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Complete Mobile Developer course with AI Projects
MP4 | Video: h264, 3840x2160 | Audio: AAC, 44.1 KHz
Language: English | Size: 35.80 GB | Duration: 22h 41m

Build real React Native & Expo apps | APIs, sensors, camera, maps, auth, EAS builds & an AI story-generator project.



What you'll learn
Build and ship real cross-platform mobile apps for Android and iOS from a single codebase using React Native and Expo.
Master Expo's core UI components and styling | View, Text, Image, TextInput, Pressable, StyleSheet, props, and list/data-display components - to build polishe
Build complete real-world apps end to end
Apply everything through hands-on mini-projects

Requirements
Basic JavaScript knowledge
No prior mobile development experience needed

Description
Become a job-ready mobile developer by building real apps with React Native and Expo | from your very first component to authentication, maps, and production builds.Mobile is where users spend most of their time, yet skilled mobile developers are still in short supply. This course closes that gap. If you already know a little JavaScript and React, you'll learn how to turn that knowledge into real, installable Android and iOS apps using Expo - the modern, beginner-friendly framework built on top of React Native and trusted in production by apps like Instagram and Discord.We start from the ground up: what mobile development is, how React Native compares to Expo, and how to set up your environment and ship your first project. From there you'll master the core components (View, Text, Image, TextInput, Pressable, StyleSheet), styling, props, and list rendering - then put them to work building real screens.Next, you'll go deep into navigation - first with React Navigation, then with modern Expo Router file-based routing, including dynamic routes, catch-all segments, layouts, route groups, stacks, tabs, drawers, and modals. You'll learn how to talk to APIs (both your own Expo API routes and external services), and how to persist data using AsyncStorage, SecureStore, SQLite, and the file system.The second half is all about going native. You'll work with device sensors (accelerometer, gyroscope, magnetometer, light sensor, pedometer), the camera and microphone, network, deep linking, haptics, and battery APIs, interactive maps with markers and polylines, and push notifications. You'll then implement complete authentication flows - protected routes, email/password login, Google and GitHub OAuth, and third-party providers like Better Auth and Clerk - and learn EAS development builds and app variants to get your app onto real devices.To tie it all together, you'll build real-world capstone projects, including a Weather app (Expo Location, live weather/forecast/AQI APIs, custom hooks, and dynamic backgrounds), a Pinterest-style Pixabay wallpaper app (search, color & category filters, detail modals, and image downloads), and a standout AI Story Generator that uses the AI SDK and OpenRouter to generate stories and images from a single prompt - routing requests to models like OpenAI, Gemini, and Claude with structured, Zod-validated output, plus local storage and dark mode.Throughout the course you'll also cement every concept with hands-on mini-projects, including a Profile Card Gallery, a Pokédex app, a Notes Buddy storage app, a News Feed reader, a Tilt-the-Ball sensor game, a Profile Pic Creator, and a Reminder Buddy notifications app.By the end, you won't just understand Expo - you'll have built a portfolio of real apps (including an AI-powered one) and the confidence to design, build, and ship your own mobile products. Enroll now and start building.

Complete beginners to mobile development,Web developers (React/JavaScript),Students and self-taught coders,Working professionals and freelancers,Anyone who wants to build real-world mobile apps

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11 Ads Platforms in 1 Course 2026: Learn Paid Advertising!
Published 7/2026
Created by Tanmoy Das
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Level: Expert | Genre: eLearning | Language: English | Duration: 460 Lectures ( 29h 23m ) | Size: 21.1 GB

Ultimate Ads Mastery: Unlock Google Ads, LinkedIn Ads, Meta Ads, TikTok Ads, X Ads, Snapchat Ads, Pinterest Ads & More!



What you'll learn
Platform-Specific Ad Formats: Master ad formats like search ads on Google Ads, video ads on TikTok Ads, and promoted pins on Pinterest Ads.
Campaign Goal Setting: Define SMART objectives for Meta Ads, LinkedIn Ads, and Microsoft Ads, targeting brand awareness, traffic, or conversions.
Audience Targeting Techniques: Learn precise targeting on Snapchat Ads, Reddit Ads, and ShareChat Ads using demographics, interests, and behaviors.
Creative Ad Development: Create compelling visuals and copy for TikTok Ads, Meta Ads, and Quora Ads tailored to platform-specific audiences.
Budget and Bidding Strategies: Optimize budget allocation and bidding (e.g., CPC, CPM) for Google Ads, X Ads, and Pinterest Ads to maximize ROI.
Campaign Structure Design: Build effective campaign hierarchies for LinkedIn Ads, Microsoft Ads, and Reddit Ads with targeted ad sets.
Performance Metrics Tracking: Identify KPIs like click-through rates for Meta Ads, impressions for Snapchat Ads, and conversions for Google Ads.
Performance Analysis: Evaluate hypothetical results for Google Ads, Meta Ads, and X Ads to propose data-driven optimizations.
Multi-Platform Integration: Develop cohesive strategies combining Meta Ads, TikTok Ads, and LinkedIn Ads for unified campaigns.
Data-Driven Optimization: Analyze campaign results on X Ads, Google Ads, and Snapchat Ads to improve performance and ROI.
Platform Best Practices: Apply strategies like keyword targeting for Microsoft Ads, visual storytelling for Pinterest Ads, and community focus for Reddit Ads.
Creative Optimization: Test and refine creatives on TikTok Ads, ShareChat Ads, and Quora Ads based on performance data.
Ad Manager Proficiency: Navigate Google Ads Dashboard, Meta Ads Manager, and LinkedIn Campaign Manager for seamless campaign setup.

Requirements
Basic Digital Marketing Knowledge: Understanding of core marketing concepts like targeting and campaign goals to grasp Google Ads and Meta Ads strategies.
Reliable Computer and Internet: Access to a computer with a stable internet connection to use platforms like Microsoft Ads Manager and TikTok Ads Manager.
Social Media Familiarity: Basic experience with platforms like Snapchat, Pinterest, and Reddit to understand their audience for Snapchat Ads and Reddit Ads.
English Proficiency: Ability to read and write in English to follow course content and create ad copy for LinkedIn Ads and Quora Ads.
Design Tool Access: Accounts on free tools like Canva or Adobe Express to design creatives for Pinterest Ads and TikTok Ads.
No Prior Ad Experience Required: No previous experience with Google Ads, LinkedIn Ads, or other platforms is needed, as the course covers fundamentals.
Time Commitment: Availability to dedicate 5-10 hours weekly to study and tasks, including mock campaign setups for Meta Ads and Snapchat Ads.
Analytical Skills: Willingness to interpret data and metrics, essential for optimizing Microsoft Ads and ShareChat Ads campaigns.
Google Account: A Google account for Google Docs and Sheets to complete assignments, such as campaign plans for Google Ads and X Ads.
Creative Enthusiasm: Interest in crafting engaging content for Reddit Ads and TikTok Ads to meet platform-specific creative demands.

Description
Hi Guys,

Welcome to my course11 Ads Platforms in 1 Course 2026: Learn Paid Advertising!

In my courseyou will learn everything about all Paid Ads platforms. I have created video lessons on every campaign and every feature of Google Ads, Microsoft Ads, Meta Ads, LinkedIn Ads, Tiktok Ads, X Ads, Pinterest Ads, Snapchat Ads, Quora Ads, Reddit Ads, ShareChat Ads. You will get to see the real practical implementation of how to create each and every campaign and how to use every feature of this product.

This is the most detailed course on all Paid Ads you will ever find on the internet. I have created different sections based on different social media ads platforms - Google Ads, Microsoft Ads, Meta Ads, LinkedIn Ads, Tiktok Ads, X Ads, Pinterest Ads, Snapchat Ads, Quora Ads, Reddit Ads, ShareChat Ads. I have gone in-depth into explaining the concept of the each feature and how to practically implement it.

This course will give you a 100% understanding of all Paid Ads platforms and after going through this course you will be capable of applying these concepts in building your own online business or handling Google Ads, Microsoft Ads, Meta Ads, LinkedIn Ads, Tiktok Ads, X Ads, Pinterest Ads, Snapchat Ads, Quora Ads, Reddit Ads, ShareChat Ads for your clients.

At such a low price, you're going to get405 detailed video lessons, 48 assignments, 2 practice tests & 1 quiz. A complete access to ourstudent discussion forum, and the ability toask me any questions you may have as you progress through the course.

On top of all that, you getlifetime access and a30 day, 100% money back guarantee!

Topics you will learn in this course

Google Ads
Google Ads Overview

Keyword Research

Google Ads Formats

Google Ads Bidding Strategies

Google Display Network

Google Conversion Tracking

Google Ads Remarketing

Google Video Ads

Google Ads Certification

Microsoft Ads
Microsoft Ads Overview

Introduction to Keywords

Microsoft Ads Formats + Extensions

Microsoft Ads Bidding Strategies

Microsoft Ads Audience Network

Microsoft Ads UET Tag Setup

Microsoft Ads Remarketing

Microsoft Shopping Ads

Microsoft Ads Mobile App Campaign

Microsoft Ads Shared Library

Microsoft Ads Certification

Facebook Ads
Facebook Marketing

Facebook Ads Basics

Facebook Ads Campaign Creation

Facebook Pixel Setup

Facebook Ads Bidding Strategies

Facebook Ads Custom Audiences

Facebook Ads Lead Gen Campaign

Facebook Ads Sales Campaign

Facebook Ads Certification

LinkedIn Ads
LinkedIn Ads Overview

LinkedIn Ads Formats

LinkedIn Ads Bidding Strategies

LinkedIn Ads Audience Templates

LinkedIn Ads Conversion Tracking

LinkedIn Ads Retargeting

LinkedIn Ads Lead Gen Campaign

LinkedIn Ads Dynamic Ad Campaign

LinkedIn Ads Carousel Image Ad Campaign

LinkedIn Ads Conversation Ad Campaign

LinkedIn Ads Document Ad Campaign

LinkedIn Ads LinkedIn Video Ad Campaign

LinkedIn Ads Event Ad Campaign

LinkedIn Ads Direct Sponsored Content Single Image Ad Campaign

How to use Reports in LinkedIn Ads

LinkedIn Ads Billing Center

LinkedIn Ads Business Manager

LinkedIn Ads Certification

Tiktok Ads
Tiktok Ads Overview

How to Open A TikTok Ads Account

Auction Basics

TikTok Ads Manager Overview

Campaign Structure

Campaign Level

Ad Group: Customer Targeting

Ad Level

Lead Gen Campaign Creation

Website Traffic Campaign Creation

Audience Manager, Comments

Creative Section

Automated Rules

Leads, Recommendation Center,

Custom Reports

Audience Insights, Comment Insights, Video Insights

Attribution Analytics, Creative Inspirations

Account Setup, Brand Safety Hub, Finance, Documents

X Ads
X Ads Overview

5 Reasons Why You Should Use X Ads

X Ads Structure

How To Set Up Your X Ads Account

X Campaign Objectives

Setting Up A X Ad Campaign To Drive Traffic

Ad Group Details & Bid Types

Audience Demographics - Gender, Age & Location

Ad Group - Devices

Targeting Features

Placements

X Ad Creative

Setting Up A X Ad Campaign To Get More Reach

How To Set Up X Conversion Tracking

X Custom Audiences - Lists

X Custom Audiences - Website Activity

Pinterest Advertising
Pinterest Ads Overview

Why is Pinterest Advertising Unique?

Pinterest Ads Account Structure

How To Set Up Your Pinterest Ads Account

Pinterest Campaign Objectives

Setting Up A Pinterest Ad Campaign To Drive Brand Awareness

Ad Group Details & Bid Types

Targeting Details

Pinterest Ad Creative

Performance+ Campaign Creation

Video Campaign Creation

Pinterest Conversion Tracking

Pinterest Custom Audiences

Pinterest Business Manager

Pinterest Billing

Pinterest Ad Reports

Ad Recommendations

Ad Account History

Pinterest Analytics

Audience Insights

Conversion Insights

Pinterest Trends

Bulk Editor

SnapChat Ads
SnapChat Ads Overview, SnapChat Ads Formats, Where SnapChat Ads Appear

Why Run Ads On SnapChat

How To Sign Up For SnapChat Ads

SnapChat Ads Structure

SnapChat Ads Account Navigation

SnapChat Ads Campaign Objectives

How to Create Brand Awareness Campaign

How To Create Traffic Campaign

How To Create Leads Campaign

How To Create App Promotion Campaign

How To Create Sales Campaign

SnapChat Ads Events Manager

SnapChat Ads Audiences

SnapChat Ads Pixel, Apps, Catalogs

Snapchat Creative Library, Lens Folders, Create Lens & Filter

SnapChat Audience Insights, Reports, Campaign Lab

SnapChat Camera Kit, Developer Portal

SnapChat Business Dashboard, Billing, Public Profiles, Lens Creator Marketplace

Reddit Ads
Reddit Ads Overview, Reddit Ads Formats, Where Reddit Ads Appear

Why Run Ads On Reddit

How To Sign Up For Reddit Ads

Reddit Ads Structure

Reddit Ads Account Navigation

Reddit Ads Campaign Objectives

How to Create Brand Awareness Campaign

How To Create Website Traffic Campaign

How To Create Video View Campaigns

How To Create Conversion Campaigns

How To Create App Installs Campaign

Audience Manager

Events Manager

Report Manager

Campaign Import, Bulk Import

AI Copywriter, Ad Inspiration, Post Library

History, Brand Safety, Billing

Business Manager

ShareChat Ads
ShareChat Ads Overview, ShareChat Ads Formats, Where ShareChat Ads Appear

Why Run Ads On ShareChat

How To Sign Up For ShareChat Ads

ShareChat Ads Account Navigation

How to Create Brand Awareness Campaign

How To Create Consideration Campaign

How To Create Conversion Campaign

ShareChat Ads Reports

ShareChat Ads Event Manager

ShareChat Ads Target Audience

Quora Ads
Quora Ads Overview, Quora Ads Formats, Where Quora Ads Appear

Why Run Ads On Quora

How To Sign Up For Quora

Structure Of A Quora Ads Campaign

Quora Ads Campaign Objectives

How to Create Brand Awareness Campaign

How To Create Website Traffic Campaign

How To Create Video View Campaigns

How To Create Lead Gen Campaigns

How To Create Conversion Campaigns

How To Create App Installs Campaign

How To Set Up Conversion Tracking

Quora Ads Custom Audiences

Quora Ads Lead Gen Form

Quora Ads Reporting

Thank you so much for checking out my course. I look forward to seeing you in the course. So wait no more!

Click on the 'Buy now' button and join my course today!! Also check out my other courses!!

Who this course is for
Aspiring Digital Marketers: Beginners aiming to start a career in digital marketing by mastering Google Ads and Meta Ads campaigns.
Small Business Owners: Entrepreneurs seeking to promote their businesses using cost-effective Pinterest Ads and Microsoft Ads.
Marketing Professionals: Marketers looking to enhance their expertise with LinkedIn Ads and Quora Ads for B2B and niche targeting.
Freelancers: Independent professionals wanting to offer TikTok Ads and Reddit Ads management services to clients.
Content Creators: Influencers or creators interested in boosting visibility through Snapchat Ads and X Ads to grow their audience.
Nonprofit Marketers: Professionals at nonprofits looking to increase awareness or donations using budget-friendly Quora Ads and Snapchat Ads.
Business or Marketing Students: College students seeking hands-on experience with Microsoft Ads and LinkedIn Ads to strengthen their resumes.
Social Media Enthusiasts: Hobbyists passionate about mastering advertising on TikTok Ads and Reddit Ads to understand platform dynamics.
Career Switchers: Individuals transitioning to marketing roles who need practical skills in Google Ads and Pinterest Ads.
E-commerce Sellers: Online retailers aiming to drive sales with targeted Meta Ads and ShareChat Ads campaigns.

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1031 Exchange Strategy for Landlords Selling Rental Property
Published 7/2026
MP4 | Video: h264, 3840x2160 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 5h 53m | Size: 23.98 GB

Sell vs refinance, 1031 rules, replacement property, boot, deadlines, and rental property tax planning



What you'll learn
Compare selling, refinancing, and using a 1031 exchange before selling appreciated rental property.
Estimate how capital gains tax, depreciation recapture, debt, and boot can affect a rental property sale.
Choose replacement property using cash flow, appreciation, risk, management burden, and investor goals.
Plan around 45-day identification, 180-day closing, backup properties, financing, and common 1031 mistakes.
Use 1031 strategy to trade up, diversify, consolidate, reduce landlord workload, or plan for retirement.
Ask better questions before working with a qualified intermediary, CPA, attorney, lender, or real estate team.

Requirements
Basic understanding of what a 1031 exchange is.
Best for students who own, are selling, or are considering selling rental or investment property.
No tax, legal, financial, or investment advice is provided. Students should consult their own professionals.
A calculator or spreadsheet is helpful for applying the examples and planning worksheets.

Description
Are you a landlord or real estate investor thinking about selling an appreciated rental property and wondering whether a 1031 exchange is actually the right move?

A 1031 exchange can help investors defer capital gains tax, keep more equity invested, and move into replacement property. But a 1031 exchange is not automatically the best answer for every property owner. Sometimes selling makes sense. Sometimes refinancing is better. Sometimes exchanging creates the most value, but only if the replacement property, debt, boot, deadlines, and tax strategy are planned before the transaction controls the timeline.

This course is designed for landlords and real estate investors who already understand the basic idea of a 1031 exchange and want a more practical, intermediate-level strategy framework. Instead of only teaching definitions, this course helps you think through real investor decisions: should you sell, refinance, or exchange; what should you exchange into; how do you avoid common 1031 mistakes; and how can the exchange support cash flow, portfolio growth, retirement income, or long-term family planning?

You will learn how to compare exit options, evaluate capital gains tax and depreciation recapture concerns, understand boot and buying power, plan around the 45-day identification period and 180-day closing deadline, choose replacement property more strategically, and avoid rushing into a property that qualifies legally but does not fit your financial goals.

This course is especially useful for landlords, Airbnb owners, commercial property owners, mixed-use property owners, and investors with appreciated real estate who want to make smarter decisions before selling. It is also helpful for high-income professionals and long-term investors who want to use rental property and 1031 exchanges as part of a larger real estate tax and wealth strategy.

Educational use only. This course does not provide tax, legal, financial, investment, real estate, or 1031 exchange advice. Always consult your own qualified intermediary, CPA, attorney, lender, financial advisor, and real estate professionals before making decisions.

This matches your course source because the course is built around intermediate strategy: when to exchange, what to exchange into, replacement strategy, execution mistakes, retirement planning, tax planning, and legacy planning.

Who this course is for
Landlords selling appreciated rental property and considering a 1031 exchange.
Real estate investors comparing sell vs refinance vs exchange before making a major property decision.
Rental, Airbnb, commercial, or mixed-use property owners worried about capital gains tax and depreciation recapture.
Investors looking for replacement property strategy beyond basic 1031 exchange rules.
Property owners who want to trade up, diversify, consolidate, reduce management work, or plan retirement income.
High-income professionals using rental property and 1031 exchanges as part of a long-term wealth strategy.


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FastAPI: Crea APIs eficientes con Python
Last updated 5/2026
Created by Fernando Herrera, {d/t} - DevTalles, Ricardo Cuéllar
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Level: All Levels | Genre: eLearning | Language: Spanish + subtitle | Duration: 317 Lectures ( 36h 16m ) | Size: 32.8 GB

Pydantic, Bases de datos, SQLAlchemy, SQLModel, JWT, Funciones síncronas y asíncronas, middlewares, alembic y más



What you'll learn
Conocer las bases del Framework FastAPI
Crear APIs con FastAPI
Usar FastAPI con SQLAlchemy
Usar FastAPI con SQLModel
Validaciones con Pydantic
FastAPI Middlewares, Queryparams, seguridad con JWT
Migraciones con Alembic

Requirements
Python básico
SQL Básico
Control de versiones con git

Description

FastAPI: Crea APIs eficientes con Python
Bienvenidos alcurso de FastAPI, este curso tiene como objetivo llevar tus conocimientos dePython al área dedesarrollo de APIs, llevando tus conocimientosdesde cero hasta un nivel competitivo en el mercado laboral. Este curso te llevará desde las bases de FastAPI hastaconstruir APIs listas para ser desplegadas utilizando únicamente elframework FastAPI.

El curso cuenta consecciones introductorias al framework,mini aplicaciones para explicar conceptos, y secciones en las cuales vamosconstruyendo una API conforme aprendemos y aplicamos lo aprendido.

También cuentas con unasección introductoria a Python para que puedas refrescar conceptos o, si te aventuraste a ir directo al framework, también puedas tomar losconocimientos más esenciales del lenguaje.

FastAPI es uno de los frameworks más poderosos y usados para la construcción de APIs de forma rápida y eficiente. Con él puedestransformar una idea en una API lista para ser consumida por un servicio o un frontend en muy poco tiempo, porque la velocidad de desarrollar un CRUD y funciones personalizadas nos da una ventaja competitiva en el mercado.

Lo mejor es que FastAPI te permite crearAPIs reales y eficientes: desde unsimple CRUD hasta unsistema de e-commerce o unared social completa. Esseguro, escalable y cuenta con unaenorme comunidad que te respalda en cada paso, además de que esta en constante crecimiento.

En pocas palabras:aprender FastAPI es una inversión en tu futuro como programador. Te dará las herramientas paracrear proyectos profesionales,abrir más oportunidades laborales ydiferenciarte en un mercado que cada vez demanda más desarrolladores con estas habilidades.

¿Qué aprenderás en el curso?
Estos son algunos de los temas que veremos

Introducción a FastAPI

Tipados y validaciones

Pydantic

Validación de parámetros y query params

Base de datos

SQLAlchemy

Arquitectura y modularización

Dependencias

Seguridad y JWT

Funciones asíncronas y síncronas

Middlewares

SQLModel

Migraciones con Alembic

PostgreSQL

Despliegue en render

Y muchas cosas más.

Objetivo del curso
El objetivo principal es queconozcas y aprendas FastAPI para que puedasconstruir APIs completas para MVPs yproyectos rápidos con un solo framework, aplicandoestándares actuales del desarrollo profesional.

Cada sección fue pensada para queconozcas una parte del framework con ejemplos prácticos. En algunas secciones aplicamos todos los conocimientos y los plasmamos en unproyecto MVP.También al final de cada sección puedes encontrar un cuestionario para reforzar los conocimientos teóricos.

Resultados al finalizar
Al finalizar el curso estarás preparado para

Enfrentar proyectos reales con Python

Postular a empleos que usen FastAPI

Ser parte esencial de un equipo de desarrollo

O inclusolanzar tus propios proyectos.

¡Te espero en el curso y deseo muchoéxito en tu trayectoria profesional!

Who this course is for
Desarrolladores en Python principiantes e intermedios
Desarrolladores con interés en Python
Desarrolladores con interés en desarrollo backend
Interesados en aprender a crear APIs con FastAPI
Desarrolladores que han manejado algún otro framework y quieren interactuar con FastAPI
Personas que deseen conocer las bases de FastAPI
Personas que quieren una guía de uso de FastAPI
Personas que necesiten aprender FastAPI fácil y rápido

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Scalable Flutter: Supabase, Clean Architecture & Riverpod
Published 7/2026
Created by Sangwook Cho
MP4 | Video: h264, 3840x2160 | Audio: AAC, 44.1 KHz, 2 Ch Level: All Levels | Genre: eLearning | Language: English | Duration: 165 Lectures ( 20h 34m ) | Size: 25.9 GB

Master professional Flutter: Build a scalable community app with Clean Architecture, Supabase, Riverpod, and Monorepo.



What you'll learn
Practical Clean Architecture: Learn to design robust, scalable, and testable app structures by separating code into Presentation, Domain, and Data layers.
Fullstack with Supabase: Build and integrate Authentication, Database, Storage, and Realtime features using Supabase without writing complex backend
State Sync with Riverpod & Event Bus: Master advanced state management by implementing an Event Bus architecture to keep data consistent across multiple screens
Building a Monorepo Environment: Experience professional development by decoupling features into reusable packages to maximize code efficiency.
Advanced Features: Implement industry-standard features like debounced reactive search, universal infinite scroll, and realtime notification systems.

Requirements
Basic Flutter Knowledge: Ability to use basic widgets and a foundational understanding of asynchronous programming (async/await).
Dart Fundamentals: Familiarity with basic OOP concepts like classes and inheritance.
State Management Exposure: Experience with any state management solution (Provider, Riverpod, Bloc, GetX, etc.) is helpful. Even if you are new to Riverpod, basic principles will carry you through.
Basic SQL CRUD: A basic understanding of reading/writing data is recommended. Complex queries and RLS policies will be covered step-by-step in the course.
A Growth Mindset: You don't need to be an expert. If you have the will to learn scalable architecture, you are ready!

Description

"Go beyond Flutter basics and become an architect capable of designing professional, production-ready apps."
Are you ready to move past simple Counter or TODO apps and tackle the complex challenges of real-world services? If you've experienced the frustration of code becoming tangled as you add features, or felt the fragility of your app with every small change, this course is designed for you.

This is more than just a tutorial on building an app; it is a deep dive intoproven development methodologies for creating scalable and maintainable applications that stand the test of time.

Why This Course Matters in the AI Era
In an era where AI can generate code snippets in seconds, what is the role of a professional developer?

Beyond Snippets: AI is excellent at writing functions, but it cannot yet design a complex, interconnected system. UnderstandingClean Architecture means you know how to organize those AI-generated pieces into a scalable whole.

The Architect's Advantage: As AI lowers the barrier to entry for coding, the market will be flooded with "fragmented code." The true value will lie in theArchitect-the one who can manage technical debt, ensure maintainability, and design a robust "vessel" (Architecture) to hold the logic.

Future-Proof Your Career: This course evolves you from a "coder" who follows instructions to an"architect" who masters AI as a tool, rather than being replaced by it.

The Three Pillars of This Course
We will build a high-performance'Community Board' app from scratch, grounded in three essential technical pillars for large-scale projects

Robust Architecture (Clean Architecture): Bring order to chaotic code. Learn to separate concerns into distinct layers, creating a structure that is easy to test, maintain, and evolve.

Modern Backend (Supabase): Bypass complex server setups. Leverage Supabase-a powerful Backend-as-a-Service-to implement databases, authentication, and realtime features in a fraction of the time.

Efficient State Management (Riverpod & Event Bus): Master Riverpod, the industry standard for Flutter, and combine it with a Global Event Bus architecture to synchronize data across multiple screens with elegance and precision.

Key Learning Features
Build a Real-World Community App: Implement industry-standard features including Authentication, Post CRUD, Real-time likes/comments, Profile management, and Reactive search.

Professional Monorepo Setup: Learn to decouple features into independent packages to maximize code reusability and manage large-scale projects like a pro.

Advanced Streams & Real-time Control: Master Supabase Realtime for instant data syncing and utilize advanced stream techniques like Debounce and timer-based input control for an optimized search experience.

The Essence of Scalability: Design an architecture so flexible that you could swap your state management tool without touching a single line of your core business logic.

Curriculum Roadmap
Foundations: Master the VS Code environment and essential productivity tools to eliminate boilerplate code.

Architecture: Establish core principles of Clean Architecture, focusing on the dependency rule and separation of concerns.

Infrastructure: Build a Monorepo environment and design a Supabase backend (SQL, RLS, Functions, and Triggers).

Development: Implement core features (Auth, Posts, Search) using Riverpod combined with a Global Event Bus.

Advanced: Deep dive into Supabase Realtime for live data detection and UI synchronization.

Next Level: Project review and a strategic look at how this architecture extends to other state management libraries.

Who is this course for?
Flutter developers who have built basic apps and are ready to tackle professional, production-ready architectures.

Developers struggling with maintenance as their projects grow and seeking "Clean Architecture" as a definitive solution.

Solo developers or startup engineers who want to launch high-performance apps quickly using Supabase (BaaS).

Job seekers looking to showcase "Scalable App Design" and "Monorepo Management" skills in their professional portfolio.

Prerequisites
Flutter & Dart Basics: You should be comfortable with basic widgets and have a foundational understanding of asynchronous programming (async/await).

State Management Exposure: Experience with any state management solution (Provider, Riverpod 2, BLoC, GetX, etc.) is helpful. Even if you are new to Riverpod, you will be able to follow along.

Basic SQL Knowledge: A basic understanding of reading/writing data is recommended. Complex database policies (RLS) and functions will be covered step-by-step.

Lecture Materials and Source Code Provided
High-quality PDF slides: PDF presentation materials containing key theories and architecture diagrams for each section are provided. (Download from the Resources tab for each section)

Final source code provided

Foundation Level: Complete code for productivity tools and core syntax (such as data_class) covered in Section 2 is provided.

Main Project: The monorepo structure and final implementation code for the entire community_board app starting in Section 4 is provided.

Links to the source code and usage instructions will be provided in detail in the first lecture of Sections 2 & 4.

Don't just learn 'how' to build; understand 'why' we design this way. Join me on this journey to elevate your development skills to the next level!

Who this course is for
Flutter developers who have built basic apps and are ready to tackle professional, real-world architectures.
Developers struggling with maintenance as code grows and seeking "Clean Architecture" as a solution.
Solo developers or startup engineers who want to launch high-performance apps quickly using Supabase (BaaS).
Those looking to master Riverpod by combining it with structured architecture rather than just simple state updates.
Students or job seekers who want to showcase "Scalable App Design" skills in their portfolio.

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Agentic AI Masters 2026: LangChain, LangGraph & CrewAI
Published 6/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 58h 8m | Size: 33 GB

Master Python to Production-Grade AI Agents: NLP, LLMs, RAG, LangGraph, CrewAI, n8n & Multi-Agent Systems



What you'll learn
Build a solid foundation in Python programming to effectively implement AI concepts and applications.
Understand the complete pipeline of Natural Language Processing, from data preprocessing to model deployment.
Learn how transformer models revolutionize NLP tasks, and how to leverage them for various applications.
Explore the essentials of Large Language Models (LLMs) and their applications in generative tasks.
Gain hands-on experience with Retrieval-Augmented Generation (RAG) and Langchain for building advanced AI applications.
Develop skills in crafting effective prompts to optimize model performance and achieve desired outputs.
Learn how to utilize vector databases for efficient storage and retrieval of embeddings in AI projects.

Requirements
Basic knowledge on Machine Learning is beneficial but not mandatory

Description
TheAgentic AI Masters 2026 is a complete, end-to-end mastery program designed to take you from Python fundamentals all the way to building autonomous, production-ready AI agents.

This comprehensive course covers the entire modern AI stack. You will start with strong Python foundations and progress through classical NLP techniques (tokenization, stopwords, n-grams, Bag of Words, TF-IDF, POS tagging, NER), word embeddings (Word2Vec CBOW & SkipGram, GloVe, FastText), and deep learning architectures including ANNs, CNNs, RNNs, LSTMs, GRUs, and bi-directional models.

You will then master the revolutionaryTransformer architecture (encoder-only, decoder-only, and full encoder-decoder) and dive deep into Large Language Models - understanding tokens, context windows, prompt engineering, prompt tuning, and working with leading models from OpenAI, xAI, and local deployment using Ollama.

The course features extensive coverage ofRetrieval Augmented Generation (RAG), vector databases vs vector indexes, advanced RAG architectures, evaluation metrics, and RAG assessment frameworks. You will also learn model fine-tuning techniques and how to deploy generative AI applications in production.

In theAgentic AI specialization phase, you will master

- LangChain for building intelligent chains and agents

- LangGraph for creating reliable, stateful, controllable multi-agent workflows

- CrewAI for orchestrating role-based collaborative AI teams

- Low-code automation using n8n

- Implementation of guardrails for safe and reliable agents

- Advanced multi-agent systems design and orchestration

Throughout the program, you will work on multiple real-world projects that simulate industry use cases - from intelligent document Q&A systems and automated research agents to smart assistants, workflow automation, and complex multi-agent solutions.

By the end of this course, you will have the confidence and practical skills to design, develop, evaluate, and deploy sophisticated agentic AI systems that can reason, plan, use tools, and collaborate - making you job-ready for the rapidly growing demand in the agentic AI space.

Whether you are a developer, data scientist, AI engineer, or tech professional looking to future-proof your career,Agentic AI Masters 2026 delivers the deepest, most practical, and up-to-date education in building the next generation of AI agents.

Who this course is for
Individuals passionate about AI and ML who want to expand their knowledge and skills in generative AI applications.
Professionals looking to enhance their expertise in building and deploying generative AI models
Developers interested in integrating advanced AI capabilities into their applications and learning about the deployment and optimization of AI models.


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Econometrics for Finance, Economics & Data Science
Published 7/2026
Created by Piyush Dave
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Level: All Levels | Genre: eLearning | Language: English | Duration: 60 Lectures ( 26h 1m ) | Size: 30.5 GB

Master regression, time series, forecasting, financial econometrics, and real-world data analysis with practical example



What you'll learn
Understand econometric concepts, statistical foundations, and regression analysis from beginner to advanced level.
Build, interpret, and validate simple and multiple regression models using real-world economic and financial datasets.
Detect and solve econometric problems including heteroscedasticity, autocorrelation, and multicollinearity.
Apply time series, financial econometrics, and forecasting techniques to practical business, finance, and research problems.

Requirements
No prior knowledge of econometrics is required. Basic mathematics and statistics are helpful but not mandatory. Anyone interested in data analysis, economics, finance, or research can follow this course. Familiarity with Excel is beneficial, and examples using R/Python are optional.

Description
Econometrics is one of the most valuable analytical skills for students, researchers, economists, finance professionals, and data analysts. This comprehensive course is designed to help you master econometric techniques from the fundamentals to advanced applications through a practical and structured learning approach.

You'll begin by understanding the statistical foundations required for econometrics before moving into simple and multiple regression analysis, hypothesis testing, model building, and interpretation of results. As the course progresses, you'll learn how to identify and solve common econometric challenges such as multicollinearity, heteroscedasticity, and autocorrelation.

The course also introduces time series econometrics, forecasting techniques, volatility modeling, financial econometrics, and asset pricing concepts that are widely used in academia, quantitative finance, investment research, and business analytics.

Rather than focusing only on mathematical theory, this course emphasizes practical understanding and real-world applications. Every concept is explained step by step using intuitive examples, enabling you to confidently analyze data and interpret econometric models.

By the end of this course, you'll be able to build and evaluate regression models, perform statistical analysis, forecast future trends, interpret econometric results, and apply these techniques to economics, finance, business, and research projects.

Whether you're preparing for university examinations, conducting academic research, working in finance, pursuing a career in data analytics, or simply looking to strengthen your quantitative skills, this course provides the complete foundation you need.

What You'll Learn

Master econometric concepts from beginner to advanced level.

Build and interpret simple and multiple regression models.

Perform hypothesis testing and evaluate model performance.

Diagnose and correct multicollinearity, heteroscedasticity, and autocorrelation.

Apply time series analysis and forecasting techniques.

Understand financial econometrics and volatility modeling.

Analyze real-world economic and financial datasets.

Gain practical skills applicable in research, finance, business analytics, and data science.

Who this course is for
This course is designed for undergraduate and postgraduate students, MBA and economics learners, finance professionals, data analysts, researchers, aspiring data scientists, CFA/FRM candidates, and anyone who wants to master econometrics for academic, business, or financial applications. It is suitable for both beginners and professionals looking to strengthen their analytical skills.

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Deep Learning Masterclass with TensorFlow 2 Over 20 Projects
Last updated 2/2026
Created by Neuralearn Dot AI
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Level: All Levels | Genre: eLearning | Language: English + subtitle | Duration: 204 Lectures ( 58h 28m ) | Size: 34.3 GB

Master Deep Learning with TensorFlow 2 with Computer Vision,Natural Language Processing, Sound Recognition & Deployment



What you'll learn
The Basics of Tensors and Variables with Tensorflow
Basics of Tensorflow and training neural networks with TensorFlow 2.
Convolutional Neural Networks applied to Malaria Detection
Building more advanced Tensorflow models with Functional API, Model Subclassing and Custom Layers
Evaluating Classification Models using different metrics like: Precision,Recall,Accuracy and F1-score
Classification Model Evaluation with Confusion Matrix and ROC Curve
Tensorflow Callbacks, Learning Rate Scheduling and Model Check-pointing
Mitigating Overfitting and Underfitting with Dropout, Regularization, Data augmentation
Data augmentation with TensorFlow using TensorFlow image and Keras Layers
Advanced augmentation strategies like Cutmix and Mixup
Data augmentation with Albumentations with TensorFlow 2 and PyTorch
Custom Loss and Metrics in TensorFlow 2
Eager and Graph Modes in TensorFlow 2
Custom Training Loops in TensorFlow 2
Integrating Tensorboard with TensorFlow 2 for data logging, viewing model graphs, hyperparameter tuning and profiling
Machine Learning Operations (MLOps) with Weights and Biases
Experiment tracking with Wandb
Hyperparameter tuning with Wandb
Dataset versioning with Wandb
Model versioning with Wandb
Human emotions detection
Modern convolutional neural networks(Alexnet, Vggnet, Resnet, Mobilenet, EfficientNet)
Transfer learning
Visualizing convnet intermediate layers
Grad-cam method
Model ensembling and class imbalance
Transformers in Vision
Model deployment
Conversion from tensorflow to Onnx Model
Quantization Aware training
Building API with Fastapi
Deploying API to the Cloud
Object detection from scratch with YOLO
Image Segmentation from scratch with UNET model
People Counting from scratch with Csrnet
Digit generation with Variational autoencoders (VAE)
Face generation with Generative adversarial neural networks (GAN)
Sentiment Analysis with Recurrent neural networks, Attention Models and Transformers from scratch
Neural Machine Translation with Recurrent neural networks, Attention Models and Transformers from scratch
Intent Classification with Deberta in Huggingface transformers
Neural Machine Translation with T5 in Huggingface transformers
Extractive Question Answering with Longformer in Huggingface transformers
E-commerce search engine with Sentence transformers
Lyrics Generator with GPT2 in Huggingface transformers
Grammatical Error Correction with T5 in Huggingface transformers
Elon Musk Bot with BlenderBot in Huggingface transformers

Requirements
Basic Math
Access to an internet connection, as we shall be using Google Colab (free version)
Basic Knowledge of Python

Description

Deep Learningis one of the most popular fields in computer science today. It has applications in many and very varied domains. With the publishing of much more efficient deep learning models in the early 2010s, we have seen a great improvement in the state of the art in domains likeComputer Vision, Natural Language Processing, Image Generation, and Signal Processing.
Thedemand for Deep Learning engineers is skyrocketing and experts in this field arehighly paid, because of their value.However, getting started in this field isn't easy. There's so much information out there, much of which is outdated and many times don't take the beginners into consideration

In this course, we shall take you on an amazing journey in which you'll master different concepts with a step-by-step and project-based approach. You shall be usingTensorflow 2 (the world's most popular library for deep learning, and built by Google) andHuggingface.We shall start by understanding how to build very simple models (like Linear regression models forcar price prediction, text classifiers formovie reviews, binary classifiers formalaria prediction) using Tensorflow and Huggingface transformers, to more advanced models (like object detection models withYOLO, lyrics generator model withGPT2and Image generation withGANs)

After going through this course and carrying out the different projects, you will develop the skill sets needed to develop modern deep-learning solutions that big tech companies encounter.

You will learn:

The Basics of Tensorflow(Tensors, Model building, training, and evaluation)

Deep Learning algorithms likeConvolutional neural networks and Vision Transformers

Evaluation of Classification Models (Precision, Recall, Accuracy, F1-score, Confusion Matrix, ROC Curve)

Mitigating overfitting withData augmentation

Advanced Tensorflow concepts likeCustom Losses and Metrics, Eager and Graph Modes and Custom Training Loops, Tensorboard

Machine Learning Operations(MLOps) with Weights and Biases(Experiment Tracking, Hyperparameter Tuning, Dataset Versioning, Model Versioning)

Binary Classification withMalaria detection

Multi-class Classification withHuman Emotions Detection

Transfer learning with modern Convnets (Vggnet, Resnet, Mobilenet, Efficientnet) and Vision Transformers(VITs)

Object Detection with YOLO(You Only Look Once)

Image Segmentation withUNet

People Counting withCsrnet

Model Deployment (Distillation, Onnx format, Quantization, Fastapi, Heroku Cloud)

Digit generation withVariational Autoencoders

Face generation withGenerative Adversarial Neural Networks

Text Preprocessing for Natural Language Processing.

Deep Learning algorithms likeRecurrent Neural Networks, Attention Models, Transformers, and Convolutional neural networks.

Sentiment analysis with RNNs, Transformers, and Huggingface Transformers(Deberta)

Transfer learning with Word2vec and modern Transformers (GPT, Bert, ULmfit, Deberta, T5...)

Machine translation with RNNs, attention, transformers, and Huggingface Transformers(T5)

Model Deployment (Onnx format, Quantization, Fastapi, Heroku Cloud)

Intent Classification withDebertain Huggingface transformers

Named Entity Relation withRoberta in Huggingface transformers

Neural Machine Translation withT5 in Huggingface transformers

Extractive Question Answering withLongformer in Huggingface transformers

E-commerce search engine withSentence transformers

Lyrics Generator withGPT2 in Huggingface transformers

Grammatical Error Correction withT5 in Huggingface transformers

Elon Musk Bot withBlenderBot in Huggingface transformers

Speech recognition with RNNs

If you are willing to move astep further in your career, this course is destined for you and we are super excited to help achieve your goals!

This course is offered to you byNeuralearn. And just like every other course by Neuralearn, we lay much emphasis on feedback. Your reviews and questions in the forum will help us better this course. Feel free to ask as many questions as possible on the forum. We do our very best to reply in the shortest possible time.

Enjoy!!!

Who this course is for
Beginner Python Developers curious about Applying Deep Learning for Computer vision and Natural Language Processing
Deep Learning for Computer vision Practitioners who want gain a mastery of how things work under the hood
Anyone who wants to master deep learning fundamentals and also practice deep learning for computer vision using best practices in TensorFlow.
Computer Vision practitioners who want to learn how state of art computer vision models are built and trained using deep learning.
Natural Language Processing practitioners who want to learn how state of art NLP models are built and trained using deep learning.
Anyone wanting to deploy ML Models
Learners who want a practical approach to Deep learning for Computer vision, Natural Language Processing and Sound recognition

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Django: Crea aplicaciones web robustas con Python
Last updated 4/2026
Created by Fernando Herrera, {d/t} - DevTalles, Ricardo Cuéllar
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Level: All Levels | Genre: eLearning | Language: Spanish + subtitle | Duration: 395 Lectures ( 44h 31m ) | Size: 39.1 GB

Model View Template, Django ORM, Django Admin, Function y Class Based Views, Middlwares, Auth, Sessions, Signals y más.



What you'll learn
Conocer las bases del framework Django
Crear aplicaciones web con Django
Arquitectura Model View Template
Vistas con Function Based Views y Class Based Views
Django ORM, Relaciones, Django Admin, Middlewares, Sessions, etc.

Requirements
Python básico
Desarrollo web básico
SQL básico
No sé nesecita experiencia en programación pero es recomendado

Description

Django: crea aplicaciones web robustas con Python
Bienvenidos alcurso de Django, este curso tiene como objetivo llevar tus conocimientos dePython al área deAplicaciones Web, llevando tus conocimientosdesde cero hasta un nivel competitivo en el mercado laboral. Este curso te llevará desde las bases de Django hastaconstruir aplicaciones listas para ser desplegadas utilizando únicamente elframework Django.

El curso cuenta consecciones introductorias al framework,mini aplicaciones para explicar conceptos, y secciones en las cuales vamosconstruyendo un proyecto conforme aprendemos y aplicamos lo aprendido.

También cuentas con unasección introductoria a Python para que puedas refrescar conceptos o, si te aventuraste a ir directo al framework, también puedas tomar losconocimientos más esenciales del lenguaje.

Django es uno de los frameworks más poderosos y usados en el mundo del desarrollo web. Con él puedestransformar una idea en una aplicación lista para usar en muy poco tiempo, porque ya incluye lo esencial:manejo de usuarios, bases de datos, seguridad y hasta un panel de administración.

Lo mejor es que Django te permite crearproyectos reales: desde unsimple blog hasta unsistema de e-commerce o unared social completa. Esseguro, escalable y cuenta con unaenorme comunidad que te respalda en cada paso.

En pocas palabras:aprender Django es una inversión en tu futuro como programador. Te dará las herramientas paracrear proyectos profesionales,abrir más oportunidades laborales ydiferenciarte en un mercado que cada vez demanda más desarrolladores con estas habilidades.

¿Qué aprenderás en el curso?
Estos son algunos de los temas que veremos

Model View Template (MVT)

URLs

Views

Templates

Modelos y bases de datos

Relaciones entre modelos

Django ORM

Django Admin

Filtros, búsquedas y paginación

Signals

Class Based Views

Function Based Views

Middlewares

Autenticación y permisos de usuarios

Sessions

Autenticación y permisos de usuarios desde código

Subida de archivos

Content Types

Context Processors

Y muchas cosas más.

Objetivo del curso
El objetivo principal es queconozcas y aprendas Django para que puedasconstruir aplicaciones web completas para MVPs yproyectos rápidos con un solo framework, aplicandoestándares actuales del desarrollo profesional.

Cada sección fue pensada para queconozcas una parte del framework con ejemplos prácticos. En algunas secciones aplicamos todos los conocimientos y los plasmamos en unproyecto MVP: una plataforma de cursos en línea, partiendo desde cero hasta tener elMVP terminado.

Resultados al finalizar
Al finalizar el curso estarás preparado para

Enfrentar proyectos reales con Python

Postular a empleos que usen Django

Ser parte esencial de un equipo de desarrollo

O inclusolanzar tus propios proyectos, como lo hicieronInstagram, Spotify o Pinterest

¡Te espero en el curso y deseo muchoéxito en tu trayectoria profesional!

Who this course is for
Desarrolladores en Python principiantes e intermedios
Desarrolladores web con interés en Python
Desarrolladores principiantes en desarrollo web
Interesados en aprender a crear aplicaciones web completas con un solo framework
Personas curiosas e interesadas en aprender un framework fácil y completo
Desarrolladores que han manejado algún otro framework y quieren interactuar con Django
Personas que deseen conocer las bases de Django

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Unity 3D Defence and 3 Draw Mechanic Games Development
Published 6/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Language: English + subtitle | Duration: 34h 50m | Size: 25.44 GB

Build a 3D defence game from scratch and 3 draw-mechanic games. Learn core systems and scalable game architecture.



What you'll learn
Full development of 3D mobile games from scratch
Implementation of various gameplay mechanics
Practical project and workflow management
Deep understanding of a specific reusable game mechanic system

Requirements
A minimum intermediate level of Unity and game development knowledge is required.

Description "This course involves the use of artificial intelligence."

DEFENCE GAME SECTION

Tower defence is one of the most popular and widely played genres in the mobile gaming market, with millions of downloads across successful titles.

In this course, we build a complete3D defence game from scratch. All assets, models, and environment elements used in the project are personally created. When requirements are met, full source code access is provided. Please refer to the preview videos for a detailed overview.

Key Features Covered in the Course
- Main Menu System

- Level Selection System

- Audio Controls (Music & SFX Toggle System)

- Multi-language system using file-based architecture

- Loading / Scene transition system

- Special abilities system (enemy freeze, slow motion, mass repair, mass upgrade)

- Wave and attack system

- Object pooling system (bullets, effects, sounds) for optimal performance

- In-game shop system for turret placement

- And many more advanced systems

Turret System Features
- Turret placement system

- Upgrade system

- Repair system

- Sell system

- Radar detection system

- Health system

- Environmental interaction system

- Type-based behaviour system (Laser and Radiation turrets)

All of these systems are implemented step by step in full detail throughout the course.

Assets Included
- 8 different turret types (including firearms, laser, and radiation weapons)

- 7 different enemy types (human characters, ranged attackers, and standard enemies)

- Full environment assets (roads, barriers, environmental props)

- Additional supporting models and assets

- Complete UI systems for main menu and in-game interface

This course is designed to be a comprehensive and practical resource for serious learners who want to build real-world game systems.

Before purchasing, please make sure to watch all preview videos, as they contain important demonstrations and explanations.

Since learners may have different levels of experience, some approaches may differ from what you are familiar with. In game development, there are usually multiple valid solutions for any given system. This course is structured forintermediate-level developers, and you are free to modify or improve the systems as needed.

3 DRAW MECHANIC GAMES SECTION
In this section, we build a highly popular and widely downloadeddraw-based game mechanic system from scratch.

We develop both2D and 3D implementations, giving you a significant advantage in understanding cross-dimensional game logic.

The draw-line mechanic we build is designed as aflexible and reusable system. The primary goal of this course is to teach the core architecture behind this mechanic so you can reuse it to build an unlimited number of games based on your own ideas and creativity.

By thinking beyond the course structure, you will be able to generate highly scalable game concepts using the same core system.

It is strongly recommended to follow the lessons step by step without skipping, as this will significantly reduce the chance of errors and misunderstandings. The system is explained in a clear, minimal, and structured way to ensure full comprehension.

Once the core architecture is understood, we build the system completely from scratch. Depending on specific conditions, you will also gain access to full source code and premium versions of the completed projects.

How You Can Use This System
- Publish your own games

- Improve your game development skills

- Build a professional portfolio

- Use it as a reusable base system for future projects

This course is intended to be a valuable resource for anyone who is serious about game development.

Please make sure to watch all preview videos before enrolling, as they include important demonstrations and course structure explanations.

As learners have different experience levels, some techniques may differ from what you are used to. In game development, multiple implementation approaches are always possible. The course is designed forintermediate-level understanding, and you are encouraged to adapt or improve the systems according to your needs.

THE ORIGINAL VIDEO NARRATION AND EXPLANATION LANGUAGE OF THIS COURSE IS TURKISH. ALL VIDEOS ARE VOICED USING ARTIFICIAL INTELLIGENCE. THERE MAY BE ERRORS OR MISREPRESENTATIONS CAUSED BY TRANSLATION. PLEASE CONSIDER THIS BEFORE MAKING YOUR PURCHASE DECISION.

Who this course is for
Anyone who wants to build games from scratch
Developers aiming to generate income through game development
Individuals who want to improve their Unity and gameplay programming skills


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Build Agentic AI Apps with OutSystems ODC Using RAG
Published 7/2026
Created by Ankit Gangrade
MP4 | Video: h264, 3840x2160 | Audio: AAC, 44.1 KHz, 2 Ch Level: All Levels | Genre: eLearning | Language: English | Duration: 55 Lectures ( 9h 26m ) | Size: 20.2 GB

Master Agentic AI using OutSystems ODC, Azure AI Search & a production-ready RAG application: English



What you'll learn
Learn how enterprise AI applications are built using OutSystems ODC and Azure AI.
Build a real-world AI Knowledge Assistant using Retrieval-Augmented Generation (RAG).
Understand Agentic AI concepts and enterprise AI architecture.
Integrate Azure AI Search with OutSystems ODC.
Design AI applications with human handoff and support workflows.

Requirements
Basic computer skills
No prior knowledge of AI, RAG, or Azure AI Search is required.
No prior experience with OutSystems ODC is required.

Description
Everyone is learning AI.

Very few are learning how to build AI applications that enterprises actually deploy.

Instead of spending hours writing prompts or creating another chatbot, you'll build a production-style AI application usingOutSystems ODC, Azure AI Search, Agentic AI, and Retrieval-Augmented Generation (RAG).

Throughout this course, you'll developIntelliCampus-an Enterprise AI Knowledge Assistant that answers questions from real documents using a complete RAG pipeline. When the AI cannot confidently answer a question, it automatically creates a support ticket and hands the conversation over to a human administrator.

This is the same architectural approach used by modern enterprise AI copilots and intelligent knowledge assistants.

What You'll Build
Enterprise AI Knowledge Assistant

Production-ready RAG pipeline

Azure AI Search integration

Document upload, indexing, and retrieval

Grounded AI responses from enterprise knowledge

Role-based authentication and authorization

Student and Admin portals

AI-to-human handoff through a Support Ticketing System

What You'll Learn
OutSystems Developer Cloud (ODC)

Enterprise application architecture

Agentic AI fundamentals

Retrieval-Augmented Generation (RAG)

Azure AI Search & Azure Portal Setup

Document chunking and indexing

Vector Search

Prompt orchestration

AI grounding techniques

Designing production-ready enterprise AI applications

Who this course is for
Software Engineers, AI Engineers, OutSystems Developers, Low-Code Developers
Computer Science & Engineering Students
Anyone interested in building enterprise AI applications

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Advanced PowerShell: PowerShell Data Mastery
Published 7/2026
By Brien Posey
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + subtitle | Duration: 15h 42m | Size: 26.7 GB

Unlock the full potential of your data with PowerShell by learning how to build advanced PowerShell tools for leveraging and visualizing complex data from multiple sources.

Overview
Take your PowerShell skills to the next level with Advanced PowerShell: PowerShell Data Mastery. This advanced course is designed to help you harness the power of PowerShell to work with complex data sets, create interactive visualizations, and build robust applications. Youll start by learning how to extend PowerShells capabilities using C#, Python, and .NET integration, and then dive into working with dates, databases, and SQL applications. With a focus on practical examples and real-world scenarios, youll gain hands-on experience in building custom classes, modules, and database-driven applications.
As you progress through the course, youll learn advanced techniques for data visualization, including chart controls, sorting, and customization. Youll also explore how to work with multiple data sources, handle errors, and optimize script performance. The course culminates in a capstone project where youll build a comprehensive IT ticketing system, leveraging all the skills and knowledge youve acquired throughout the course. By the end of this course, youll be equipped with the expertise to interact with complex data sets, create visualizations, and build robust applications that drive business value. Whether youre a seasoned PowerShell user or an IT professional looking to expand your skillset, Advanced PowerShell: PowerShell Data Mastery will help you unlock the full potential of your data and take your career to the next level.

Skill Level
Intermediate to advanced

Learn How To
Build PowerShell scripts that leverage SQL Server
Visualize data with charts and graphs
Combine multiple data sources
Harness the power of the .NET Framework

Course Requirement
The Beginner course and the User Interface Design course should be considered prerequisites for taking this course.

Who Should Take This Course
These courses are designed for IT professionals, system administrators, and power users who want to move beyond basic scripting and learn how to build polished, interactive tools using PowerShell. Whether youre new to PowerShell or looking to deepen your skills, youll learn how to automate real-world administrative tasks, create intuitive user interfaces, and develop advanced applications that streamline everyday operations. The material is ideal for learners who enjoy problem-solving, value efficiency, and want to bridge the gap between command-line automation and professional-grade software design.

About Pearson Video Training
Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, and Que. Topics include IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at

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