• Regeln für den Video-Bereich:

    In den Börsenbereich gehören nur Angebote die bereits den Allgemeinen Regeln entsprechen.

    Einteilung

    - Folgende Formate gehören in die angegeben Bereiche:
    - Filme: Encodierte Filme von BluRay, DVD, R5, TV, Screener sowie Telesyncs im Format DivX, XviD und x264.
    - DVD: Filme im Format DVD5, DVD9 und HD2DVD.
    - HD: Encodierte Filme mit der Auflösung 720p oder darüber von BluRay, DVD, R5, TV, Screener sowie Telesyncs im Format x264.
    - 3D: Encodierte Filme von BluRay, die in einem 3D Format vorliegen. Dies gilt auch für Dokus, Animation usw.
    - Serien: Cartoon/Zeichentrick, Anime, Tutorials, Dokumentationen, Konzerte/Musik, Sonstiges sind demnach in die entsprechenden Bereiche einzuordnen, auch wenn sie beispielsweise im High Definition-Format oder als DVD5/DVD9/HD2DVD vorliegen. Ausnahme 3D.
    - Bereich Englisch: Englische Releases gehören immer in diesen Bereich.
    - Bereich Talk: Der Bereich, in dem über die Releases diskutiert werden kann, darf, soll und erwünscht ist.


    Angebot/Beitrag erstellen

    - Ein Beitrag darf erst dann erstellt werden, wenn der Upload bei mindestens einem OCH komplett ist. Platzhalter sind untersagt.
    - Bei einem Scenerelease hat der Threadtitel ausschließlich aus dem originalen, unveränderten Releasenamen zu bestehen. Es dürfen keine Veränderungen wie z.B. Sterne, kleine Buchstaben o.ä. vorgenommen werden. Ausnahme Serienbörse:
    - Bei einem Sammelthread für eine Staffel entfällt aus dem Releasename natürlich der Name der Folge. Beispiel: Die Simpsons S21 German DVDRip XviD - ITG
    - Dementsprechend sind also u.a. verboten: Erweiterungen wie "Tipp", "empfehlenswert", "only", "reup", usw. / jegliche andere Zusatzinformation oder Ergänzung, welche nicht in obiger Beschreibung zu finden ist.

    Aufbau des Angebots und Threadtitel

    Der Titel nach folgendem Muster erstellt zu werden. <Name> [3D] [Staffel] [German] <Jahr> <Tonspur> [DL] [Auflösung] <Quelle> <Codec> - <Group>
    Beispiel: The Dark Knight German 2008 AC3 DVDRip XviD - iND
    Beispiel: The Dark Knight 2008 DTS DL BDRip x264 - iND
    Beispiel: The Dark Knight 2008 AC3 DL BDRip XviD - iND
    Beispiel: The Dark Knight German 2008 AC3 720p BluRay x264 iND
    Beispiel: The Dark Knight 2008 DTS DL 1080p BluRay x264 iND
    Beispiel: Die Simpsons S01 German AC3 DVDRip XviD iND
    Beispiel: Die Simpsons S20 German AC3 720p BluRay x264 iND
    Beispiel: Sword Art Online II Ger Sub 2014 AAC 1080p WEBRip x264 - peppermint
    Entsprechend sind also u.a. verboten: Sonderzeichen wie Klammern, Sterne, Ausrufezeichen, Unterstriche, Anführungszeichen / Erweiterungen wie "Tipp", "empfehlenswert", "only", "reup", usw. / jegliche andere Zusatzinformation oder Ergänzung, welche nicht in obiger Beschreibung zu finden ist
    Ausnahmen hiervon können in den Bereichen geregelt sein.

    Die Beiträge sollen wie folgt aufgebaut werden:
    Überschrift entspricht dem Threadtitel
    Cover
    kurze Inhaltsbeschreibung
    Format, Größe, Dauer sind gut lesbar für Downloader außerhalb des Spoilers zu vermerken
    Nfo sind immer Anzugeben und selbige immer im Spoiler in Textform.
    Sind keine Nfo vorhanden z.B. Eigenpublikationen, sind im Spoiler folgende Dateiinformationen zusätzlich anzugeben :
    Quelle
    Video (Auflösung und Bitrate)
    Ton (Sprache, Format und Bitrate der einzelnen Spuren)
    Untertitel (sofern vorhanden)
    Hosterangabe in Textform außerhalb eines Spoiler mit allen enthaltenen Hostern.
    Bei SD kann auf diese zusätzlichen Dateiinformationen verzichtet werden.

    Alle benötigten Passwörter sind, sofern vorhanden, in Textform im Angebot anzugeben.
    Spoiler im Spoiler mit Kommentaren :"Schon Bedankt?" sind unerwünscht.


    Releases

    - Sind Retail-Release verfügbar, sind alle anderen Variationen untersagt. Ausnahmen: Alle deutschen Retail-Release sind CUT, in diesem Fall sind dubbed UNCUT-Release zulässig.
    - Im Serien-Bereich gilt speziell: Wenn ein Retail vor Abschluss einer laufenden Staffel erscheint, darf diese Staffel noch zu Ende gebracht werden.62
    - Gleiche Releases sind unbedingt zusammenzufassen. Das bedeutet, es ist zwingend erforderlich, vor dem Erstellen eines Themas per Suchfunktion zu überprüfen, ob bereits ein Beitrag mit demselben Release besteht. Ist dies der Fall, ist der bereits vorhandene Beitrag zu verwenden.
    - P2P und Scene Releases dürfen nicht verändert oder gar unter einem iND Tag eingestellt werden.


    Support, Diskussionen und Suche

    - Supportanfragen sind entweder per PN oder im Bereich Talk zu stellen.
    - Diskussionen und Bewertungen sind im Talk Bereich zu führen. Fragen an die Uploader haben ausschließlich via PN zu erfolgen, und sind in den Angeboten untersagt.
    - Anfragen zu Upload-Wünschen sind nur im Bereich Suche Video erlaubt. Antworten dürfen nur auf Angebote von MyBoerse.bz verlinkt werden.


    Verbote

    - Untersagt sind mehrere Formate in einem einzigen Angebotsthread, wie beispielsweise das gleichzeitige Anbieten von DivX/XviD, 720p und 1080p in einem Thread. Pro Format, Release und Auflösung ist ein eigener Thread zu eröffnen.
    - Grundsätzlich ebenso verboten sind Dupes. Uploader haben sich an geeigneter Stelle darüber zu informieren, ob es sich bei einem Release um ein Dupe handelt.
    - Gefakte, nur teilweise lauffähige oder unvollständige Angebote sind untersagt. Dies gilt auch für eigene Publikationen, die augenscheinlich nicht selbst von z.B. einer DVD gerippt wurden. Laufende Serien, bei denen noch nicht alle Folgen verfügbar sind, dürfen erstellt und regelmäßig geupdatet werden.
    - Untersagt sind Angebote, welche nur und ausschließlich in einer anderen Sprache als deutsch oder englisch vorliegen. Ausnahmen sind VORHER mit den Moderatoren zu klären.


    Verstoß gegen die Regeln

    - Angebote oder Beiträge, die gegen die Forenregeln verstoßen, sind über den "Melden"-Button im Beitrag zu melden.
  • Bitte registriere dich zunächst um Beiträge zu verfassen und externe Links aufzurufen.

++ Premium IPTV ++ 7000 Live Sender ++ UHD Qualität ++ Mediathek mit 18.000 Inhalten ++


VenneTV


Englische Tutorials

Probability and Statistics 1: The Complete Guide

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Probability and Statistics 1: The Complete Guide
Duration: 5h 52m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 7.27 GB
Genre: eLearning | Language: English

Learn everything fast through concise yet contented lectures

What you'll learn
representation and characterisation of data
elementary probability theory
combinatorics
rules for computing probabilities
conditional probability and independence of events
discrete random variables and their probability distributions
expectation value of a discrete random variable
examples of discrete random variables
moment generating functions
continuous random variables and their probability distributions
expectation value of a continuous random variable
examples of continuous random variables
Chebyshev's theorem
bivariate probability distributions
expectations of functions of random variables
covariance
independent random variables
sums of independent random variables
hypothesis testing

Requirements
Basic Calculus, particularly simple differentiation and integration :)


Description
I know, Probability and Statistics is difficult. But is there a way to make it easy? Of course. I for one managed that.

I know a lot of people struggle with it; a very small group of people are good at it. Back in university, I was in that bigger group, the group that struggled through Probability and Statistics lecture. I needed help; I couldn't understand a thing, but I finally found help and turned my exam result around. I guess since you're looking at this, you need help too.

This 6-hour COMPLETE GUIDE course contains everything you need to know to get started with Probability and Statistics. It's packed with videos that have been categorised into different topics, hence easy for you to learn.

I've included lots of definitions, theorems, quizzes, examples, concise notes for EVERY single section, exercises, and a walkthrough of all the exercise sheets. Most importantly, I've done a BONUS section for you! It includes some additional questions that will strengthen your skill even more.

With this basic Probability and Statistics course, you will have a good core understanding to pursue many more difficult Mathematics topic. In this course, everything has been broken down into a simple structure to make learning and understanding easy for you.

This COMPLETE guide is for those of you are looking to get a full understanding of the basics; the important parts. You've already shown half of your determination by looking at the course, so if this course sounds right for you, boost your eagerness to learn and join me on this journey!

Tips:

1) It will be very useful if you also take notes of your own as you're watching the lectures, it will help you understand everything better and quicker. Just pause if I move on to other topics too fast or if you haven't fully understood the previous sub-topic before you move on to the next parts.

2) Please ask any questions you may have in the Q&A section if you don't understand. It's one thing to not understand it, but it's a whole new experience and a very important thing to do when learning Maths to be able to discuss it with fellow students who are going through the same thing.

3) Use headphones for better sound. (I suggest you turn the volume up)

4) Don't forget you can always slow down or speed up the video!


Who this course is for:
high school students
university students
courses that require probability and statistics (e.g. computer science, and other sciences)

Homepage

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Flight Mechanics - From Theory to Certification of Aircraft

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Flight Mechanics - From Theory to Certification of Aircraft
MP4 | Video: h264, 1280x720 | Audio: AAC, 44100 Hz
Language: English | Size: 5.10 GB | Duration: 8h 55m



What you'll learn
Industry like experience on how to approach flight mechanics of airplanes, from design to certification
Aerodynamics that affect flight mechanics
Create and simulate a complete aircraft on Simulink
Understand how to demonstrate that an aircraft is safe
Stability and Control theory
Requirements
Basic Aerodynamics, Basic Engineering initial curriculum

Description
This course starts with a theoretical overview of 3D equations of motion applied for aircraft simulations. In this initial topic, a classical mechanics overview with a review of aerodynamics will provide the theoretical base for the second section.

On the second section we will cover Matlab & Simulink Intro and start the modelling of a generic aircraft. This final model will be used for trim analysis, simulation and can also be used for control law design, flight control sizing and design and many more.

Finally, in the last section we will cover the process for Part 25 aircraft certification. If you don't know what Part 25 is, don't worry, together we will learn all aspects of current regulations. We will cover all the way from understanding the requirements and how to demonstrate compliance with them up to the flight test campaign and maneuvers used in real aircraft certification.

This course is filled with real examples and is a more hands-on approach of a flight mechanics engineer.


Who this course is for:
Those who are looking to know more regarding Flight Mechanics
People interested in Engineering
Aviation enthusiasts in general
Those who want to work with Aerospace related Projects
Those who want to learn how the industry relates to Flight Mechanics - including certification
Those who I want to see a more applied approach in the topic, different from University
Aerospace Engineers
Mechanical Engineers


Homepage

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Ramit Sethi - Earnable

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Ramit Sethi - Earnable
MP4 + PDF Guides | Video: 1920x1080 | Audio: AAC 44.1Khz 2ch | Duration: 9 hours | Language: English | 8.6 GB

You CAN start your own business. One that pays *you* to live the life of your dreams. I'll show you how to go from "no idea" to profitable business, then expand to ongoing, automatic income with this all-in-one course.

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Zuletzt bearbeitet:
Udemy - Deep Learning with Keras

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Udemy - Deep Learning with Keras
Duration: 12h 57m | Video: .MP4 1280x720, 30 fps(r) | Audio: AAC, 44100 Hz, 2ch | Size: 11.6 GB
Genre: eLearning | Language: English

Deep Learning & Keras concepts, model, layers, modules. Build a Neural Network and Image Classification Model with Keras

What you'll learn
Introduction to Deep Learning and Neural Networks
Understand Deep Learning with Keras
Take a big step towards becoming a Deep Learning / Machine Learning engineer
Keras overview, features, benefits
Keras installation
Keras - Models, Layers and Modules
Keras Models - Sequential Model, Functional API
Keras Layers - Dense Layers, Dropout Layers, Convolution Layers, Pooling Layers
Keras Modules
Keras - Model Compilation, Evaluation and Prediction
Loss, Optimizer, Metrics, Compile the Model
Model Training, Model Evaluation, Model Prediction
Life-Cycle for Neural Network Models in Keras
Define Network, Compile Network, Fit Network, Evaluate Network, Make Predictions
Building your first Neural Network with Keras
Building a Multilayer Perceptron neural network
Building Image Classification Model with Keras
Convolutional Neural Network (CNN) & its layers

Requirements
Enthusiasm and determination to make your mark on the world!


Description
Keras is an open-source library of neural network components written in Python. Keras is capable of running atop TensorFlow, Theano, PlaidML and others. The library was developed to be modular and user-friendly. Keras enables fast experimentation through a high level, user-friendly, modular and extensible API. Keras can also be run on both CPU and GPU. Keras was developed and is maintained by Francois Chollet and is part of the TensorFlow core, which makes it TensorFlow preferred high-level API.

Comprised of a library of commonly used machine learning components including objectives, activation functions, and optimizers, Keras' open-source platform also offers support for recurrent and convolutional neural networks. Additionally, Keras offers mobile platform development for users intending to implement deep learning models on smartphones, both iOS and Android.

Keras is essentially an API designed for machine learning and deep learning engineers and follows best practices for reducing cognitive load. Keras offers consistent & simple APIs, minimizes the number of user actions required for common use cases, and provides clear & actionable error messages. It also supports extensive documentation and developer guides.

It is made user-friendly, extensible, and modular for facilitating faster experimentation with deep neural networks. It not only supports Convolutional Networks and Recurrent Networks individually but also their combination

Why do we need Machine Learning libraries such as Keras?

Machine learning uses a variety of math models and calculations to answer specific questions about data. Examples of machine learning in action include detecting spam emails, determining certain objects using computer vision, recognizing speech, recommending products, and even predicting commodities values years in the future.

The calculations implicit in machine learning and deep learning are very complicated to set up to ensure correct output (answers). A variety of machine learning libraries have emerged to help navigate these complexities. With these options, new folks can start getting into data science easily. Some of the most popular machine learning libraries include:

TensorFlow

Keras

sciKit learn

Theano

Microsoft Cognitive Toolkit (CNTK)

Uplatz provides this comprehensive course on Deep Learning with Keras. This Keras course will help you implement deep learning in Python, preprocess your data, model, build, evaluate and optimize neural networks. The Keras training will teach you how to use Keras, a neural network API written in Python. This Keras course will show how the full implementation is done in code using Keras and Python. You will learn how to organize data for training, build and train an artificial neural network from scratch, build and fine-tune convolutional neural networks (CNNs), implement fine-tuning and transfer learning, deploy models using both front-end and back-end deployment techniques.

Deep Learning with Keras - Course Syllabus

1. Introduction to Deep Learning & Keras

What is deep learning?

What is ANN?

Introduction to Keras

a) Overview of Keras

b) Features of Keras

c) Benefits of Keras

Keras Installation

2. Keras - Models, Layers and Modules

Keras Models

a) Sequential Model

b) Functional API

Keras Layers

a) Dense Layers

b) Dropout Layers

c) Convolution Layers

d) Pooling Layers

Keras Modules

3. Keras - Model Compilation, Evaluation and Prediction

Loss

Optimizer

Metrics

Compile the model

Model Training

Model Evaluation

Model Prediction

4. Life-Cycle for Neural Network Models in Keras

Define Network

Compile Network

Fit Network

Evaluate Network

Make Predictions

5. Building our first Neural Network with Keras

(Building a Multilayer Perceptron neural network)

Load Data

Define Keras Model

Compile Keras Model

Fit Keras Model

Evaluate Keras Model

Make Predictions

6. Building Image Classification Model with Keras

What is Image Recognition (Classification)

Convolutional Neural Network (CNN) & its layers

Building Image Classification Model (step by step)

Key Features of Keras

Keras is an API designed for humans

Focus on user experience has always been a major part of Keras

Large adoption in the industry

Highly Flexible

It is a multi backend and supports multi-platform, which helps all the encoders come together for coding

Research community present for Keras works amazingly with the production community

Easy to grasp all concepts

It supports fast prototyping

It seamlessly runs on CPU as well as GPU

It provides the freedom to design any architecture, which then later is utilized as an API for the project

It is really very simple to get started with

Easy production of models actually makes Keras special

Easy to learn and use


Who this course is for:
Deep Learning / Machine Learning Engineers
Machine Learning Researchers - NLP, Python, Deep Learning
Data Scientists and Machine Learning Scientists
Newbies and Beginners aspiring for a career in Machine Learning / Data Science / Deep Learning
Head of Engineering and Technical Leads
Anyone who wants to learn Deep Learning and Machine Learning
Computer Vision Researchers
AI Deep Learning Platform Leads
Senior ML and Deep Learning Scientists
Senior Data Consultants & Analytics Professionals
Product Managers
Artificial Intelligence Program Leads

Homepage

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Deep Learning with TensorFlow (2021)

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Deep Learning with TensorFlow (2021)
Duration: 29h 18m | Video: .MP4 1280x720, 30 fps(r) | Audio: AAC, 44100 Hz, 2ch | Size: 11.2 GB
Genre: eLearning | Language: English

TensorFlow concepts, components, pipeline, ANN, Classification, Regression, Object Identification, CNN, RNN, TensorBoard

What you'll learn
End-to-end knowledge of TensorFlow
TensorFlow concepts, development, coding, applications
TensorFlow components & pipelines
TensorFlow examples
Introduction to Python, Linear Algebra, Matplotlib, NumPy, Pandas
Introduction to Files
Introduction to Machine Learning
TensorFlow Playground & Perceptrons
TensorFlow and Artificial Intelligence
Building Artificial Neural Networks (ANN) with TensorFlow
Types of ANN and Components of Neural Networks
TensorFlow Classification and Linear Regression
TensorFlow vs. PyTorch vs. Theano vs. Keras
Object Identification in TensorFlow
TensorFlow Superkeyword
CNN & RNN, RNN Time Series
TensorBoard - TensorFlow's visualization toolkit

Requirements
Enthusiasm and determination to make your mark on the world!


Description
TensorFlow is an end-to-end open-source machine learning / deep learning platform. It has a comprehensive ecosystem of libraries, tools, and community resources that lets AI/ML engineers, scientists, analysts build and deploy ML-powered deep learning applications. The name TensorFlow is derived from the operations which neural networks perform on multidimensional data arrays or tensors. Deep learning is a subfield of machine learning that is a set of algorithms that is inspired by the structure and function of the brain.

TensorFlow is a machine learning framework that Google created and used to design, build, and train deep learning models. You can use the TensorFlow library do to numerical computations, which in itself doesn't seem all too special, but these computations are done with data flow graphs. In these graphs, nodes represent mathematical operations, while the edges represent the data, which usually are multidimensional data arrays or tensors, that are communicated between these edges.

In simple words, TensorFlow is an open-source and most popular deep learning library for research and production. TensorFlow in Python is a symbolic math library that uses dataflow and differentiable programming to perform various tasks focused on training and inference of deep neural networks. TensorFlow manages to combine a comprehensive and flexible set of technical features with great ease of use.

There have been some remarkable developments lately in the world of artificial intelligence, from much publicized progress with self-driving cars to machines now composing imitations or being really good at video games. Central to these advances are a number of tools around to help derive deep learning and other machine learning models, with Torch, Caffe, and Theano amongst those at the fore. However, since Google Brain went open source in November 2015 with their own framework, TensorFlow, the popularity of this software library has skyrocketed to be the most popular deep learning framework.

TensorFlow enables you to build dataflow graphs and structures to define how data moves through a graph by taking inputs as a multi-dimensional array called Tensor. It allows you to construct a flowchart of operations that can be performed on these inputs, which goes at one end and comes at the other end as output.

Top organizations such as Google, IBM, Netflix, Disney, Twitter, Micron, all use TensorFlow.

Uplatz provides this extensive course on TensorFlow. This TensorFlow course covers TensorFlow basics, components, pipelines to advanced topics like linear regression, classifier, create, train and evaluate a neural network like CNN, RNN, auto encoders etc. with TensorFlow examples.

The TensorFlow training is designed in such a way that you'll be able to easily implement deep learning project on TensorFlow in an easy and efficient way. In this TensorFlow course you will learn the fundamentals of neural networks and how to build deep learning models using TensorFlow. This TensorFlow training provides a practical approach to deep learning for software engineers. You'll get hands-on experience building your own state-of-the-art image classifiers and other deep learning models. You'll also use your TensorFlow models in the real world on mobile devices, in the cloud, and in browsers. Finally, you'll use advanced techniques and algorithms to work with large datasets. You will acquire skills necessary to start creating your own AI applications and models.

You'll master deep learning concepts and models using TensorFlow frameworks and implement deep learning algorithms, preparing you for a career as Deep Learning Engineer. Learn how to build a neural network and how to train, evaluate and optimize it with TensorFlow.

TensorFlow is completely based on Python. This course also provides a sound introduction to Python programming concepts, NumPy, Matplotlib, and Pandas so that you can acquire those skills in this course itself before moving on to learn the TensorFlow concepts. The aim of this TensorFlow tutorial is to describe all TensorFlow objects and method.

This TensorFlow course also includes a comprehensive description of TensorBoard visualization tool. You will gain an understanding of the mechanics of this tool by using it to solve a general numerical problem, quite outside of what machine learning usually involves, before introducing its uses in deep learning with a simple neural network implementation.

TensorFlow Architecture

TensorFlow architecture works in three parts:

Preprocessing the data

Build the model

Train and estimate the model

It is called TensorFlow because it takes input as a multi-dimensional array, also known as tensors. You can construct a sort of flowchart of operations (called a Graph) that you want to perform on that input. The input goes in at one end, and then it flows through this system of multiple operations and comes out the other end as output.

This is why it is called TensorFlow because the tensor goes in it flows through a list of operations, and then it comes out the other side.

TensorFlow - Course Syllabus


Who this course is for:
Machine Learning & Deep Learning Engineers
Data Scientists & Senior Data Scientists
Beginners and newbies aspiring for a career in Machine Learning / Deep Learning
Data Analysts & Advanced Data Analytics Professionals
TensorFlow Engineers
Machine Learning Developers - TensorFlow/Hadoop
Software Developers - AI/ML/Deep Learning
Anyone wishing to learn TensorFlow algorithms and applications
Deep Learning Engineers - Python/TensorFlow
Artificial Intelligence Engineers and Senior ML/DL Engineers
Researchers and PhD students
Data Engineers
AI & RPA Developers - TensorFlow/ML
AI/ML Developers
Machine Learning Leads & Enthusiasts
TensorFlow and Advanced ML Developers

Homepage

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Brian Moran - The Facebook Ads Academy

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Brian Moran - The Facebook Ads Academy
MP4+ MP3 + PDF guides | Video: 960x540 | Audio: AAC 44.1 Khz , 2ch | Duration: 9 hours | Language: English | 5.8 GB

Get the No B.S. secrets behind a $17,000 per day campaign.And tap into an unlimited source of hyper-targeted traffic so you can rapidly scale your sales.
Exclusive Webinar-Only Bonuses!
As promised we are also throwing in over $7,676 in bonuses, 100% FREE when you enroll today.

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Azure Database Administrator Associate

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Azure Database Administrator Associate
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 82 Lessons (10h 6m) | Size: 6.2 GB

Use this course to prepare for the DP-300: Administering Relational Databases on Microsoft Azure exam This course prepares students who are already familiar with core Azure services and Azure and SQL database skills used by Azure Database Administrators.

An Azure Database Administrator is responsible for the management, availability, security, performance monitoring, and optimization of modern relational database solutions. They also assist Azure Data Engineers in managing operational aspects of a data platform solution. Azure Database Administrators are familiar with:

Deploying SQL database solutions within Azure
Azure SQL Server, database, and query architecture
Basic usage of Transact-SQL for administrative tasks
Securing Azure SQL resources and data
Interconnecting Azure SQL resources with other Azure services
Monitoring and optimizing Azure SQL Database performance
Maintaining business continuity for Azure SQL resources
Processes for migrating on-premises SQL Server databases to Azure
Other options for managing relational data in Azure
This course also prepares exam candidates to pass the DP-300: Administering Relational Databases on Microsoft Azure exam to attain the Azure Database Administrator Associate certification. Candidates for the exam are presumed to be database administrators and data management specialists that manage on-premises and cloud relational databases built on top of Microsoft SQL Server and Microsoft Azure data services.

Homepage

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Android Development: Android App Development From Scratch

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Android Development: Android App Development From Scratch
Duration: 18h 31m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 9.05 GB
Genre: eLearning | Language: English

Learn Java. Learn Android App development with Android Oreo. Use Android Studio like a pro. Become an App Developer!

What you'll learn
Android is the most used operating system on the planet
Learn Android App Development step by step
Learn Java
Learn the most popular Android version ( Oreo )
Android 8
Android Studio
Gradle Build System
Android Components
Learn Publishing Android App on Google Play
Learn Releasing Android App
We continually update the course, so you'll learn the very latest as Android Oreo ( Android 8 )
Become a professional Anroid App developer
No previous experience is required!
No programming knowledge required!
Enroll now, start your own App business and work from anywhere in the world

Requirements
No prior knowledge is required!
No programming knowledge required!
A Windows PC, Mac or Linux Computer
Internet and Basic Computer Knowledge
Desire to learn Android Application Development
Nothing else! It's just you, your computer and your ambition to get started today
Don`t worry. Setup and installation instructions are included for each platform


Description
Hi there,

Welcome to Android Development: Android App Development From Scratch course.

Do you want to improve your career options by learning Android app Development?

Do you want to learn Android Development from Scratch?

Do you want to be an Android Studio master?

Do you want to build your first app?

If your answer is "yes" to these questions and if you want more, you are at the right place!

Android is the most used operating system on the planet. In fact, it's almost omnipresent in the mobile ecosystem and Android Oreo has become the most popular Android version.

My "Android Development: Android App Development From Scratch" course will take you from beginner to advance level.

You will learn Android development step-by-step with hands-on demonstrations. In this course, we will learn to build and publish 2 major apps. During the lectures, we will also be practicing with more than 10 examples.

What's important

There're a lot of people out there teaching Android 8 who are not developers. We're developers with many years' field experience with the Android platform. So you will learn from an expert who has great knowledge of Android. This course is expertly designed to teach everyone from complete beginners, right through to professionals as a refresher.

In this course you will learn;

Java Environment Setup

Java Development Environment

Java Syntax

Java Object Oriented Concept

Java Strings

Android Environment Setup - Download, install and configure the necessary software

Creating a New Project

Android Studio

Android Components

Components and Life Cycles

Publishing Your App on Google Play and more

Why would you want to take this course?

Our answer is simple: The quality of teaching.

When you enroll, you will feel the OAK Academy's seasoned instructors' expertise.

Fresh Content

It's no secret how technology is advancing at a rapid rate. New tools are released every day, Google updates Android and it's crucial to stay on top of the latest knowledge. With this course, you will always have a chance to follow the latest trends.

Video and Audio Production Quality

All our contents are created/produced as high-quality video/audio to provide you the best learning experience.

You will be,

· Seeing clearly

· Hearing clearly

· Moving through the course without distractions

You'll also get:

Lifetime Access to The Course

Fast & Friendly Support in the Q&A section

Udemy Certificate of Completion Ready for Download

Dive in now!

We offer full support, answering any questions.

See you in the course!


Who this course is for:
A total beginner, with a curious mind and wants to be an app developer
Anyone who wants to learn to code
Anyone who wants to become an Android Developer
Programmers who are interested in building Android apps
Anyone who wants to create Android Applications
Anyone who has no previous coding experience but wants to become expert
Anyone who wants to learn Android 8 ( Android Oreo )
Anyone who are planning job transformation
Anyone who would like to work from anywhere in the world

Homepage

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Unreal Engine Game Environment Design MasterClass

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Unreal Engine Game Environment Design MasterClass
Nabil Kechiche | Duration: 45h 12m | Video: H264 1280x720 | Audio: AAC 48 kHz 2ch | 45,9 GB | Language: English

Learn How to Create AAA game environment using unreal engine 4

In this course, we will create a professional, next-gen-game environment using state of the art tools and resources
Here are few of the main points we'll cover in this course:

- How to properly use Megascans and Unreal Engine 4 to create ray traced game environments
- Use tiled textures from Megascans to create modular pieces or custom pieces. We will make around 35-40 custom pieces using 3Dsmax and I will show you how, step-by-step.
- Setup a wide variety of advanced shaders in Unreal Engine 4
- Learn how to make every portion of the environment blend together very well to create a single seamless world
- How to properly use and reuse decals
- Using foliage to enhance the scene look by placing them in a smart way.
- Create custom masks for things like window glass using Substance Painter
- Learn how to customise Megascans PBR textures to make them more usable and to suit your environment
- How to enhance and carry out storytelling through your level design
- How to fake destroyed assets such as ruins of buildings and walls
- Use Unreal Engine's Blueprints system to create splines tools that support both instancing and procedural meshes.
- Make sure the Blueprints tools we created are extensible and artist-friendly
- We will cover a bit of VFX and their shaders to help bring the scene to life
- Lighting is key to bring everything together and create truly beautiful worlds. You will learn how to beautifully light your scene and present it in the best possible way. You will also learn how to optimise lightning alongside ray tracing and post-process effects
- AND MUCH, MUCH MORE ...

The best way to describe this course is: become a one-man army. It's not for beginners as I won't cover the basics but if you've got a handle on artist tools then get strapped-in for quite the ride! There are no time lapse sequences and no pre-planned segments. Students will be able to follow me live digging my way to the end. I'll be showing and explaining every little step along the way, allowing you to follow along in real-time or watch at your leisure.

Homepage

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Railway Systems Engineering | (Equivalent to Micro MSc)

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Railway Systems Engineering | (Equivalent to Micro MSc)
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 75 lectures (15h 52m) | Size: 9.25 GB

A Journey in the World of Railway Systems | Operation | Rolling Stock | Traction | System Engineering | Infrastructure

What you'll learn:
Introduction to Railway Systems Engineering
Railway Systems Planning and Operations
Railway Rolling Stock Systems
Railway Traction Systems
Railway Systems Engineering
Railway Infrastructure Systems
Railway Signaling & Train Control Systems
Railway Economics and Strategic Management

Requirements
A BSc in an Engineering Discipline is preferable.
Great interest in Railway Engineering


Description
This course represents a comprehensive explanation for railway systems. It can be described as a Micro MSc in Railway Systems, I will include the following chapters: -

1- Introduction to Railway Operations and Management.
In this section, you will learn about Railway Operations Management | Railway Safety Management | Rail History and Railway Systems Complexity and more.

2- Introduction to Railway Rolling Stock
In this section, you will learn about Railway Rolling Stock and many scientific disciplines associated with this subject, including Railway Aerodynamics, Railway Vehicle Dynamics, Railway Materials and More.

3- Introduction to Railway Traction Systems.

In this section, you will learn about Railway Traction Systems, AC and DC Motors, Railway Power Supply systems and a brief introduction to power Electronics.

4- Introduction to Railway Systems Engineering.
In this section, you will learn about the discipline of systems engineering and how you can apply this discipline in the world of railways.

5- Introduction to Railway Infrastructure Systems.
In this section you will learn about Railway infrastructure systems such as Track, Station, Tunnels, bridges and Switches and Crossings, but you will also learn about railway construction and maintenance.

6- Introduction to Railway Signaling and Train Control Systems.
In this section, you will learn about Railway Infrastructure Signaling and Control systems, including European Railway Traffic Management System (ERTMS), ETCS signaling as well three and four aspects signaling.

7- Introduction to Railway Economics and Strategic Management.
In this section, we will provide you with a brief introduction to the world of railway economics and strategic management.

8- Questions Thursdays
Students will be able to ask questions and we will be answering them and adding them to the course materials, we will have a zoom meeting Every Thursday at 1:00 PM GMT.

9- Innovations Wednesday
We will be introducing Rail innovation and Small to Medium Size Companies every Wednesday at 1:00 PM GMT.

This course represent a comprehensive explanation for railway systems that is useful for Professionals who are working in the railway field. It also represent a great introduction to students who are studying any engineering dripline and would like to know more about the railway world.

The course is being delivered by leader Feras Naser, who is one of the most innovative spirits in the world, his story of venturing to the railway industry is remarkable. You will enjoy this course and it will act as a great reference for any railway professional. You can know more about Feras by visiting his group Feras Naser or his university Feras Uni or his transport consultancy Transport Men

Feras is keen to help the next generation of entrepreneurs and innovators as well the next generation of railway engineers.

Who this course is for
Railway Professionals and Engineering
4th year Engineering Students
Researchers in Railway Topics

Homepage

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Modern Bare-Metal Embedded C++ Programming from Ground Up™ (Update)

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Modern Bare-Metal Embedded C++ Programming from Ground Up™ (Update)
MP4 | Video: h264, 1280x720 | Audio: AAC, 44100 Hz
Language: English | Size: 8.02 GB | Duration: 17h 56m



What you'll learn
Write Class Templates for accessing Microcontroller Registers
Write Object-Oriented Peripheral Drivers
Master Object-Oriented Techniques for Microcontrollers
Master C++ Templates for Microcontrollers
Master how to read Datasheets of Microcontrollers
Write Universal Asynchronous Receiver-Transmitter (UART) drivers using bare-metal Embedded-C++
Write General Purpose Timer (GPTM) drivers using bare-metal Embedded-C++
Write System Tick (SysTick) Timer drivers using bare-metal Embedded-C++
Write Pulse Width Modulation (PWM) drivers using bare-metal Embedded-C++
Write Analog-to-Digital Converter (ADC) drivers using bare-metal Embedded-C++
Write Interrupt drivers using bare-metal Embedded-C++
Write Serial Peripheral Interface (SPI) drivers using bare-metal Embedded-C++
Write Inter-Integrated Circuit (I2C) drivers using bare-metal Embedded-C++
Requirements
STM32F411- NUCLEO BOARD

Description
Welcome to the Modern Embedded C++ Bare Metal course.

This is a practical programming course on embedded systems programming using the C++ programming language. Key features of C++ such as template programming and object-oriented programming can greatly improve embedded software portability, in recent years this has made C++ very attractive to embedded developers.

The goal of this course is to teach you how to navigate the microntroller reference manual and datasheet to extract the right information to professionally build peripheral drivers and firmware. To achieve this goal, no libraries are used in this course, purely bare-metal Embedded-C++ and register manipulations.

By the end of this course you will be able write drivers for peripherals like ADC, UART, PWM, GPIO, TIMER,I2C, SPI, etc. You will also master the ARM architecture and how to build professional embedded firmware for ARM processors.

Furthermore, you will master C++ key features like Object-Oriented methods, Template Programming, and optimization.

Highlights :

-------------------

Write Class Templates for accessing Microcontroller Registers

Write Object-Oriented Peripheral Drivers

Master Object-Oriented Techniques for Microcontrollers

Master C++ Templates for Microcontrollers

Master how to read Datasheets of Microcontrollers

Write Universal Asynchronous Receiver-Transmitter (UART) drivers using bare-metal Embedded-C++

Write General Purpose Timer (GPTM) drivers using bare-metal Embedded-C++

Write System Tick (SysTick) Timer drivers using bare-metal Embedded-C++

Write Pulse Width Modulation (PWM) drivers using bare-metal Embedded-C++

Write Analog-to-Digital Converter (ADC) drivers using bare-metal Embedded-C++

Write Interrupt drivers using bare-metal Embedded-C++

Write Serial Peripheral Interface (SPI) drivers using bare-metal Embedded-C++

Write Inter-Integrated Circuit (I2C) drivers using bare-metal Embedded-C++


Who this course is for:
If you are an absolute beginner to embedded systems, then take this course.
If you are an experienced embedded developer and want to learn how to professionally develop embedded applications for ARM processors, then take this course.
If you want to develop embedded firmware and drivers using the C++ programming language, then take this course.


Homepage

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Fundamentals of Mathematics - udemy

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Fundamentals of Mathematics - udemy
MP4 | Video: h264, 1280x720 | Audio: AAC, 48000 Hz
Language: English | Size: 6.12 GB | Duration: 11h 37m



What you'll learn
SETS: Introduction, Names, Types and Forms of sets. Solve numerical problems
SET OPERATIONS: Introduction, types, properties, laws of set operation.
DE MORGRAN'S LAWS: De Morgan's First Law and De Morgan's Second Law with relevant examples
VENN DIAGRAMS: Venn diagrams for subsets, disjoint, overlapping, complement and difference of sets. Then some solved numericals
BINARY OPERATIONS: Introduction, Properties, Addition Laws, Multiplication Laws with applications and some solved problems
NUMBER SYSTEM: Real numbers, Complex numbers, Derivations, Verification, conjugate, modulus, Properties of equality & Inequality, Addition Laws, Multiplication Laws and some solved problems
COORDINATE SYSTEM: Cartesian coordinate system; x-y plane, complex plane, Polar coordinate system; real plane, complex plane. Some solved numerical problems
GROUPS: Categories; Groupoid, Monoid, Semi-Group, Group, Abelian Group. Some solved problems
Requirements
Be able to know the very basic algebra operations

Description
Learn the Fundamental of Mathematics through animation. This course includes videos explanation starting right from introduction and basics, then takes graphical and numerical phase with formulas, verification and proofs. At the end it carries plenty of solved numerical problems with the relevant examples. The lectures' videos are appealing, attractive, fancy (with some nice graphic designing), fast and take less time to walk you through the whole lecture. It's a prefect choice for students who feel boredom watching long lectures and wants things to finish them quickly with the maximum knowledge gain. So join me here and do it in a quick and easy way. This course covers the below list of topics:

Sets

Introduction

Names

Types

Forms

Numerical problems

Set Operations

Introduction

Types

Properties

Laws of set operation

De Morgan's Laws

De Morgan's First Law

De Morgan's Second Law

Relevant examples

Venn Diagrams

Venn diagrams for subset of sets

Venn diagrams for disjoint of sets

Venn diagrams for overlapping of sets

Venn diagrams for complement of sets

Venn diagrams for difference of sets.

Some solved problems

Binary Operations

Introduction

Properties

Addition Laws with applications

Multiplication Laws with applications

Some solved problems

Numerical System

Real numbers

Complex numbers

Derivations & Verification

Conjugate of complex numbers

modulus of complex numbers

Properties of equality & Inequality

Addition Laws

Multiplication Laws

Solved Problems

Coordinate System

Cartesian coordinate system

X-Y plane

Cartesian coordinate system

X-Y plane

Complex plane

Polar coordinate system

Real plane & complex plane

Solved numerical problems

Groups

Categories

Groupoid

Monoid

Semi-Group

Group

Abelian Group

Some solved problems


Who this course is for:
Beginners at school and college level


Homepage

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