Becoming a hitmaker with Scott Storch
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Becoming a hitmaker with Scott Storch
Scott Storch | Duration: 2h 00m | Video: H264 1920x1080 | Audio: AAC 48 kHz 2ch | 7,51 GB | Language: English
Discover the hitmaking workflow that made him a legend. The 8x Grammy-winning producer
in his first-ever Masterclass
Get inside his hits
Learn from the mastermind producer behind hits like Dr. Dre's 'Still D.R.E.' and 50 Cent's 'Candy Shop'. You'll discover everything from his keyboard techniques to keeping things simple, composing strong melodies that make great tracks, looking for the perfect imperfection and finding that one sonic element which makes a track special.
Watch him create step by step
Follow his workflow for the first time as he lays out how to create a track from scratch. Watch him progress quickly and follow his range of techniques - how he lays the foundations, the plugins he uses when picking the sounds, how he defines the song's structure and chooses the right tempo, and adds 808s to his beat.
Grasp the keys to his sound
Pick up on the valuable insights from the 30-year career of one of the most famous record producers of all time. Discover his methods for working with labels and major artists, dealing with egos in the studio and building a good vibe to get the best results from a session.
Homepage
Code:
https://anonymz.com/?https://www.aulart.com/masterclass/scott-storch-becoming-a-hitmaker/
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Code:
https://k2s.cc/file/928d8d8352d62/Scott_Storch_-_Becoming_a_hit_maker.part1.rar
https://k2s.cc/file/aa6577c772485/Scott_Storch_-_Becoming_a_hit_maker.part2.rar
Code:
https://rapidgator.net/file/1e2ea3bb29c2f15466cb97fc6f1aee6b/Scott_Storch_-_Becoming_a_hit_maker.part1.rar.html
https://rapidgator.net/file/518adbafc06041e8ae04f0c39613bad8/Scott_Storch_-_Becoming_a_hit_maker.part2.rar.html
AWS Certified Machine Learning Specialty (MLS-C01)
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AWS Certified Machine Learning Specialty (MLS-C01)
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 5.5 GB | Duration: 234 lectures • 17h 36m
Hands on AWS ML SageMaker Course with Practice Test. Join Live Study Group Q&A!
What you'll learn
You will gain first-hand experience on how to train, optimize, deploy, and integrate ML in AWS cloud
AWS Built-in algorithms, Bring Your Own, Ready-to-use AI capabilities
Complete Guide to AWS Certified Machine Learning - Specialty (MLS-C01)
Includes a high-quality Timed practice test (a lot of courses charge a separate fee for practice test)
Zero Downtime Model Deployment
How to Integrate and Invoke ML from your Application
Automated Hyperparameter Tuning
Requirements
Familiarity with Python
AWS Account - I will walk through steps to setup one
Basic knowledge of Pandas, Numpy, Matplotlib
Be an active learner and use course discussion forum if you need help - Please don't put help needed items in course review
Description
Learn about cloud based machine learning algorithms, how to integrate with your applications and Certification Prep
*** NEW Labs - A/B Testing, Multi-model endpoints ***
*** NEW section Emerging AI Trends and Social Issues. How to detect a biased solution, ensure model fairness and prove the fairness ***
*** New Endpoint focused section on how to make SageMaker Endpoint Changes with Zero Downtime ***
*** Lab notebook now use spot-training as the default option. Save over 60% in training costs ***
*** NEW: Nuts and Bolts of Optimization, quizzes ***
*** All code examples and Labs were updated to use version 2.x of the SageMaker Python SDK ***
*** Anomaly Detection with Random Cut Forest - Learn the intuition behind anomaly detection using Random Cut Forest. With labs. ***
*** Bring Your Own Algorithm - We take a behind the scene look at the SageMaker Training and Hosting Infrastructure for your own algorithms. With Labs ***
*** Timed Practice Test and additional lectures for Exam Preparation added
Welcome to AWS Machine Learning Specialty Course!
I am Chandra Lingam, and I am your instructor
In this course, you will gain first-hand SageMaker experience with many hands-on labs that demonstrates specific concepts
We start with how to set up your SageMaker environment
If you are new to ML, you will learn how to handle mixed data types, missing data, and how to verify the quality of the model
These topics are very important for an ML practitioner as well as for the certification exam
SageMaker uses containers to wrap your favorite algorithms and frameworks such as Pytorch, and TensorFlow
The advantage of a container-based approach is it provides a standard interface to build and deploy your models
It is also straightforward to convert your model into a production application
In a series of concise labs, you will in fact train, deploy, and invoke your first SageMaker model
Like any other software project, ML Solution also requires continuous improvement
We look at how to safely incorporate new changes in a production system, perform A/B testing, and even rollback changes when necessary
All with zero downtime to your application
We then look at emerging social trends on the fairness of Machine learning and AI systems.
What will you do if your users accuse your model as racially biased or gender-biased? How will you handle it?
In this section, we look at the concept of fairness, how to explain a decision made by the model, different types of bias, and how to measure them
We then look at Cloud security - how to protect your data and model from unauthorized use
You will also learn about recommender systems to incorporate features such as movie and product recommendation
The algorithms that you learn in the course are state of the art, and tuning them for your dataset is especially challenging
So, we look at how to tune your model with automated tools
You will gain experience in time series forecasting
Anomaly detection and building custom deep learning models
With the knowledge, you gain here and the included high-quality practice exam, you will easily achieve the certification!
And something unique that I offer my students is a weekly study group meeting to discuss and clarify any questions
I am looking forward to seeing you!
Thank you!
Who this course is for
This course is designed for anyone who is interested in AWS cloud based machine learning and data science
AWS Certified Machine Learning - Specialty Preparation
Homepage
Code:
https://anonymz.com/?https://www.udemy.com/course/aws-machine-learning-a-complete-guide-with-python
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Code:
https://k2s.cc/file/c7cf406d061e7/AWS_Certified_Machine_Learning_Specialty_(MLS-C01).part1.rar
https://k2s.cc/file/3d895acee8f6e/AWS_Certified_Machine_Learning_Specialty_(MLS-C01).part2.rar
Code:
https://rapidgator.net/file/d37662a173d9699b96e158760c7b95b1/AWS_Certified_Machine_Learning_Specialty_(MLS-C01).part1.rar.html
https://rapidgator.net/file/802988d7a7903607f021ff67db969239/AWS_Certified_Machine_Learning_Specialty_(MLS-C01).part2.rar.html
HTML JavaScript & AspNet C# Programming : Beginner to Expert
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HTML JavaScript & AspNet C# Programming : Beginner to Expert
Published 06/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 142 lectures (16h 32m) | Size: 6.3 GB
Learn HTML, JavaScript and C# Basic Concepts, OOP C# programming techniques and methods for Object Oriented Programming
What you'll learn
Create web applications and websites
Get a job as a aspnet application developer
Create your own stunning, html layouts for awesome websites
Start your own online business
Master front-end development using HTML & JavaScript code development using C# language
Add Client-Side interaction to Web Pages using JavaScript
Apply HTML, JavaScript and aspnet C# Beginner to start code on real-world tasks
Learn to apply fully function dynamic web applications using Microsoft C# coding
Requirements
No programming experience needed. You will learn everything you need to know
No software is required in advance of the course (all software used in the course is free)
No pre-knowledge is required - you will learn from basic
Description
In this course, we will learn the basic tools that every web developer needs to know. We will start from the scratch by learning how to implement trending web development with HTML, JavaScript and Aspnet C# language.
Learn to code HTML, JavaScript and C# is The first step to Coding you need to learn to succeed in application development, it is easy to learn and understand our online HTML, JavaScript and C# basic with object oriented programming Training course is designed for you with the complete steps to require learn Complete Application Developer topics. Mr. Sekhar Metla[MCP - Microsoft Certified Professional] will explain to you even complex topics to simplify and teach you even beginners can easily understand with real-time examples.
At this Application Development course is without a doubt the most comprehensive development course available online. Even if you have zero programming experience, this course will take you from beginner to mastery. Here's why
The course is taught by the lead instructor having 20+ years of professional experience.
Become a Full-Stack Developer with just ONE course. HTML, JavaScript and Microsoft C# language
The course has been updated to be trending technology ready and you'll be learning the latest tools and technologies used at large companies such as Microsoft, Facebook, Google and Netflix.
The curriculum was developed over a period of four years, with comprehensive student testing and feedback who are working and applying these coding examples.
We've taught many students how to code and many have gone on to change their lives by becoming professional developers or starting their own tech startup.
The course is constantly updated with new content, with new projects and modules determined by students - that's you!
We'll take you step-by-step through engaging video tutorials and teach you everything you need to know to succeed as a web or application developer.
Learn HTML, JavaScript and C# Basic Concepts, OOP C# programming techniques and methods for Object Oriented Programming
The course includes HD video tutorials and builds your programming knowledge while making real-world websites and web apps.
Throughout this comprehensive course, we cover a massive amount of tools and technologies, including
Front-End Web Development
HTML 5
Website layout
JavaScript
Validations
Microsoft C# coding
Datatypes
Strings
Control flow statements
Code Development
Web Design
Functions
Methods
Object oriented programming
Class, Objects
Inheritance
Polymorphism
Abstraction
Interfaces
Error Handling
By the end of this course, you will be fluently programming and be ready to make any application you can dream of.
Sign up today, and look forward to
HD Video Lectures
Code Challenges and Coding Exercises
Beautiful Real-World dynamic Projects
ABOUT YOUR INSTRUCTOR
Sekhar Metla is a software engineer with 20 years of professional experience. He is the author of several online-selling courses with more than 30,000+ students in many countries. He has a Master of Science in Computer Applications as Software Engineering. His students describe him as passionate, pragmatic, and motivational in his teaching.
What are you waiting join now to start learning how to make your own Application Developer Career TODAY :)
Who this course is for
Beginner HTML, JavaScript and AspNet C# developers curious about web development
Anyone who wants to generate new income streams
Anyone who wants to build websites
Anyone who wants to become financially independent
Anyone who wants to start their own business or become freelance
Anyone who wants to become a Full stack web developer
Anyone who wants to start AspNet Coding career
Code:
https://anonymz.com/?https://www.udemy.com/course/html-javascript-aspnet-csharp-programming-beginner-to-expert/
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Download from RapidGator
Code:
https://rapidgator.net/file/d8009bdd1578ecfbfd89e759681916b9/HTML_JavaScript__AspNet_C#_Programming__Beginner_to_Expert.part1.rar
https://rapidgator.net/file/5d3f65c0bd13e3235e4394ba1539ea0a/HTML_JavaScript__AspNet_C#_Programming__Beginner_to_Expert.part2.rar
https://rapidgator.net/file/3851d9d62cb3c71d467e0a22e3091074/HTML_JavaScript__AspNet_C#_Programming__Beginner_to_Expert.part3.rar
https://rapidgator.net/file/d853f570ee50e64f67e53b689bff2d79/HTML_JavaScript__AspNet_C#_Programming__Beginner_to_Expert.part4.rar
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Code:
https://k2s.cc/file/33aebe4fbe33d/HTML_JavaScript__AspNet_C%23_Programming__Beginner_to_Expert.part1.rar
https://k2s.cc/file/595b2c2fc9d4f/HTML_JavaScript__AspNet_C%23_Programming__Beginner_to_Expert.part2.rar
https://k2s.cc/file/726039b1ff129/HTML_JavaScript__AspNet_C%23_Programming__Beginner_to_Expert.part3.rar
https://k2s.cc/file/2fcdceb0e1935/HTML_JavaScript__AspNet_C%23_Programming__Beginner_to_Expert.part4.rar
Spring and Spring Boot Fundamentals, 3E
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Spring and Spring Boot Fundamentals, 3E
Instructors: Ken Kousen
32 Lessons | Duration: 4h 4m
Video: MP4 1920x1080 44 KHz | English
October 2021 | Size: 8GB
What is this learning path about, and why is it important?
For many developers, Spring is the go-to framework for quickly and easily creating web-based enterprise applications. With its comprehensive ecosystem that includes an extensive array of tools and testing capabilities, Spring relieves developers of much of the drudge work when building out web-based, RESTful applications. Spring Boot helps out even further by enabling autoconfiguration of many of the tedious chores that you need to do when starting a new project.
In this updated learning path, designed for basic- to intermediate-level web application developers, you'll examine the Spring approach to development as you explore the fundamentals that drive this powerful application framework. You'll see how to build applications from scratch and then test and manage those applications. You'll also look at Spring's Model-View-Controller (MVC) framework as well as ways to save your data using the JdbcTemplate, JPA support, and Spring Data framework. When you've completed this learning path, you'll be well on your way to being able to rapidly create web-based, RESTful services and applications.
What you'll learn-and how you can apply it
How to create new applications with Spring
How to build web applications using Spring's MVC framework
How to create executable RESTful web services
How to persist data using Spring's JdbcTemplate, JPA support, and Spring Data framework
How to do transactional tests for your system
This learning path is for you because.
You're a developer who wants to write web apps or REST-based services
You have a Java background (or other related language) and want to work with Spring
You're interested in the Spring ecosystem of projects
Prerequisites
You should be comfortable with Java, either through training or equivalent experience
Some knowledge of web development techniques using a Model-View-Controller framework would be helpful, but is not required
Familiarity with persistence mechanisms for object-relational persistence (ORM), especially with tools like Hibernate, would be helpful
Materials or downloads needed in advance: None
About the Publisher
O'Reilly's mission is to change the world by sharing the knowledge of innovators. For over 40 years, we've inspired companies and individuals to do new things-and do things better-by providing them with the skills and understanding that's necessary for success.
Quote:
~/blogs/vamusicVA Music:[/url] Newest Music
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Code:
https://rapidgator.net/file/f8bd5f630431550fb17b5260675ef4ac/Spring_and_Spring_Boot_Fundamentals_3E.part1.rar
https://rapidgator.net/file/643d269b1ae8dd20947961bf79466de3/Spring_and_Spring_Boot_Fundamentals_3E.part2.rar
https://rapidgator.net/file/9db4c93d1e1129acaa6a3650fd1b6ba8/Spring_and_Spring_Boot_Fundamentals_3E.part3.rar
https://rapidgator.net/file/c945fa4c9d4485add215994b0205368d/Spring_and_Spring_Boot_Fundamentals_3E.part4.rar
Download from Keep2Share
Code:
https://k2s.cc/file/2b831f10dabd0/Spring_and_Spring_Boot_Fundamentals_3E.part1.rar
https://k2s.cc/file/bb0f229fb6e71/Spring_and_Spring_Boot_Fundamentals_3E.part2.rar
https://k2s.cc/file/f60338d4dfb51/Spring_and_Spring_Boot_Fundamentals_3E.part3.rar
https://k2s.cc/file/496598c642d58/Spring_and_Spring_Boot_Fundamentals_3E.part4.rar
Gaia - Open Minds - Season 10
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Gaia - Open Minds - Season 10
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + Subs | Duration: 16 Lessons (15h 27m) | Size: 24.4 GB
Host Regina Meredith conducts interviews with thought-provoking luminaries, cutting-edge visionaries and tireless researchers, providing crucial information to awaken viewers to new perspectives that spark awareness, understanding and ultimately, transformation.
Code:
https://anonymz.com/?https://www.gaia.com/series/open-minds?season=10
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Code:
https://rapidgator.net/file/a6cd6aad0e959af2381c0fb22990acc7/Open_Minds_-_Season_10.part01.rar
https://rapidgator.net/file/aa20e4aa5a500fe1c8267ed8e9fbaa20/Open_Minds_-_Season_10.part02.rar
https://rapidgator.net/file/eb2ab68c60a4bf6804a2615792104cff/Open_Minds_-_Season_10.part03.rar
https://rapidgator.net/file/1367dfda66afa5de1bd2ccacd4fff13d/Open_Minds_-_Season_10.part04.rar
https://rapidgator.net/file/6ccc7a1453afedba6d63652b55ff02f0/Open_Minds_-_Season_10.part05.rar
https://rapidgator.net/file/d633182e32b5f47b5e168770f0246517/Open_Minds_-_Season_10.part06.rar
https://rapidgator.net/file/b17695b1e1d7fd0fda477f14af02a9d9/Open_Minds_-_Season_10.part07.rar
https://rapidgator.net/file/5d5d5183fd78ec256a28d5c6c3355a40/Open_Minds_-_Season_10.part08.rar
https://rapidgator.net/file/f2d9b6f5888f1d777ea4e4458fce2ef5/Open_Minds_-_Season_10.part09.rar
https://rapidgator.net/file/c6451ab4d595a0d8de5acc0b71936d83/Open_Minds_-_Season_10.part10.rar
https://rapidgator.net/file/4243fbefcd55b6dea260365b81c88149/Open_Minds_-_Season_10.part11.rar
https://rapidgator.net/file/f344f88ffb19e5fca1a00486bea7cae0/Open_Minds_-_Season_10.part12.rar
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Code:
https://k2s.cc/file/668e7f4341e97/Open_Minds_-_Season_10.part01.rar
https://k2s.cc/file/915c7da8c22ec/Open_Minds_-_Season_10.part02.rar
https://k2s.cc/file/e847b2c14f27e/Open_Minds_-_Season_10.part03.rar
https://k2s.cc/file/a75257a2370da/Open_Minds_-_Season_10.part04.rar
https://k2s.cc/file/7c9ce593a4f60/Open_Minds_-_Season_10.part05.rar
https://k2s.cc/file/778be5409a44b/Open_Minds_-_Season_10.part06.rar
https://k2s.cc/file/1f7d8925763db/Open_Minds_-_Season_10.part07.rar
https://k2s.cc/file/1e6572f3ee7a0/Open_Minds_-_Season_10.part08.rar
https://k2s.cc/file/9c38571cff9da/Open_Minds_-_Season_10.part09.rar
https://k2s.cc/file/e93c48826a3e3/Open_Minds_-_Season_10.part10.rar
https://k2s.cc/file/abf2b44b9d1b4/Open_Minds_-_Season_10.part11.rar
https://k2s.cc/file/dc99121102e7e/Open_Minds_-_Season_10.part12.rar
CBTNuggets - Angular Basics Online Training
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CBTNuggets - Angular Basics Online Training
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 154 Lessons (26h 29m) | Size: 9 GB
This foundational Angular Basics training prepares app developers to write and develop with the Angular platform so that you can quickly build scalable web applications
Angular is a development platform that is increasingly popular because of how quickly a web application written in it can scale up from a one-person project to an enterprise-level tool. Angular relies on unique components and frameworks for building web applications that are easy to update, but also makes it challenging to code in without training.
This Angular Basics training will introduce even brand new developers or non-technical professionals to what a coding framework is and how the Angular platform speeds development and scaling.
For anyone who leads an IT team, this JavaScript training can be used to onboard new app developers, curated into individual or team training plans, or as a JavaScript reference resource.
Angular Basics: What You Need to Know
This Angular Basics training has videos that cover JavaScript libraries topics including
Building single-page client applications using HTML and TypeScript
Writing Angular components for easy templates and scalable development
Importing additional functionality to your applications with TypeScript Libraries
Using Angular modules to collect related code into functional sets for you
Who Should Take Angular Basics Training?
This Angular Basics training is considered foundational-level JavaScript training, which means it is valuable for new or aspiring IT professionals and non-technical professionals.
JavaScript basics. If Angular is your first language, that's great. This Angular Basics course will define all the general terms associated with development while explaining what makes Angular unique.
New or aspiring IT professionals. If you hope to become an app developer, or you've recently started your first application development job, this Angular Basics training will show you whether or not the Angular development platform is right for you and your projects. In addition to making you a more effective developer, it'll also explain the basics of using components, frameworks and development platforms so you can make better development choices throughout your entire career.
Code:
https://anonymz.com/?https://www.cbtnuggets.com/it-training/javascript/angular-basics
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Code:
https://rapidgator.net/file/5394ed741d68698d760b8745e6a79f84/Angular_Basics.part1.rar
https://rapidgator.net/file/8b25b48f5f0671292b0a7ef960031a5b/Angular_Basics.part2.rar
https://rapidgator.net/file/ada39e2dda34f80326f137ca4c3ddd99/Angular_Basics.part3.rar
https://rapidgator.net/file/9b3515e45a3308ff68ea0bc935b70f56/Angular_Basics.part4.rar
https://rapidgator.net/file/7a4f206f0a73eceded8750f377a13413/Angular_Basics.part5.rar
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Code:
https://k2s.cc/file/213a8a3748654/Angular_Basics.part1.rar
https://k2s.cc/file/a7c3d99ee8bc7/Angular_Basics.part2.rar
https://k2s.cc/file/cfb254e447ecc/Angular_Basics.part3.rar
https://k2s.cc/file/993e7c7792573/Angular_Basics.part4.rar
https://k2s.cc/file/7c582edb92f6b/Angular_Basics.part5.rar
English Grammar: From Advanced to Native
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English Grammar: From Advanced to Native
Published 06/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 51 lectures (4h 59m) | Size: 5 GB
Master complex English grammar rules through expert instruction from an English university lecturer
What you'll learn
Learn how to avoid common errors with words and phrases
Develop more effective and accurate use of modal verbs
Master complex choices between tenses
Build expertise in how to use articles
Grow in knowledge of how to use many other key grammatical points, such as using the passive form, advanced English phrases, inversion and cleft sentences.
Requirements
Students should be advanced learners of English (e.g. IELTS 6.0 or above, CEFR B2-C2)
Description
This course will help you raise your English level to become more like a native speaker. The teacher, Rupert, has created the course based upon his experience of teaching thousands of advanced English learners and the errors they make that prevent them from speaking or writing like a native.
Rupert is one of the most experienced and qualified English teachers on Udemy. He has taught English to degree, MA and PhD students at a British university for more than a decade, and his qualifications include a distinction at Masters level in Applied Linguistics and TEFL.
The course will teach you over 100 grammar points, and, in particular, contains 50 key grammar rules that all learners should be able to use confidently in order to appear native.
You will benefit from this course by
Learning how to avoid common errors with words and phrases
Developing more effective and accurate use of modal verbs
Mastering complex choices between tenses
Building expertise in how to use articles
Growing in knowledge of how to use many other key grammatical features, such as using the passive form, advanced English phrases, inversion and cleft sentences
Included in the course are
Short lectures looking at language points in detail
Practice tasks on each grammar point covered
The 50 key grammar rules in PDF form (included in "Resources" after the Introduction video)
A final test on the 50 key grammar rules
PDFs summarising all video lessons and tasks, with additional exercises
Because this is a course for advanced learners of English, Rupert goes straight to the points which he has found to cause advanced learners most difficulties, without spending undue time on less demanding points.
So, this course will be ideal for you if you are
A top advanced learner (e.g. C2 or IELTS 8.0+) who wants to check their knowledge of complex grammar points
A learner on the journey from being intermediate to advanced (B2-C1 or IELTS 6.0-7.5), who wishes to progress to a higher level of English
An English Language teacher who is starting out, and wants to grow in confidence in their teaching of the hardest grammatical structures
At an advanced level, learning needs differ from student to student. That is why I will be adding new videos regularly, based upon the mostly common requested topics. So, if there is a grammar point you would like to see added to the course, let me know in the questions and answers section.
Who this course is for
Advanced English learners seeking to perfect their English
Code:
https://anonymz.com/?https://www.udemy.com/course/english-grammar-from-advanced-to-native/
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Code:
https://rapidgator.net/file/66d1b48124f2a45baf4e0bf38fd2faa2/English_Grammar_From_Advanced_to_Native.part1.rar
https://rapidgator.net/file/7fd14c6ae492c171a397b4ca3303fbd9/English_Grammar_From_Advanced_to_Native.part2.rar
https://rapidgator.net/file/68256ddca7858275f000911e7ba9b33d/English_Grammar_From_Advanced_to_Native.part3.rar
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Code:
https://k2s.cc/file/a6851a8943a1a/English_Grammar_From_Advanced_to_Native.part1.rar
https://k2s.cc/file/f8b2299833640/English_Grammar_From_Advanced_to_Native.part2.rar
https://k2s.cc/file/bcde22904281e/English_Grammar_From_Advanced_to_Native.part3.rar
Data Science & Python - Maths, Models, Stats PLUS Case Study
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Data Science & Python - Maths, Models, Stats PLUS Case Study
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 10.8 GB | Duration: 14h 37m
Learn statistics, inferential tests, supervised & unsupervised learning, data science careers PLUS Python & libraries
What you'll learn
Introduce data and information concept
Identify difference between business intelligence and data science
Understand and learn process of data science
Define demand and challenges for data scientists
Identify the difference between dispersion and descriptive vs inferential statistics discussion
Learn after install anaconda steps to be follow
Learn spread of data discussion and inter quartile range
Define advantages of getting conditional probability based on example
Identify advantage of calculating z scores and other factors
Learn calculating p value and learning other factors on p value
Know the Prerequisites and Questions for a Data Scientist
Learn Types of Data Acquisition
Know Career Aspects for a Data Scientist
Discuss Mathematical and Statistical Concepts and Examples
Learn Descriptive and Inferential Statistics and factors of it
Learn how to use Jupyter application
Calculate variance and discussing other factors
Get Conditional Probability based on example
Learn what is Distribution and Probability Density
Learn Z test and finding percentage under the curve
Compare Mean and Variable discussion
Learn what is chi squared test and discussing based on example data
Learn Data Preprocessing in Python
Checking Array and Dimension Shape and Discussing on Encode Window
Learn why is data visualization is important and how to use it
Learn Parametric Methods and Algorithm Trade Off
Learning Classification and Concept on learning
Learn K means Clustering and Algorithm
Doing cluster and using sklearn on it and encoding other factors
Learn TP,TN,FP and FN of Confusion Matrix and Discussing accuracy
Learn Classification report and calculation on encoding window on Python
Requirements
No programming experience necessary, you will learn everything you need to know
Description
Get instant access to a 135-page workbook on Data Science, follow along and keep for reference
Introduce yourself to our community of students in this course and tell us your goals with data science
Encouragement and celebration of your progress every step of the way: 25% > 50% > 75% & 100%
Over 14 hours of clear and concise step by step instructions, lessons, and engagement
This data science course provides participants with the knowledge, skills and experience associated with Data Science. Students will explore a range of data science tools, algorithms, Machine Learning and statistical techniques, with the aim of discovering hidden insights and patterns from raw data in order to inform scientific business decision making.
What you will learn
Introduce data and information concept
Identify difference between business intelligence and data science
Understand and learn process of data science
Define demand and challenges for people working in data science
Identify the difference between dispersion and descriptive vs inferential statistics discussion
Learn after install anaconda steps to be follow
Learn spread of data discussion and inter quartile range
Define advantages of getting conditional probability based on example
Identify advantage of calculating z scores
Learn calculating p value and learning factors on p value
Know the Prerequisites and Questions for a Data Scientist
Types of Data Acquisition
Know Career Aspects for Data Science
Discuss Mathematical and Statistical Concepts and Examples
Descriptive and Inferential Statistics
how to use Jupyter application
Calculate variance
Get Conditional Probability based on example
Distribution and Probability Density
Z test and finding percentage under the curve
Compare Mean and Variable discussion
chi squared test and discussing based on example data
Data Preprocessing in Python
Checking Array and Dimension Shape and Discussing on Encode Window
Why is data visualization important in data science and how to use it
Parametric Methods and Algorithm Trade Off
Classification and Concept on learning
K means Clustering and Algorithm
Doing cluster and using sklearn on it and encoding
TP,TN,FP and FN of Confusion Matrix and Discussing accuracy
Classification report and calculation on encoding window on Python
...and more!
Contents and Overview
You'll start with Data and Information Concept; Difference between Business Intelligence and Data Science; Business Intelligence vs Data Science based on parameters factors; Prerequisites and Questions for a Data Scientist; Questions on applying as a Data Scientist - Statistics and Data Domain; Prerequisite on Business Intelligence and discussing tools on Data Science; Types of Data Acquisition; Data Preparation, Exploration, and its factors; Process of Data Science; Know Career Aspects for a Data Scientist; Demand and Challenges for Data Science; Discussion of Mathematical and Statistical Concepts and Examples; Discussing Variables - Numerical and Categorical; Discussing Qualitative Variables and Central Tendency; Dispersion and Descriptive vs Inferential Statistics Discussion.
Descriptive and Inferential Statistics; Descriptive Statistics, Examples and steps on installing Anaconda; Steps to follow after installing Anaconda; Using Jupyter on Anaconda Application; how to use Jupyter application; Continuation of Jupyter application, explanation, and discussion; Getting data and putting data on Jupyter; Minimizing data to be see on Jupyter app and bringing data from Excel; Explaining modes used on Jupyter app on Data statistics and Analysis; Variables - continues and categorical variable; Inputting and typing data on Jupyter app; Getting mean data on Jupyter based on example; How to summarize data of median and mean; Inputting quantiles data and explaining factors; Spread of data discussion and interquartile range; Interquartile range and inputting data; Variance averaged deviation on the mean; Calculating variance; Discussing degree of freedom based on variables and calculation; Introduction to probability and overview of the lesson; Getting Conditional Probability based on example; Continuation of example based on students data on probability; Make a new column for absences and column for pivot table; Calculating and encoding of the result of condition probability of students.
We will also cover Inferential statistics; Distribution and Probability Density; Gaussion Distribution; Define distribution parameters and graphing normal distribution; PDF and CDF - Cumulative Distribution Function; Learn what is Correlation Coefficient, Z score, and Z test; Calculating Z scores; What does Z scores tell you?; Z test and finding percentage under the curve; Getting the mean, getting data, hypothesis and comparing mean; Comparing Mean and Variable discussion; Continuing Z test, Calculating P test and continuing steps on Z test; Doing small Z test, Stats, and discussing factors; Null Hypothesis, run Z test, finding and defining P value; Calculating P value and learning factors on P value; T test, Diamond data test and mean of concerned value; how to import data set, t test and learning; Learn what is correlation coefficients, scatter plot , calculation; Getting scatter plot data correlation.
This course will also tackle chi squared test and discussing based on example data; Chi square test , getting data set and discussing factor; Chi2 contingency method discussion and result on data ci square test; Data Preprocessing in Python - Step 1: Importing the libraries; Step 2 importing data set; Step 3 handling the missing values; Step 3 continuation and factors; Step 4 Encoding categorical data; step 4 label encoding; step 5 Normalizing the data set; step 6 Splitting the data set; numpy and pandas and The numpy ndarray A multidimensional; Learn Checking Array and Dimension Shape and Discussing on Encode Window; Learn panda series and creating a panda series; data frame on panda series and know how to use reindex function; Learn Pandas Dataframe; Learn what is data visualization; why is data visualization is important and how to use it; Learn plotting libraries and know its steps; Learn what is machine learning; Learn Examples of Learning Problems, Research Fields, and Applications; Discussing the Learning Problem; Learn what is Prediction and its examples; Parametric Methods and Algorithm Trade Off; Supervised and Unsupervised Learning Terminology, and Regression vs Classification; Assessing model accuracy, Bias and Variance learning of methods and Test MS; Doing linear regression on code window; Doing scatter plot method to get linear regression; from sklearn linear model to linear regression regressor; Finding intercept regression or regressor and learning other factor; Sklearn import metrics and getting the final data on linear regression.
Next, we will discuss Learning Classification and Concept on learning; machine learning areas and Important concepts; Example of spam filter, Label data and unlabelled data, Training vs error; Classification has 2 step process, Issues Data preparation; Learning decision trees and sample problem; Learn Decision Tree Induction - Training dataset and discussing examples; Doing decision tree classification on Python; Importing some libraries and data, factors and format ; Continuation with understanding the data and discussing it; Checking on train test split and creating decision tree classified; Solution on tree plot tree too interpret data and what is Gini index, K means Clustering and Algorithm; Stopping/Convergence Criterion giving examples and Algorithm K means; Strength and weakness of K means and discussing factors; how clustering K means method works and learning factors; Combining data processing and getting data and encoding factors; Label encoding code to use, data encoding, using transform ; Doing cluster and using sklearn; Continuation of k-means clustering and other factor on coding Python; Preview on Data in sales and other factors and topic; Data science use cases in sales , Case study - future sales prediction ; Describing the data on mean standard deviation and factors; Load data, Removing the index column and Relationship between Predictor.
Then, how to change the default policy; Accuracy, MSE, RMSE, RSquare, Seaborn Library; machine learning model building; Evaluation metrics and different evaluation matrix and confusion matrix; TP,TN,FP and FN of Confusion Matrix and Discussing accuracy; precision, recall and F1 score in data science; Learn Classification report and calculation on encoding window on Python.
Who are the Instructors?
Laika Satish is your lead instructor - a professional making a living from teaching data science. As a data science expert, she has joined with content creator Peter Alkema to bring you this amazing new course.
You'll get premium support and feedback to help you become more confident with finance!
Our happiness guarantee...
We have a 30-day 100% money-back guarantee, so if you aren't happy with your purchase, we will refund your course - no questions asked!
We can't wait to see you on the course!
Enrol now, and we'll help you improve your data science skills!
Peter and Laika
Who this course is for
This course is for anyone interested in data science, machine learning, stats, probability and business intelligence
Code:
https://anonymz.com/?https://www.udemy.com/course/data-science-and-python/
[Only registered and activated users can see links. Click Here To Register...]
Download from RapidGator
Code:
https://rapidgator.net/file/931ad51c3c508e345bb664f122274c22/Data_Science__Python_-_Maths_Models_Stats_PLUS_Case_Study.part1.rar
https://rapidgator.net/file/48e26e93ccba7d7ba049ab502a97cc29/Data_Science__Python_-_Maths_Models_Stats_PLUS_Case_Study.part2.rar
https://rapidgator.net/file/dce36ae8617645a4d342b76fa59b5693/Data_Science__Python_-_Maths_Models_Stats_PLUS_Case_Study.part3.rar
https://rapidgator.net/file/f4f8f1298b8e3dbe8e08b9a37b106dc8/Data_Science__Python_-_Maths_Models_Stats_PLUS_Case_Study.part4.rar
https://rapidgator.net/file/043d12d0f33a75fb64451ee343531c0d/Data_Science__Python_-_Maths_Models_Stats_PLUS_Case_Study.part5.rar
https://rapidgator.net/file/6371496bb614273e443dee666a5cb53f/Data_Science__Python_-_Maths_Models_Stats_PLUS_Case_Study.part6.rar
Download from Keep2Share
Code:
https://k2s.cc/file/d444725e17eb5/Data_Science__Python_-_Maths_Models_Stats_PLUS_Case_Study.part1.rar
https://k2s.cc/file/14ab5966865b7/Data_Science__Python_-_Maths_Models_Stats_PLUS_Case_Study.part2.rar
https://k2s.cc/file/fc1ed8e4f8ea6/Data_Science__Python_-_Maths_Models_Stats_PLUS_Case_Study.part3.rar
https://k2s.cc/file/af99cc879cdf9/Data_Science__Python_-_Maths_Models_Stats_PLUS_Case_Study.part4.rar
https://k2s.cc/file/8b0644b576a3b/Data_Science__Python_-_Maths_Models_Stats_PLUS_Case_Study.part5.rar
https://k2s.cc/file/3a363f8f88d31/Data_Science__Python_-_Maths_Models_Stats_PLUS_Case_Study.part6.rar
Developing an Interactive Menu in Unreal Engine 5
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Developing an Interactive Menu in Unreal Engine 5
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz
Language: English | Size: 11.1 GB | Duration: 82 lectures • 15h 22m
What you'll learn
Learn Blueprints
Learn Niagara and VFX
Learn to make UI Art
Learn to create games in Unreal Engine 5
Requirements
A basic understanding on Unreal Engine 5 is required.
Description
In this course you will learn how to create a complete Game Feature in Unreal Engine 5 using the Style of Genshin Impact.
This course is not about showing you one part of game development, is about showing you the complete picture.
You will learn Blueprints, Niagara, Materials, UI and how to make them work together to create an entire Game Feature.
UI is one of the most least overlooked topics on Game Development and almost all games have one. To make a great UI is all about User Experience and that can make the difference between someone liking or disliking your game.
Learn Blueprints
You will learn the best practices used by professionals in Game Dvevelopment to create Widgets and organize them to create any kind of UI. Not only that but you will learn Blueprint Communication and connect your Gameplay with the UI creating a great User Experience.
Learn Niagara and VFX
You will learn how to decorate your Menu using Niagara and learn Materials to create magical effects. Niagara is one of the most important features in Unreal Engine and learning it can give you a huge advantage to make your games stand out from the croud.
Learn to make UI Art
You will learn how to decorate your widgets using Photoshop to create nice and stylish themes for your UI and enhance the User Experience.
Who this course is for
Beginner Game Developers who want to create games in Unreal Engine 5
Code:
https://anonymz.com/?https://www.udemy.com/course/developing-an-interactive-menu-in-unreal-engine-5/
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Download from RapidGator
Code:
https://rapidgator.net/file/ed6f48589e32d9c97054469f4286f917/Developing_an_Interactive_Menu_in_Unreal_Engine_5.part1.rar
https://rapidgator.net/file/62e42e181215bad9b660547952db2b04/Developing_an_Interactive_Menu_in_Unreal_Engine_5.part2.rar
https://rapidgator.net/file/89b992ed0f256f45dcd225e47e856fdf/Developing_an_Interactive_Menu_in_Unreal_Engine_5.part3.rar
https://rapidgator.net/file/4636969af10fae18781ff7fbce390944/Developing_an_Interactive_Menu_in_Unreal_Engine_5.part4.rar
https://rapidgator.net/file/efb864db4a1fa2ecd0adb0b4fee8eb31/Developing_an_Interactive_Menu_in_Unreal_Engine_5.part5.rar
https://rapidgator.net/file/46ad1c1a448d56ec900dee64e094e3a0/Developing_an_Interactive_Menu_in_Unreal_Engine_5.part6.rar
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Code:
https://k2s.cc/file/d87904ebd9be8/Developing_an_Interactive_Menu_in_Unreal_Engine_5.part1.rar
https://k2s.cc/file/326ebca99b903/Developing_an_Interactive_Menu_in_Unreal_Engine_5.part2.rar
https://k2s.cc/file/31cad7dd21b15/Developing_an_Interactive_Menu_in_Unreal_Engine_5.part3.rar
https://k2s.cc/file/a604e918c0408/Developing_an_Interactive_Menu_in_Unreal_Engine_5.part4.rar
https://k2s.cc/file/1f137e3c43971/Developing_an_Interactive_Menu_in_Unreal_Engine_5.part5.rar
https://k2s.cc/file/d6c461173dd37/Developing_an_Interactive_Menu_in_Unreal_Engine_5.part6.rar
Hands-On Application Of Vehicle Performance Using MATLAB
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Hands-On Application Of Vehicle Performance Using MATLAB
Published 06/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 26 lectures (8h 18m) | Size: 6.16 GB
Analyzing Vehicle Performance For Petrol,Hybrid And Electric Cars Using MATLAB From Zero to Hero
What you'll learn
Understand and analyze the different resisting forces that affect the vehicle while driving and build the mathematical resistance model of the vehicle.
Analyze Vehicle dynamics related to vehicle performance.
Study and generate the characteristic curves of a vehicle's engine and understand how an engine/motor torque is used by the vehicle to overcome road resistance.
Understand the influence of Resisting forces on vehicle Power requirements and Model the road resistances in MATLAB .
Understand and calculate the performance characteristics of a vehicle ( eg. max. Vehicle speed, Acceleration time, Max Grade, Electric vehicle Range)..
Understand vehicle Braking performance and How ABS is used to maintain vehicle stability in MATLAB.
Learn How to analyze the braking performance of the vehicle including braking efficiency.
Grab the Know-how of Predicting vehicle performance under certain required driving conditions .
Understand how different parameters influence vehicle performance.
Simulation of Vehicle Dynamics using the dynamic characteristic graph and determine vehicle power factor.
How to Analyze the factors affecting the power performance of an electric vehicle.
learn how to perfotm a driving range simulation for an electric vehicle at a constant speed.
Analyze the performance of (BEV, Battery-powered electric vehicle) based on power characteristics matching simulation of the vehicle transmission system.
Grab the Know-how of calculating and determining the electric motor power according to the vehicle resistance requirement.
Learn how to perform transmission system matching with MATLAB simulation for Extended range Electric Vehicles (E-REV) .
Learn How to select a motor that matches your designed electric vehicle requirements ( parameter matching ).
Grab the Know-how of performing a battery parameter matching to achieve the desired requirement for your designed electric vehicle.
Know how to perform Driving system matching simulation of a fuel cell electric vehicle.
Establishment of fuel cell matching mathematical model and Matching fuel cell parameters with MATLAB .
Cycle state of an electric vehicle - Driving range simulation according to NEDC driving cycle.
Analysis and simulation of the driving range of the electric vehicle under the NEDC driving cycle condition.
Study of factors affecting the driving range of an electric vehicle.
simulation of Electric vehicle transmission based on a conditional method to match NEDC cycle requirements.
learn how to match the driving motor parameters, power battery based on the NEDC working condition.
Requirements
Just basic knowledge of MATLAB,Mathematics,and Calculus.
Description
It is said that the best way to understand a theory is to put it into practice.
This course is an example-based course in which most of the lectures are given as problems that need to be solved through a proper understanding of the theoretical part. Thus, the student will be able to apply what he learns at a fast rate from one example to another.
What you are going to learn from this course
1-Understand and analyze the different resisting forces that affect the vehicle while driving and build the mathematical resistance model of the vehicle.
2-Analyze Vehicle dynamics that is related to vehicle performance.
3-Study and generate the characteristic curves of a vehicle's engine and understand how the engine/motor torque is used by the vehicle to overcome road resistances.
4-Understand the influence of Resisting forces on vehicle Power requirements and Model the road resistances in MATLAB.
5-Understand and calculate the performance characteristics of a vehicle ( eg. max. vehicle speed, Acceleration time, Max Grade, Electric vehicle Range).
6-Grab the Know-how of Predicting vehicle performance under certain required driving conditions.
7-Understand how different parameters influence vehicle performance.
8-Simulation of Vehicle Dynamics using the dynamic characteristic graph and determining vehicle power factor.
9-How to Analyze the factors affecting the power performance of an electric vehicle.
10-Learn how to Perform a Driving range simulation for an electric vehicle at a constant speed.
11-Analyzing the performance of (BEV, Battery-powered electric vehicle) based on power characteristics matching simulation of the vehicle transmission system.
12-Grab the Know-how of calculating and determining the electric motor power according to the vehicle resistance requirement.
13-Learn how to perform transmission system matching with MATLAB simulation for Extended-range Electric Vehicles (E-REV).
14-Learn how to select a motor that matches your designed electric vehicle requirements ( parameter matching ).
15-Grab the Know-how of performing a battery parameter matching to achieve the desired requirement for your designed electric vehicle.
16-Know how to Perform a Driving system matching simulation of a fuel cell electric vehicle.
17-Establishment of fuel cell matching mathematical model and Matching fuel cell parameters with MATLAB.
18-Know about cycle state of an electric vehicle -Driving range simulation according to NEDC driving cycle.
19-Analysis and simulation of the driving range of the electric vehicle under the NEDC driving cycle condition.
20-Study of factors affecting the driving range of an electric vehicle.
21-Simulation of Electric vehicle transmission based on a conditional method to match NEDC cycle requirements.
22-learn how to match the driving motor parameters, and power battery based on the NEDC working condition.
Who this course is for
You are a beginner to the field of vehicle dynamics and control
You are an enthusiast who wants to join and get insight into the Vehicle Control Field in the future
You want to join the fast-pace-developing field of designing and building your own electric vehicle.
You are research student who is new to Research Life and want to speed up the process of learning about the Automotive field
you are getting prepared to join a Master degree program in vehicle engnieering.
you are joining one of the vehicle engineering famous competitions (e.g. Formula student competition & Formula student electric challenge )
Code:
https://anonymz.com/?https://www.udemy.com/course/hands-on-application-of-vehicle-performance-using-matlab/
[Only registered and activated users can see links. Click Here To Register...]
Download from RapidGator
Code:
https://rapidgator.net/file/64deddb02e07cd8c0ab638612071bd94/Hands-On_Application_Of_Vehicle_Performance_Using_MATLAB.part1.rar
https://rapidgator.net/file/2225199b0a5aabf31304e8d980511af7/Hands-On_Application_Of_Vehicle_Performance_Using_MATLAB.part2.rar
https://rapidgator.net/file/6f4c7db73447b9320769a524c24194e6/Hands-On_Application_Of_Vehicle_Performance_Using_MATLAB.part3.rar
https://rapidgator.net/file/21d9e22c364d767d1d86f7fff9a380bc/Hands-On_Application_Of_Vehicle_Performance_Using_MATLAB.part4.rar
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Code:
https://k2s.cc/file/85f71af91956b/Hands-On_Application_Of_Vehicle_Performance_Using_MATLAB.part1.rar
https://k2s.cc/file/2928a6e83363d/Hands-On_Application_Of_Vehicle_Performance_Using_MATLAB.part2.rar
https://k2s.cc/file/2b4f9b2f4bd89/Hands-On_Application_Of_Vehicle_Performance_Using_MATLAB.part3.rar
https://k2s.cc/file/2804507847745/Hands-On_Application_Of_Vehicle_Performance_Using_MATLAB.part4.rar
