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Year of manufacture : 2015
Manufacturer : LinkedIn Learning
Manufacturer’s website : Code:Copy to clipboard

https://www.linkedin.com/learning/

Posted by Evan Sutton
Duration : 3h35m
Type of material distributed : Video lesson
Language : En

Description :
MASSIVE is Native Instruments’ flagship digital synth; musicians all over the world use it to create music in the studio and on the stage. In this course, author Evan Sutton will dive deep into the instrument, including its flexible and powerful filters and routing, audio processing, and modulation features. He covers the basic signal flow and shows how to use MASSIVE’s wavetable system to create unique sounds. After processing those sounds with filters and modulators, Evan uses audio effects to sweeten and brighten the mix, and then brings the entire sound to life with MASSIVE’s macro controls and automation.
Content
Introduction:
Welcome
1m video
What you should know before watching this course
27s video
Using the exercise files
42s video
1. Digital Synthesis with MASSIVE:
Basic layout and signal flow
2m 9s video
Envelope setting and routing
5m 45s video
The oscillators, wavetables, and how to use them
6m 44s video
MASSIVE’s wavetables
8m 20s video
Bend modes
7m 17s video
Filter modes
7m 21s video
Alternate filter modes and modulation
16m 10s video
LFO (low-frequency oscillator)
11m 45s video
Envelope looping
9m 1s video
Stepper
10m 44s video
Performer
12m 34s video
Master settings and polyphony
17m 34s video
Modulation oscillator, part one: Ring mod
8m 22s video
Modulation oscillator, part two: Phase mod
8m 11s video
Modulation oscillator, part three: Position and filter FM
8m 42s video
Insert effects, part one: Distortion
7m 11s video
Insert effects, part two: Feedback and more
8m 59s video
Master effects
8m 47s video
Noise
7m 49s video
Macro control, part one: Incoming midi
7m video
Macro control, part two: Knobs
8m 48s video
Sidechaining
8m 40s video
Automating macros in Logic Pro
6m 49s video
Automating macros in Ableton Live
4m 6s video
Saving and naming
3m 41s video
Conclusion:
Next steps
1m 10s video
Example files : present
Video format : MP4
Video : MPEG-4 AVC, 1280x720p, 15fps, (16:9), ~800 kb/s
Аудио: AAC LC, 48kHz, 2 channels, 320kb/s, stereo

MASSIVE：Digital Synthesis (844.58 MB)
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https://rapidgator.net/file/064db77823c51609bfb50048c3d7e22f/MASSIVE：Digital.Synthesis.rar

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https://drop.download/6fics73uvo0s/MASSIVE%EF%BC%9ADigital.Synthesis.rar

Manus AI Mastery: Build Real-World Projects with AI Agents
Published 1/2026
Duration: 50m | .MP4 1920×1080 30fps(r) | AAC, 44100Hz, 2ch | 543.42 MB
Genre: eLearning | Language: English​

A step-by-step guide to using Manus AI agents for research, automation, content creation, and no-code app building.

What you’ll learn

• Execute large-scale data analysis using "Wide Research" to investigate market trends, competitors, and products in parallel
• Configure email-based agent triggers to automate research, study planning, and administrative tasks directly from your inbox
• Build functional web applications and internal tools without writing a single line of code
• Develop a "Content Factory" workflow to mass-produce structured educational materials or marketing assets
• Differentiate between traditional chatbots and autonomous AI agents to understand the paradigm shift toward execution-first AI.
• Master the Manus interface by correctly toggling between Chat Mode and Agent Mode to optimize credit usage and task efficiency.
• Adopt the "Manager Mindset" to effectively delegate complex, multi-step workflows to agents rather than writing single prompts.
• Automate financial data analysis to transform raw spreadsheets into actionable insights
• Create professional, studio-quality presentation decks using the Nano Banana Pro integration within Manus AI Slides.
• Implement "Human-in-the-Loop" verification strategies to ensure the accuracy, safety, and reliability of autonomous agent outputs.

Requirements
– No programming or technical experience is needed. This course relies entirely on Manus AI’s natural language interface and No-Code tools.

Description
Manus AI is not just another chatbot.

It is an AI agent platform that can research, automate tasks, build content, analyze data, and even create web apps for you.

In this course, you will learn how to use Manus AI the right way-not by chatting, but by thinking like a manager and assigning real work to AI agents.

This is a practical, step-by-step course designed for beginners, creators, freelancers, founders, students, and professionals who want to use Manus AI agents to do real work, not just generate text.

Manus AI Mastery is a project-based bootcamp designed to take you from a complete beginner to an AI Systems Architect. Unlike other courses that focus on "prompt engineering" for chatbots, this course teaches you the "Manager Mindset"-how to delegate complex, multi-step workflows to autonomous agents.

What You Will Learn

By the end of this course, you will be able to:

Master the Manus Interface:Understand the critical difference between Chat Mode and Agent Mode to save credits and maximize output.

Perform Research at Scale:Use Wide Research to analyze market trends, competitors, and financial data in parallel-doing a week’s worth of research in minutes.

Create Stunning Visuals:Generate professional presentation decks using the Nano Banana Pro integration within Manus AI Slides.

Build Software Without Code:Use the No-Code MVP Builder to deploy fully functional web apps and internal tools simply by describing them.

Automate Your Life:Set up Agent Triggers to automate research and study planning directly through email workflows.

Adopt the Agentic Mindset:Learn the art of Human-in-the-Loop verification to ensure high-quality, reliable outputs every time.

Course Curriculum Overview

This course is built around Real-World Projects, not just theory. You will watch over the shoulder of an expert as we build:

Foundation & Setup:We demystify the Paradigm Shift from Chatbots to Agents and look "Under the Hood" of Manus’s unique architecture.

Project 1: AI-Powered Market Research Agent:Build a bot that scours the web to deliver comprehensive competitive intelligence.

Project 2: Automated Industry Intelligence:Create a "Weekly Report Bot" that keeps you updated on your sector without you lifting a finger.

Project 3: Financial Data Analyst:Automate the extraction and analysis of complex financial data for instant insights.

Project 4: The AI Design Studio:Master Nano Banana Pro to generate editable, high-fidelity slides for your next big presentation.

Project 5: Content Factory:Build a system to generate language learning materials (or any educational content) at scale.

Project 6: No-Code SaaS MVP:Watch Manus write code, set up databases, and deploy a real web application from a single prompt.

Why Learn Manus AI Now?

Manus AI represents the next generation of AI tools-AI that acts, not just talks.

Manus has recently been acquired by Meta, and many new features are coming. Learning Manus AI now gives you a huge early advantage as agent-based AI becomes mainstream.

If you want to stay ahead in:

AI automation

AI agents

No-code development

Future-proof skills

This is the right time to learn Manus AI.

Enroll now and start building real-world projects with AI agents.

Who this course is for:

• Beginners curious about Manus AI
• Freelancers and consultants
• Founders and startup builders
• Content creators and educators
• Students and professionals
• Anyone who wants to automate work using AI agents

More Info

Managing the Kubernetes API Server and Pods
MP4 | Video: AVC 1280×720 | Audio: AAC 44KHz 2ch | Duration: 3 Hours | 421 MB
Genre: eLearning | Language: English​

It’s time to dig deeper into Kubernetes. You will learn about its API architecture and its internals, how to organize workloads, and look closely at the primary workload element in Kubernetes, the Pod.

It’s time to take your Kubernetes admin skills to the next level and dig into how to deploy and manage container-based applications in Kubernetes. In this course, Managing the Kubernetes API Server and Pods, you will gain the ability to deploy, manage, and troubleshoot container-based workloads in Kubernetes. First, you will learn how to use the Kubernetes API and API Server internals. Next, you will discover how to use labels, annotations, and namespaces to organize the largest workloads and how Kubernetes uses labels internally for its own operations. Finally, you will explore how to create, manage, and maintain healthy container-based applications with the primary Kubernetes workload construct, the Pod. When you’re finished with this course, you will have the skills and knowledge of creating and maintaining container-based workloads in Kubernetes.

Managing Kubernetes Controllers and Deployments
MP4 | Video: AVC 1280×720 | Audio: AAC 44KHz 2ch | Duration: 2 Hours 40M | 288 MB
Genre: eLearning | Language: English​

Learn how to deploy and maintain applications using Kubernetes Controllers. In this course you’ll learn how to select a Controller for your workload, deploy it, and maintain your container-based applications in your Kubernetes cluster.

Let’s take your Kubernetes admin skills to the next level and continue along on your Certified Kubernetes Administrator (CKA) learning path. This course, Managing Kubernetes Controllers and Deployments, dives into the primary building block of Kubernetes-based applications: Controllers. In this course you will learn the critical skills for deploying and maintaining your self-healing applications in Kubernetes. The course covers Deployments, DaemonSets, StatefulSets, Jobs, and CronJobs. You’ll also learn how to select a Controller type for your workload, and how to deploy and maintain your container-based application in your Kubernetes cluster.

Released 9/2022 MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Intermediate | Genre: eLearning | Language: English + vtt | Duration: 1h 32m | Size: 256.7 MB​

Managing the encryption key, storage backend, and the upgrades of the hashicorp vault server is tricky. In this course, Managing HashiCorp Vault Server, you’ll learn all about the management of various aspects of the vault server right from its installation to its upgradation. First, you’ll explore how to manage the encryption key and the storage backend. Next, you’ll discover how to troubleshoot the vault server during an incident. Finally, you’ll learn how to upgrade the vault server to a latest version. When you’re finished with this course, you’ll have the skills and knowledge of vault server needed to successfully administer it.

Welcome to – Check it Every Days
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Happy Learning!! Click to expand…

Managing Access and Secrets in HashiCorp Vault
Duration: 2h 39m | .MP4 1280×720, 30 fps(r) | AAC, 48000 Hz, 2ch | 398 MB
Level: Intermediate | Genre: eLearning | Language: English​

HashiCorp Vault provides centralized secrets management for users and applications, and helps you stop and eliminate secrets sprawl. In this course, Managing Access and Secrets in HashCorp Vault, you’ll learn how to install and work with authentication methods. First, you’ll explore access management and Vault tokens. Next, you’ll discover the auditing features Vault provides. Finally, you’ll learn how to leverage different secrets engines and storage backends that work seamlessly with Vault. When you’re finished with this course, you’ll have the skills and knowledge of leveraging Vault’s features needed to centralize secrets management for your organization or your customers.

Making Music In Bitwig: Mastering Drums
Published 10/2024
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.04 GB | Duration: 4h 16m​

Sound Designing, Programming, Layering and Mixing Drums in Bitwig Studio

What you’ll learn

Deepen your Bitwig Knowledge

Improve your Mixing Skills

Learn Drum Sound Design

Record & Create Unique Percussion

Requirements

Basic Bitwig Knowledge recommended

Description

Welcome to my big course on drums, from sound design, over composition & texturing to mixing, this is my grand tour of different production techniques you can use to create better drum loops.We’ll be synthesizing kicks in the grid, talking about the theory and fundamental characteristics of snare drums, synthesizing them in phase 4 and then layering & processing them,we’ll be writing with hihat samples, synthesizing our own hihats with convolution and unison in the grid & then using modulators to humanize them,we’ll be recording our own percussions with household objects, synthesizing unique percussion loops and then sequencing them using the multi-sampling capabilities of sampler & audio editingand lastly we’ll write a proper drumloop, use bitwigs group clips system to efficiently write variations and fills, add risers and sfx to our drums and mixing them to make them sound great together.This course does expect some previous knowledge about Bitwig, its modulators, arrangement view etc, but by no means does it require you to be an expert already.If you’re completely new to Bitwig Studio, i would recommend taking my course on the Basics first tho. You can also try to follow this in another DAW, but that’ll be a bit more challenging because you’ll need to know it well enough to translate what I show you into that DAWs tools. It can be done, but it’s gonna take some extra thinking on your end. So yeah, i hope to see you in the course, there are a lot of fun techniques i have to show to you!

Overview

Section 1: Kick and Snare

Lecture 1 Making Kicks in the Grid

Lecture 2 The Anatomy of a Snare Drum

Lecture 3 Synthesizing Snares with Phase 4

Lecture 4 Layering Snares

Lecture 5 Processing Snares

Section 2: Hihats

Lecture 6 The easy way

Lecture 7 Complex Hihat Patterns with Noise and Convolution

Lecture 8 Fully Synthesizing Hi-Hats using E-hat or the Grid

Lecture 9 Humanizing Hihats with Modulation & Layering

Section 3: Percussion

Lecture 10 Recording your own Percs

Lecture 11 Creating Percussion Mudpies

Lecture 12 Sequencing Hits with Multisampling

Lecture 13 Quantizing, Chopping & Arranging Percussion Mudpies

Section 4: Programming & Mixing

Lecture 14 Writing a Drumloop

Lecture 15 A Quick Way to get Variations

Lecture 16 Cleaning up & adding texture to the drumloop

Lecture 17 Mixing a Drumloop

Bitwig Users and beyond that want to learn more about Drums

Machine Learning with Python Data Science for Beginners

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Format:mp4
Size: 1.17 GB
Duration:00:31:37 Click to expand…

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https://rapidgator.net/file/023512ac103050c1ef87c7497056c9e0/Machine.Learning.with.Python.Data.Science.for.Beginners.rar

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https://drop.download/dqhclhn0eky6/Machine.Learning.with.Python.Data.Science.for.Beginners.rar

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Year of release : 2025
Manufacturer : UDEMY
Manufacturer’s site : Code:Copy to clipboard

https://www.udemy.com/course/machinelearning/?couponCode=ST9MT120225A

Author : Kirill Eremenko Hadelin de Ponteves
Duration : 42 hours 30m
Type of material given : Video lesson
Language : En
Description: Authors
Kirill Eremenko Hadelin de Ponteves SuperDataScience Team Ligency Team
The request not to leave the distribution, I can not maintain the distribution forever.
Share a freebie with other people, do not leave the distribution.
Call other people to switch to the rutrex.
Course in En. Added En subtitles using Speech to Text for Adobe Premier Pro.
Interested in the field of Machine Learning? Then this course is for you!
This course has been designed by a Data Scientist and a Machine Learning expert so that we can share our knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way.
Over 1 Million students world-wide trust this course.
We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.
This course can be completed by either doing either the Python tutorials, or R tutorials, or both – Python & R. Pick the programming language that you need for your career.
This course is fun and exciting, and at the same time, we dive deep into Machine Learning. It is structured the following way:
Part 1 – Data Preprocessing
Part 2 – Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
Part 3 – Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
Part 4 – Clustering: K-Means, Hierarchical Clustering
Part 5 – Association Rule Learning: Apriori, Eclat
Part 6 – Reinforcement Learning: Upper Confidence Bound, Thompson Sampling
Part 7 – Natural Language Processing: Bag-of-words model and algorithms for NLP
Part 8 – Deep Learning: Artificial Neural Networks, Convolutional Neural Networks
Part 9 – Dimensionality Reduction: PCA, LDA, Kernel PCA
Part 10 – Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost
Each section inside each part is independent. So you can either take the whole course from start to finish or you can jump right into any specific section and learn what you need for your career right now.
Moreover, the course is packed with practical exercises that are based on real-life case studies. So not only will you learn the theory, but you will also get lots of hands-on practice building your own models.
And last but not least, this course includes both Python and R code templates which you can download and use on your own projects.
Content
01 – Welcome to the course! Here we will help you get started in the best conditions
02 – ——————– Part 1 Data Preprocessing ——————–
03 – Data Preprocessing in Python
04 – Data Preprocessing in R
05 – ——————– Part 2 Regression ——————–
06 – Simple Linear Regression
07 – Multiple Linear Regression
08 – Polynomial Regression
09 – Support Vector Regression (SVR)
10 – Decision Tree Regression
11 – Random Forest Regression
12 – Evaluating Regression Models Performance
13 – Regression Model Selection in Python
14 – Regression Model Selection in R
15 – ——————– Part 3 Classification ——————–
16 – Logistic Regression
17 – K-Nearest Neighbors (K-NN)
18 – Support Vector Machine (SVM)
19 – Kernel SVM
20 – Naive Bayes
21 – Decision Tree Classification
22 – Random Forest Classification
23 – Classification Model Selection in Python
24 – Evaluating Classification Models Performance
25 – ——————– Part 4 Clustering ——————–
26 – K-Means Clustering
27 – Hierarchical Clustering
28 – ——————– Part 5 Association Rule Learning ——————–
29 – Apriori
30 – Eclat
31 – ——————– Part 6 Reinforcement Learning ——————–
32 – Upper Confidence Bound (UCB)
33 – Thompson Sampling
34 – ——————– Part 7 Natural Language Processing ——————–
35 – ——————– Part 8 Deep Learning ——————–
36 – Artificial Neural Networks
37 – Convolutional Neural Networks
38 – ——————– Part 9 Dimensionality Reduction ——————–
39 – Principal Component Analysis (PCA)
40 – Linear Discriminant Analysis (LDA)
41 – kernel pca
42 – ——————– Part 10 Model Selection & Boosting ——————–
43 – Model Selection
44 – XGBoost
45 – Annex Logistic Regression (Long Explanation)
46 – Congratulations!! Don’t forget your Prize )
Example files : present
Format Video : mp4
Video : H265 1920×1080 16: 9 30k / SEK 300 kbit / sec
Audio : AAC 48 kHz 128 kbps 2 channels

Machine Learning A-Z AI, Python & R + ChatGPT Prize (8.09 GB)

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https://clicknupload.click/xnv1xmeotfg6
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RapidGator Link(s)
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https://rapidgator.net/file/39740bb4391430236963e3dc14e2bd55/Machine.Learning.A-Z.AI.Python..R..ChatGPT.Prize.part1.rar
https://rapidgator.net/file/07c39f77f5d0d2d23213de7d192e14ec/Machine.Learning.A-Z.AI.Python..R..ChatGPT.Prize.part2.rar
https://rapidgator.net/file/89a9da573f583073d8a0d70287a1494d/Machine.Learning.A-Z.AI.Python..R..ChatGPT.Prize.part3.rar
https://rapidgator.net/file/01fbcc8c177f2d8dcf91e3330c2556f0/Machine.Learning.A-Z.AI.Python..R..ChatGPT.Prize.part4.rar
https://rapidgator.net/file/b7f3d58806a57b0191e5bdd3560c41f9/Machine.Learning.A-Z.AI.Python..R..ChatGPT.Prize.part5.rar