you by the hand and guides you step-by-step through the entire process of building a polished, fully functional 2D arcade space shooter from scratch.

Throughout this hands-on learning adventure, you won't just watch theory—you will code, design, and ship a complete game. You will master the essentials of the Unity engine, C# scripting, and game design principles by implementing core gameplay mechanics that every great game needs

✨Player Mechanics & Controls: Program smooth player movement, boundary clamping, and responsive shooting mechanics.

✨Enemies & Obstacles: Code diverse enemy behaviors and floating obstacles that challenge the player and keep the gameplay engaging.

✨Power-Ups & Bonuses: Implement rewarding mechanics including health bonuses and temporary immortality shields to add depth and strategy.

✨User Interface & Menus: Design professional start menus, pause screens, game-over states, and real-time score/health HUDs.

✨Audio & Atmosphere: Elevate your game's polish by integrating immersive background music, laser sound effects, and explosive audio cues.

By the end of this course, you will not only have a complete, playable space shooter ready to share with friends, family, or your portfolio, but you will also have the foundational confidence to tackle your own game ideas in Unity.

Take the first step toward becoming a game developer. Enroll today and start building your gaming universe!

Who this course is for
⭐ Absolute Beginners: Aspiring game developers with zero prior coding or game design experience.
⭐ Hobbyists & Creatives: Anyone who wants to understand how video games are made by building a fun, classic arcade game from scratch.
⭐ Indie Game Aspirants: Creators looking for a solid foundational project to kickstart their Unity and C# learning journey.
⭐ Students & Tinkering Programmers: Learners wanting a hands-on, practical introduction to game loops, UI, and audio integration without getting bogged down in heavy math.

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• views: 206
• date: 16 September 2026
• posted by: 0nelove

Claude Code for Windows: Build Real Apps with Vibe Coding
Published 9/2026
Created by Being Commerce
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 33 Lectures ( 5h 45m ) | Size: 5.8 GB

Learn claude code windows setup and windows vibe coding to build real apps, games, and websites - no coding skills!

What you'll learn
⚡ Install, set up, and configure claude code windows from scratch
⚡ Understand vibe coding and how to guide AI to write real code
⚡ Build apps using HTML, CSS, and jаvascript
⚡ Set up Claude Code with VS Code and other IDEs on Windows
⚡ Build backend systems using Python and Django
⚡ Work with databases and Django ORM
⚡ Build a game using AI-assisted modularity
⚡ Set up Python packages and virtual environments
⚡ Scrape and analyze real websites
⚡ Connect to and build projects using real APIs
⚡ Add user interfaces, error pages, and authentication systems
⚡ Add token and billing systems to an app
⚡ Publish a finished app live using GitHub and Railway

Requirements
❗ A Windows computer with internet access
❗ No prior coding experience needed
❗ Willingness to build, not just watch

Description
You already have Claude Code for Windows on your screen. What you don't have yet is the skill to turn it into real, working apps. That gap is what this course closes.

This is a full claude code for windows course built for people who want to create actual software — websites, games, APIs, and full backend systems — using AI as the coder. You don't need a computer science degree. You don't need years of practice. You need a clear path, and that is exactly what this course gives you.

We start from zero. You will install and set up claude code windows on your machine, connect it with Python and VS Code, and understand exactly how windows claude code works before touching a single real project. From there, every section adds a new real skill: HTML, CSS, and jаvascript apps, backend work with Python and Django, database handling, web scraping, working with real APIs, building user login systems, adding token and billing systems, and finally publishing your app live on the internet.

Here is the problem most beginners face: they watch tutorials, copy code, and still cannot build anything on their own. This course fixes that by teaching you windows vibe coding — a way of building software where you describe what you want and guide the AI to write, fix, and improve the code with you. You stay in control. You understand what is happening. You are not just copying — you are building.

If you skip this course, you will keep depending on other people to build your ideas, or you will keep getting stuck at the same wall every beginner hits — knowing what to do in theory, but freezing when it is time to actually build. Every section here removes one more reason to stay stuck.

By the time you finish, you will have shipped multiple real projects: a working website, a game, a scraping tool, an API-based project, and a full app with login, billing, and a live database — deployed and published for anyone to use. This is not a course about watching. This is a course about building.

Whether you are a complete beginner, a small business owner who wants to build your own tools, or someone curious about claude for windows and what it can actually do, this course gives you a direct, practical path from zero to a published app.

Enroll now and start building with claude code for windows today.

Who this course is for
⭐ Beginners who want to build real apps without learning to code the hard way
⭐ Small business owners who want to build their own tools
⭐ Students who want a practical, project-based way to learn software building
⭐ Freelancers who want to offer app-building services using AI
⭐ Anyone curious about claude for windows and what it can really do
⭐ People who tried coding before and quit, and want a simpler way back in

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• views: 166
• date: 16 September 2026
• posted by: 0nelove

AI Red Teaming: Test, Evaluate & Improve AI Systems
Published 9/2026
Created by Marina Langer
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 17 Lectures ( 2h 11m ) | Size: 1.1 GB

Learn AI red teaming, identify AI failures, test model behavior, assess risks, and report findings professionally.

What you'll learn
⚡ Identify and analyze common AI failure modes, including hallucinations, reasoning errors, and instruction-following failures.
⚡ Design practical red-team tests and challenging prompts to evaluate AI system behavior and reliability.
⚡ Evaluate AI responses using structured rubrics, evidence, severity levels, and risk-based scoring. Поле 4
⚡ Document AI failures and create clear, professional red-team findings with actionable recommendations.

Requirements
❗ No programming or advanced technical knowledge is required. Basic computer skills and an interest in AI are sufficient.

Description
This course contains the use of artificial intelligence.

Course Description

This course provides a practical introduction toAI Red Teaming — the systematic process of testing AI systems, identifying weaknesses, evaluating failures, and documenting findings.

You will learn how to examine AI-generated responses beyond surface-level quality and identify problems that may remain hidden behind confident or polished language.

Throughout the course, you will explore important AI failure modes includinghallucinations, factual errors, instruction-following failures, reasoning problems, bias, unsafe responses, and hidden omissions.

You will also learn how professional red teamers design effective test prompts, use adversarial testing techniques, compare AI responses, assess the severity and potential impact of failures, and document findings in a clear and evidence-based red team report.

The course includes practical examples and structured exercises designed to help you develop a systematic approach to AI evaluation and red teaming.

By the end of the course, you will understand how to

✨ Design purposeful red team tests rather than rely on random prompting

✨ Identify obvious and hidden failures in AI-generated responses

✨ Test instruction following, reasoning, factuality, bias, and safety

✨ Compare multiple AI responses objectively

✨ Assess failure severity and potential impact

✨ Document evidence and create professional red team reports

✨ Apply a structured red teaming workflow to realistic AI scenarios

No previous AI red teaming experience is required. The course is designed to be accessible to beginners while introducing methods that reflect real AI evaluation and testing workflows.

AI Transparency Notice
This course was developed and directed byMarina Langer with the assistance of generative AI tools. AI technology was used to support the creation of selected educational materials, visuals, narration, and video content. The course structure, learning objectives, topic selection, instructional direction, review, and final editorial decisions were overseen by the instructor.

The goal is not simply to find mistakes in AI systems, but to understand their behavior throughsystematic, objective, and evidence-based testing.

Test systematically. Judge objectively. Document with evidence.

Who this course is for
⭐ Beginners who want to develop practical skills in AI evaluation, testing, and red teaming.
⭐ AI Evaluators, data annotators, QA professionals, and aspiring AI safety specialists who want to expand their skills.
⭐ Professionals and career changers interested in testing AI systems and building practical AI evaluation portfolio projects.

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