Generative AI for Interviewers


Generative AI for Interviewers
.MP4, AVC, 1280×720, 30 fps | English, AAC, 2 Ch | 19m | 74.2 MB
Instructor: Alice Meredith​

This course will help you streamline and enhance your hiring process using AI.

What you’ll learn

Recruiting the right talent is becoming increasingly complex, with larger pools of applicants and the need for diverse and inclusive hiring practices. In this course, Generative AI for Interviewers, you’ll explore how AI can elevate your interviewing process.

First, you’ll see how to create effective job descriptions and inclusive and fair interview guides using AI tools. Next, you’ll explore how different AI tools that automate and improve resume summarizing, allowing you to identify the most suitable candidates quickly. Finally, you’ll learn how to use AI tools to capture critical notes from interviews accurately.

When you’re finished with this course, you’ll have increased AI skills and knowledge to efficiently identify and engage top talent while maintaining high standards of equity.

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Generative AI for Innovators


Generative AI for Innovators
.MP4, AVC, 1920×1080, 30 fps | English, AAC, 2 Ch | 19m | 115 MB
Instructor: Esteban Herrera​

Generative AI tools can dramatically accelerate product innovation. This course will teach you how to harness these tools to create new products and solutions.

What you’ll learn

Innovators often struggle to make informed decisions quickly in today’s rapidly evolving technology landscape.

In this course, Generative AI for Innovators, you’ll learn to use Generative AI-powered tools to accelerate your research and innovation processes. First, you’ll explore how to conduct technology landscape research. Next, you’ll discover how to transform research findings into actionable strategies by leveraging AI’s analytical capabilities. Finally, you’ll learn how to design and structure experiments to validate your innovations.

When you’re finished with this course, you’ll have the skills and knowledge of Generative AI-powered tools needed to drive innovation initiatives efficiently.

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GenAI Model Access Layer and Structured Outputs


GenAI Model Access Layer and Structured Outputs
Last Updated Feb 10, 2026
Duration: 1h 56m | .MP4 1920×1080 30 fps(r) | AAC, 48000 Hz, 2ch | 308.73 MB
Genre: eLearning | Language: English​

Learn how to design production-grade GenAI systems. This course will teach you to build reliable, scalable, and cost-efficient LLM applications using advanced prompting, structured outputs, validation, and API integration.

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GenAI Model Access Layer and Structured Outputs


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GenAI Inference and Serving Architecture


GenAI Inference and Serving Architecture
Last Updated Jan 30, 2026
Duration: 1h 56m | .MP4 1920×1080 30 fps(r) | AAC, 48000 Hz, 2ch | 309.29 MB
Genre: eLearning | Language: English​

Running GenAI systems efficiently is key for real-world AI. This course will teach you how to make informed model-selection decisions and implement fast, scalable, and cost-optimized transformer inference pipelines.

More Info:
GenAI Inference and Serving Architecture


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GenAI for Busy Java Developers


GenAI for Busy Java Developers
English | 2025 | h264, yuv420p, 1280×720 | 48000 Hz, 2channels | Duration: 4h 18m | 853 MB​

Java software engineers who need to learn how to harness the capabilities of generative AI tools for critical aspects of the production software process.
This video course empowers Java engineers with the basic knowledge and skills needed to harness the capabilities of generative AI tools for various aspects of the production software process.
Developed for beginner and early intermediate Java developers, it explores the impact of Machine Learning on the Java ecosystem and features hands-on coding using tools such as OpenAI ChatGPT, Google Gemini, Anthropic Claude, and other GenAI services using the LangChain4j API. With a focus on practical applications, participants will gain proficiency in GenAI, an understanding of context, learn about embeddings, and how to responsibly integrate GenAI into Java applications.
Attendees will:
Learn the skills they need in order to apply generative AI to real-world software development. Enterprise developers will learn the fundamentals of generative AI and how to best apply them to reliably put GenAI applications into production.
Understand programmatic interfaces to GenAI using REST APIs and featuring the LangChain4J Java API, including many source code examples covering different prompt techniques, streaming, embeddings, templates, context, Retrieval-Augmented Generation (RAG) and an introduction to agents
Architect and implement a basic chatbot application that understands private document sets.
Skill Level:
Beginner to Early Intermediate
Learn How To:

Differentiate between the two basic types of deep learning
Structure prompts and select techniques that produce useful output
Use LangChain4j to create a working GenAI application
Apply embeddings to various use cases
Manage context for effective LLM responses
Choose an appropriate vector database and what to store in that database
Create tools and understand the basics of agents

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GenAI Data and Knowledge Layer


GenAI Data and Knowledge Layer
.MP4, AVC, 1920×1080, 30 fps | English, AAC, 2 Ch | 1h 56m | 298 MB
Instructor: Laurentiu Raducu​

This course will teach you how to design and build robust, production-ready GenAI data and knowledge layers.

What you’ll learn

Engineers often struggle with how to represent their data as vectors, choose and operate vector stores, design knowledge graphs, and build robust pipelines that keep everything up to date and testable at scale. In this course, GenAI Data and Knowledge Layer, you’ll gain the ability to design and implement production-ready data and knowledge layers that power reliable GenAI applications.

First, you’ll explore how embeddings, vector stores, and chunking strategies turn raw data into effective semantic representations for retrieval-augmented generation. Next, you’ll discover how to architect and operate vector databases, integrate knowledge graphs, and orchestrate end-to-end pipelines that continuously ingest, transform, and index data. Finally, you’ll learn how to apply advanced preprocessing and synthetic data generation techniques to improve retrieval quality, robustness, and test coverage of your GenAI systems.

When you’re finished with this course, you’ll have the skills and knowledge of modern GenAI data and knowledge layers needed to confidently build and maintain scalable, production-grade GenAI systems grounded in your own data.

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Game Dev Essentials: Code Architectures for Indie Developers


Game Dev Essentials: Code Architectures for Indie Developers
Duration: 11h 24m | .MP4 1920×1080 30fps(r) | AAC, 44100Hz, 2ch | 5.70 GB
Genre: eLearning | Language: English​

Learn by comparison how to create a First Person Game using two scalable approaches in Unity
What you’ll learn

  • Learn Two Game Architectures that you can apply to your games
  • Create Maintainable and Scalable Code
  • How to Implement Solid Code Architecture that you can Reuse in different Projects
  • How to separate logic, visual and data in your code that are less dependent of Monobehaviour class
  • Basic concepts of Dependency Injection
  • How to integrate GUI with Audio Mixer, user interactions and flow control

Requirements
– Advanced knowledge in Unity Game Engine

Description
Scalability is one of the biggest problems in Unity projects. The unimaginable amount of freedom and lack of clear guidelines can lead us to complex systems interacting in such a way that no human brain can handle it. In a project with 10,000+ lines of code, every single change can be a high risk of breaking another component, with endless edge cases emerging with every new feature.

Especially if you are a small studio or a solo developer, this course can be the key to avoiding this problem and gaining confidence in building complex, solid Unity projects. In this course, we will develop a simple survival game using two different scalable architectures.

Introduction:

Here we will dive deeper into architecture problems, explore the proposed solutions in this course, and understand in which scenarios each one is better than the other. What is flow control? What is glue? These concepts are presented here.

Creating and Understanding the Project:

We will quickly prepare everything we need to dive into the code. We will create the project, add visual assets, and prepare the scene.

Handling Gameplay Features – Movement:

At this point, we will have our first contact with both architectures. We will discuss and build together a First Person Controller, handling movement, reading inputs, splitting the problem into small pieces, and solving each piece. We will also learn how to separate data from logic.

Handling Gameplay Features – Health:

Here we are going to discuss and implement the Health System. Why? Because it is a feature that involves triggers and interactions between the Player and the environment, and we’ll see how differently these interactions are handled between the different architectures.

Handling Gameplay Features – Day and Night Cycle:

Time, Skybox, and Fog are different components that we will combine into a system that will work as the Day and Night Cycle of the game. This is where we will find a few similarities between Glue and UD, explore the idea of dependency injection, and much more.

Handling GUI:

Finally, here you will understand the full power of the UD architecture. We will build a simple Pause and Settings Menu that will enable the player to control the Mixer (Volume) of the game. How to handle user interactions? How to separate view from logic? We are going to dive into these questions at the end.

Do you prefer flexibility and speed? Or do you want full control of your project?

Get this course, learn them both, and decide.

Who this course is for:
– Game Developers
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FXPHD – AIF201 – Generative AI for VFX with ComfyUI & InvokeAI


2.58 GB | 34min 32s | mp4 | 1920X1080 | 16:9
Genre:eLearning |Language:English
Files Included :
FileName :Class 1 Introduction and Setup.mp4 | Size: (183.98 MB)
FileName :Class 2 Essential SD Building Blocks.mp4 | Size: (257.2 MB)
FileName :Class 3 Seamless Textures Tool Part 1.mp4 | Size: (197.05 MB)
FileName :Class 4 Seamless Textures Tool Part 2.mp4 | Size: (228.82 MB)
FileName :Class 5 Using CG Elements as Guidance Part 1.mp4 | Size: (257.93 MB)
FileName :Class 6 Using CG Elements as Guidance Part 2.mp4 | Size: (312.36 MB)
FileName :Class 7 Generating 3D Assets Part 1.mp4 | Size: (276.68 MB)
FileName :Class 8 Generating 3D Models Part 2.mp4 | Size: (250.78 MB)
FileName :Class 9 Inpainting with InvokeAI.mp4 | Size: (369.68 MB)
FileName :Class 10 Segmentation and Upscaling Techniques.mp4 | Size: (302.44 MB)]
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Fundamentals of Database Engineering


Fundamentals of Database Engineering
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 9.16 GB | Duration: 20h 24m​

Learn ACID, Indexing, Partitioning, Sharding, Concurrency control, Replication, DB Engines, Best Practices and More!

What you’ll learn
Learn and understand ACID Properties
Database Indexing
Database Partitioning
Database Replication
Database Sharding
Database Cursors
Concurrency Control (Optimistic, Pessimistic)
B-Trees in Production Database Systems
Database System Designs
Difference between Database Management System, Database Engine and Embedded database
Database Engines such as MyISAM, InnoDB, RocksDB, LevelDB and More
Benefits of Using one database engine over the other
Switching Database Engines with MySQL
Database Security
Homomorphic Encryption

Requirements
Have worked with databases before but wish to get deeper understanding
Basic SQL knowledge
Description
Database Engineering is a very interesting sector in software engineering. If you are interested in learning about database engineering you have come to the right place. I have curated this course carefully to discuss the Fundamental concepts of database engineering.

This course will not teach you SQL or programming languages, however, it will teach you skillsets and patterns that you can apply in database engineering. A few of the things that you will learn are Indexing, Partitioning, Sharding, Replication, b-trees in-depth indexing, Concurrency control, database engines and security, and much more.

I believe that learning the fundamentals of database engineering will equip you with the necessary means to tackle difficult and challenging problems yourself. I always compare engineering to math, you never memorize specific formulas and equations, you know the basic proves and derive and solve any equation one throws at you. Database engineering is similar, you can’t possibly say MongoDB is better than MySQL or Postgres is better than Oracle. Instead, you learn your use case and by understanding how each database platform does its own trade-offs you will be able to make optimal decisions.

One other thing you will learn in this course is the lowest database interface that talks to the OS which is the database engine. Database engines or storage engines or sometimes even called embedded databases is a software library that a database management software uses to store data on disk and do CRUD (create update delete) Embedded means move everything in one software no network client-server. In this video course, I want to go through the few popular database engines, explain the differences between them, and finally, I want to spin up a database and change its engine and show the different features of each engine.

Enjoy the course.

Who this course is for
Software Engineers and Database Engineers

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Fullstack TypeScript (feat. GraphQL & Node.js)


Fullstack TypeScript (feat. GraphQL & Node.js)
MP4 | Video: h264, yuv420p, 2560×1440 | Audio: aac, 48000 Hz | Duration: 3h 11m | 1.32 GB
Genre: eLearning | Language: English​

TypeScript offers a delightful authoring experience, but all bets are off once you make an API call and receive an

any

response. We’ll build a Twitter App with React and generate TypeScript code based on a GraphQL schema. Combine TypeScript and GraphQL’s type systems to create full-stack, fully-type-checked codebases (even the data layer!), making the entire codebase shockingly easy to evolve, refactor and maintain.

More info

RapidGator
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https://rapidgator.net/file/9e5a1570f63a46ec46176aebb7d8b02d/Fullstack.TypeScript.feat..GraphQL..Node.js.part1.rar
https://rapidgator.net/file/fbce39d43cd6c5487b389e2d2e342100/Fullstack.TypeScript.feat..GraphQL..Node.js.part2.rar

DDownload
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https://ddownload.com/6u5vsclyttga/Fullstack.TypeScript.feat..GraphQL..Node.js.part1.rar
https://ddownload.com/ukerl0vb3s3m/Fullstack.TypeScript.feat..GraphQL..Node.js.part2.rar

<—====All Premium====—>
UsersDrive
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https://usersdrive.com/vnvjafag8rw3/Fullstack.TypeScript.feat..GraphQL..Node.js.part1.rar
https://usersdrive.com/td6plcqx0ry0/Fullstack.TypeScript.feat..GraphQL..Node.js.part2.rar