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[mitsumi1]

Create A Nice Professional Tropical House Music From Scratch
Published 4/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.79 GB | Duration: 3h 15m

I will show you how to create a professional EDM Tropical House Music using only our ears and without any inspiration

What you'll learn
how to create you chords by ears
how to mix you elements
how to use EQ and Reverb
how to create a melody by ears
how to layer your melody
how to add your percussions
how to create ambience elements of your music like the atmosphere background sound and the pads
how to use compression
how to use distortion
how to sidechain your elements and what are the elements that needs sidechain
how to create a nice Pre-intro Part
how to create a nice break
how to create a good build up and drop
how to create a nice vocal chops
how to master your song

Requirements
Basic Understanding Of FL Studio
Average Headphones
Average Computer

Description
Hi there, and welcome to this course where I will show you how to create a nice, professional, electronic tropical House Music in 3hours from scratch using FL Studio.So basically, in this course you won't be in need of any music theory because the whole process of making this song is going to be using only our ears, also you don't need to be inspired because the process of making this music was without any pre-ideas of the melody the chords...So basically, throughout this course you will be discovering the real process of how to make a song using FL studio because we will keep adding instruments and elements and making choices and replacing stuff and deleting stuff until we finish this song.In this course I tried to be as minimalistic in my video editing as possible so you can fully discover this process with me.In this Course I will show you how to make each section of this course starting from the pre intro until the outro with the mastering processAnd we will slowly keep building it until we end up with a one complete song of 3minutes long.So, don't forget to give me your feedback on this Course and I hope you like it and you learned something new today

Overview
Section 1: Starting The Intro & Break

Lecture 1 How To Create Your Main Chords Progressions And Humanize Them

Lecture 2 Structuring Your Playlist And Creating,Layering and Mixing Your Pads In

Lecture 3 How To Create A Nice Atmospheric Sound And Mix It

Lecture 4 Mixing The Piano and Creating A New Intro Arrangement

Lecture 5 Creating a Hihat and Mix it to fit the Vibe Of The Song

Section 2: Designing The Pluck & Creating Other Elements

Lecture 6 Sound Designing a Pluck and Mixing It

Lecture 7 Consolidating Your Chords and Adding your First Percussions

Lecture 8 Adding Arp and Sidechaining the Elements

Lecture 9 Creating The Pre Intro Section

Section 3: Build up & Drop Creation

Lecture 10 Starting the Build Up and Creating the Melodies

Lecture 11 Adding Multiple Elements To The Build Up

Lecture 12 Adjusting The Build Up And Starting The Drop

Lecture 13 Layering the Melody and Creating The Sub Bass

Section 4: Creating The Second Part of The Song

Lecture 14 Starting the 2nd Part Of The Song

Lecture 15 Creating the 2nd Build up And Drop

Lecture 16 Creating the Outro Section

Lecture 17 Creation Of The Vocal Chops

Section 5: Mastering The Last Result

Lecture 18 Mastering and Exporting The Final Result

People who are willing to learn how to produce EDM Music,People that like Electronic Music,People that want to learn how to make melodic music

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[mitsumi1]

Cyber Security Architecture Fundamentals
Published 4/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.87 GB | Duration: 3h 3m

Learn all the fundamentals and skills needed to become a security architect

What you'll learn
Understand the core concepts of security architecture
Develop and design security patterns
Work with Enterprise Architecture Frameworks
Properly run threat modelling

Requirements
Some knowledge of Cyber Security is required

Description
In this course, students will learn about the principles, concepts, and best practices of designing and implementing effective cyber security architectures. The course will cover a wide range of topics, including threat modeling, risk assessment, security design patterns, access control, cryptography, network security, cloud security, and incident response.Overview of Cyber Security ArchitectureThe course will begin with an overview of the fundamental concepts of cyber security architecture, and will then delve into the specifics of how to design and implement effective security solutions. Students will learn how to identify and assess security risks, and how to develop and apply appropriate security controls to mitigate those risks.Designing Effective Security SolutionsThroughout the course, students will also explore various security design patterns and strategies, and learn how to apply these to real-world security challenges. Additionally, students will gain hands-on experience with a range of security tools and technologies, and will develop practical skills in threat modeling, risk assessment, security testing, and incident response.Course Goals and Learning OutcomesBy the end of this course, students will have a deep understanding of the principles and best practices of cyber security architecture, and will be well-equipped to design, implement, and manage effective security solutions for a wide range of applications and environments.PrerequisitesThis course assumes a basic understanding of networking concepts and protocols, as well as some experience with programming and scripting languages. Students should also have some familiarity with common security tools and technologies, such as firewalls, intrusion detection/prevention systems, and vulnerability scanners.

Overview
Section 1: Introduction

Lecture 1 Introduction to Cyber Security

Lecture 2 The Problem with Security Today

Lecture 3 Introduction to Security Architecture

Lecture 4 Who is a Security Architect?

Lecture 5 Security Principles & Approaches

Lecture 6 Cyber Security Processes

Lecture 7 Risk Management

Lecture 8 Understanding Residual Risk

Section 2: Threat Modelling

Lecture 9 Threat Modelling - Part 1

Lecture 10 Threat Modelling vs Risk Assessment

Lecture 11 Threat Modelling - Part 2

Lecture 12 STRIDE

Lecture 13 DREAD

Lecture 14 PASTA

Lecture 15 OCTAVE

Lecture 16 TRIKE

Lecture 17 Attack Trees

Section 3: Enterprise Architecture Frameworks

Lecture 18 Section Preview

Lecture 19 TOGAF Framework

Lecture 20 Zachman Framework

Lecture 21 SABSA Framework

Section 4: Cyber Architecture for Enterprise Security

Lecture 22 Network Security

Lecture 23 Application Security

Lecture 24 Endpoint Security

Lecture 25 Identity & Access Management

Lecture 26 Data Protection

Lecture 27 Vulnerability, Patch & Availability Management

Lecture 28 Supply Chain Security

Section 5: Designing for Security

Lecture 29 Security Design Patterns

Lecture 30 Security Design Pattern Example

Lecture 31 Reference Security Architectures

Section 6: Case Study

Lecture 32 Case Study Preview

Lecture 33 Business Requirements

Lecture 34 Data Classification

Lecture 35 Threat Modelling

Lecture 36 Security Requirements

Lecture 37 Reference Architecture

Lecture 38 Identifying the Residual Risk

Section 7: Conclusion

Lecture 39 Conclusion

Cyber Security professionals who want to become security architects

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[mitsumi1]

Data Science And Machine Learning Fundamentals [Theory Only]
Published 4/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 648.92 MB | Duration: 2h 12m

Theorical Course for Data Science, Machine Learning, Deep Learning to understand the logic of Data Science algorithms

What you'll learn
Machine learning isn't just useful for predictive texting or smartphone voice recognition. Machine learning is constantly being applied to new industries.
What is Machine Learning?
Machine Learning Terminology
Evaluation Metrics
What are Classification vs Regression?
Evaluating Performance-Classification Error Metrics
Evaluating Performance-Regression Error Metrics
Supervised Learning
Cross Validation and Bias Variance Trade-Off
Linear Regression Algorithm
Logistic Regresion Algorithm
K Nearest Neighbors Algorithm
Decision Trees And Random Forest Algorithm
Support Vector Machine Algorithm
Unsupervised Learning
K Means Clustering Algorithm
Hierarchical Clustering Algorithm
Principal Component Analysis (PCA)
Recommender System Algorithm
Machine learning is one of the fastest-growing and popular computer science careers today. Constantly growing and evolving.
Python instructors on OAK Academy specialize in everything from software development to data analysis, and are known for their effective.
Machine learning describes systems that make predictions using a model trained on real-world data.
Requirements
Basic knowledge of Python Programming Language
Be Able To Operate & Install Software On A Computer
Free software and tools used during the machine learning a-z course
Free software and tools used during the machine learning a-z course
Determination to learn machine learning and patience.
Motivation to learn the the second largest number of job postings relative program language among all others
Curiosity for machine learning python
Desire to work on python machinace learning
Desire to learn machine learning a-z, complete machine learning
Any device you can watch the course, such as a mobile phone, computer or tablet.
Watching the lecture videos completely, to the end and in order.
Nothing else! It's just you, your computer and your ambition to get started today.
LIFETIME ACCESS, course updates, new content, anytime, anywhere, on any device.
Description
Hello there,Welcome to the "Data Science and Machine Learning Fundamentals[Theory Only]" course.Theorical Course for Data Science, Machine Learning, Deep Learning to understand the logic of Data Science algorithmsMachine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.You can develop the foundational skills you need to advance to building neural networks and creating more complex functions through the Python and R programming languages. Machine learning helps you stay ahead of new trends, technologies, and applications in this field.Machine learning describes systems that make predictions using a model trained on real-world data.Machine learning is being applied to virtually every field today. That includes medical diagnoses, facial recognition, weather forecasts, image processing, and more. In any situation in which pattern recognition, prediction, and analysis are critical, machine learning can be of use. Machine learning is often a disruptive technology when applied to new industries and niches. Machine learning engineers can find new ways to apply machine learning technology to optimize and automate existing processes. With the right data, you can use machine learning technology to identify extremely complex patterns and yield highly accurate predictions.It's hard to imagine our lives without machine learning. Predictive texting, email filtering, and virtual personal assistants like Amazon's Alexa and the iPhone's Siri, are all technologies that function based on machine learning algorithms and mathematical models. Python, machine learning, python programming, machine learning python, python for beginners, data science. Python instructors on OAK Academy specialize in everything from software development to data analysis, and are known for their effective, friendly instruction for students of all levels.Whether you work in machine learning or finance, or are pursuing a career in web development or data science, Python is one of the most important skills you can learn. Python's simple syntax is especially suited for desktop, web, and business applications. Python's design philosophy emphasizes readability and usability. Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization. The core programming language is quite small and the standard library is also large. In fact, Python's large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasks.We have more data than ever before. But data alone cannot tell us much about the world around us. We need to interpret the information and discover hidden patterns. This is where data science comes in. Data science uses algorithms to understand raw data. The main difference between data science and traditional data analysis is its focus on prediction. Data science seeks to find patterns in data and use those patterns to predict future data. It draws on machine learning to process large amounts of data, discover patterns, and predict trends. Data science includes preparing, analyzing, and processing data. It draws from many scientific fields, and as a science, it progresses by creating new algorithms to analyze data and validate current methodsDo you know data science needs will create 11.5 million job openings by 2026?Do you know the average salary is $100.000 for data science careers!Data Science Careers Are Shaping The FutureData science experts are needed in almost every field, from government security to dating apps. Millions of businesses and government departments rely on big data to succeed and better serve their customers. So data science careers are in high demand.If you want to learn one of the employer's most request skills?If you are curious about Data Science and looking to start your self-learning journey into the world of data with Python?If you are an experienced developer and looking for a landing in Data Science!In all cases, you are at the right place!We've designed for you "Machine Learning & Data Science with Python & Kaggle | A-Z" a straightforward course for Python Programming Language and Machine Learning.In the course, you will enter the world of Data science and machine learning with theory. Only by learning the theories will you grasp the logic of algorithms. You will understand why you do what you do and say hello to the magical world of data scienceThroughout the course, we will teach you how to use Python to analyze data, create beautiful visualizations, and use powerful machine learning python algorithms.This Machine Learning course is for everyone!If you don't have any previous experience, not a problem! This course is expertly designed to teach everyone from complete beginners, right through to professionals ( as a refresher).What is machine learning?Machine learning describes systems that make predictions using a model trained on real-world data. For example, let's say we want to build a system that can identify if a cat is in a picture. We first assemble many pictures to train our machine learning model. During this training phase, we feed pictures into the model, along with information around whether they contain a cat. While training, the model learns patterns in the images that are the most closely associated with cats. This model can then use the patterns learned during training to predict whether the new images that it's fed contain a cat. In this particular example, we might use a neural network to learn these patterns, but machine learning can be much simpler than that. Even fitting a line to a set of observed data points, and using that line to make new predictions, counts as a machine learning model.Why we use a Python programming language in Machine learning?Python is a general-purpose, high-level, and multi-purpose programming language. The best thing about Python is, it supports a lot of today's technology including vast libraries for Twitter, data mining, scientific calculations, designing, back-end server for websites, engineering simulations, artificial learning, augmented reality and what not! Also, it supports all kinds of App development.What is machine learning used for?Machine learning a-z is being applied to virtually every field today. That includes medical diagnoses, facial recognition, weather forecasts, image processing, and more. In any situation in which pattern recognition, prediction, and analysis are critical, machine learning can be of use. Machine learning is often a disruptive technology when applied to new industries and niches. Machine learning engineers can find new ways to apply machine learning technology to optimize and automate existing processes. With the right data, you can use machine learning technology to identify extremely complex patterns and yield highly accurate predictions.Does Machine learning require coding?It's possible to use machine learning data science without coding, but building new systems generally requires code. For example, Amazon's Rekognition service allows you to upload an image via a web browser, which then identifies objects in the image. This uses a pre-trained model, with no coding required. However, developing machine learning systems involves writing some Python code to train, tune, and deploy your models. It's hard to avoid writing code to pre-process the data feeding into your model. Most of the work done by a machine learning practitioner involves cleaning the data used to train the machine. They also perform "feature engineering" to find what data to use and how to prepare it for use in a machine learning model. Tools like AutoML and SageMaker automate the tuning of models. Often only a few lines of code can train a model and make predictions from itWhat is the best language for machine learning?Python is the most used language in machine learning using python. Engineers writing machine learning systems often use Jupyter Notebooks and Python together. Jupyter Notebooks is a web application that allows experimentation by creating and sharing documents that contain live code, equations, and more. Machine learning involves trial and error to see which hyperparameters and feature engineering choices work best. It's useful to have a development environment such as Python so that you don't need to compile and package code before running it each time. Python is not the only language choice for machine learning. Tensorflow is a popular framework for developing neural networks and offers a C++ API. There is a complete machine learning framework for C# called ML. NET. Scala or Java are sometimes used with Apache Spark to build machine learning systems that ingest massive data sets.What are the different types of machine learning?Machine learning is generally divided between supervised machine learning and unsupervised machine learning. In supervised machine learning, we train machine learning models on labeled data. For example, an algorithm meant to detect spam might ingest thousands of email addresses labeled 'spam' or 'not spam.' That trained model could then identify new spam emails even from data it's never seen. In unsupervised learning, a machine learning model looks for patterns in unstructured data. One type of unsupervised learning is clustering. In this example, a model could identify similar movies by studying their scripts or cast, then group the movies together into genres. This unsupervised model was not trained to know which genre a movie belongs to. Rather, it learned the genres by studying the attributes of the movies themselves. There are many techniques available within.Is Machine learning a good career?Machine learning python is one of the fastest-growing and popular computer science careers today. Constantly growing and evolving, you can apply machine learning to a variety of industries, from shipping and fulfillment to medical sciences. Machine learning engineers work to create artificial intelligence that can better identify patterns and solve problems. The machine learning discipline frequently deals with cutting-edge, disruptive technologies. However, because it has become a popular career choice, it can also be competitive. Aspiring machine learning engineers can differentiate themselves from the competition through certifications, boot camps, code repository submissions, and hands-on experience.What is the difference between machine learning and artifical intelligence?Machine learning is a smaller subset of the broader spectrum of artificial intelligence. While artificial intelligence describes any "intelligent machine" that can derive information and make decisions, machine learning describes a method by which it can do so. Through machine learning, applications can derive knowledge without the user explicitly giving out the information. This is one of the first and early steps toward "true artificial intelligence" and is extremely useful for numerous practical applications. In machine learning applications, an AI is fed sets of information. It learns from these sets of information about what to expect and what to predict. But it still has limitations. A machine learning engineer must ensure that the AI is fed the right information and can use its logic to analyze that information correctly.What skills should a machine learning engineer know?A python machine learning engineer will need to be an extremely competent programmer with in-depth knowledge of computer science, mathematics, data science, and artificial intelligence theory. Machine learning engineers must be able to dig deep into complex applications and their programming. As with other disciplines, there are entry-level machine learning engineers and machine learning engineers with high-level expertise. Python and R are two of the most popular languages within the machine learning field.What is data science?We have more data than ever before. But data alone cannot tell us much about the world around us. We need to interpret the information and discover hidden patterns. This is where data science comes in. Data science uses algorithms to understand raw data. The main difference between data science and traditional data analysis is its focus on prediction. Data science seeks to find patterns in data and use those patterns to predict future data. It draws on machine learning to process large amounts of data, discover patterns, and predict trends. Data science includes preparing, analyzing, and processing data. It draws from many scientific fields, and as a science, it progresses by creating new algorithms to analyze data and validate current methods.Why would you want to take this course?Our answer is simple: The quality of teaching.OAK Academy based in London is an online education company. OAK Academy gives education in the field of IT, Software, Design, development in English, Portuguese, Spanish, Turkish, and a lot of different languages on the Udemy platform where it has over 1000 hours of video education lessons. OAK Academy both increases its education series number by publishing new courses, and it makes students aware of all the innovations of already published courses by upgrading.When you enroll, you will feel the OAK Academy`s seasoned developers' expertise.*Questions sent by students to our instructors are answered by our instructors within 48 hours at the latest.Video and Audio Production QualityAll our videos are created/produced as high-quality video and audio to provide you the best learning experience.You will be,Seeing clearlyHearing clearlyMoving through the course without distractionsYou'll also get:Lifetime Access to The CourseFast & Friendly Support in the Q&A sectionUdemy Certificate of Completion Ready for DownloadWe offer full support, answering any questions.If you are ready to learn Dive in now into the "Data Science and Machine Learning Fundamentals[Theory Only]" course.Theorical Course for Data Science, Machine Learning, Deep Learning to understand the logic of Data Science algorithmsSee you in the course!
Overview
Section 1: Introduction to Machine Learning?
Lecture 1 What is Machine Learning?
Lecture 2 What are Machine Learning Terminologies?
Section 2: Evaluation Metrics in Machine Learning
Lecture 3 Classification vs Regression in Machine Learning
Lecture 4 Evaluating Performance: Classification Error Metrics
Lecture 5 Evaluating Performance: Regression Error Metrics
Section 3: Supervised Learning with Machine Learning
Lecture 6 What is Supervised Learning in Machine Learning?
Section 4: Supervised Learning Algorithms
Lecture 7 Linear Regression Algorithm Theory
Lecture 8 What is Bias Variance Trade-Off?
Lecture 9 Logistic Regression Algorithm Theory
Lecture 10 K-Fold Cross-Validation Theory
Lecture 11 Hyperparameter Optimization Theory
Lecture 12 K Nearest Neighbors Algorithm Theory
Lecture 13 Decision Tree Algorithm Theory
Lecture 14 Random Forest Algorithm Theory
Lecture 15 Support Vector Machine Algorithm Theory
Section 5: Unsupervised Learning with Machine Learning
Lecture 16 What is unsupervised Learning in Machine Learning?
Section 6: Unsupervised Learning Algorithms
Lecture 17 K Means Clustering Algorithm Theory
Lecture 18 Hierarchical Clustering Algorithm Theory
Lecture 19 Principal Component Analysis (PCA) Theory
Lecture 20 What is the Recommender System? Part 1
Lecture 21 What is the Recommender System? Part 2
Section 7: Extra
Lecture 22 Data Science and Machine Learning Fundamentals[Theory Only]
Machine learning isn't just useful for predictive texting or smartphone voice recognition. Machine learning is constantly being applied to new industries and new problems. It is for everyone,Anyone who wants to start learning "Machine Learning",Anyone who needs a complete guide on how to start and continue their career with machine learning,Students Interested in Beginning Data Science Applications in Python Environment,People Wanting to Specialize in Anaconda Python Environment for Data Science and Scientific Computing,Students Wanting to Learn the Application of Supervised Learning (Classification) on Real Data Using Python,Anyone eager to learn python for data science and machine learning bootcamp with no coding background,Anyone who plans a career in data scientist,,Software developer whom want to learn python,,People who want to become data scientist,People who want to learn machine learning a-z and data science

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[mitsumi1]

Data science for finance
Last updated 03/2023
Duration: 52m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 389 MB
Genre: eLearning | Language: English[Auto]

Learn to trade in stock market using machine learning and reinforcement learning techniques

What you'll learn
Use a variety of data preparation methods with financial data
Predict future prices using advance deep learning and reinforcement learning techniques
Get hands-on financial forecasting experience using machine learning with Python, Keras, Scikit-Learn and pandas
Predict future values based on single and multiple values
Understand the process behind choosing the best performing data preparation method and model
Grasp Machine Learning forecasting on a specific real-world financial data
Apply various AI techniques for prediction
Learn how to fetch stock data from api
Requirements
Basic python syntax
Description
You will learn about how to work with stock data using AI techniques like deep learning,machine learning and reinforcement learning.
While humans remain a big part of the trading equation, AI plays an increasingly significant role. According to a recent study electronic trades account for almost 45 percent of revenues in cash equities trading. And while hedge funds are more reluctant when it comes to automation, many of them use AI-powered analysis to get investment ideas and build portfolios.
AI is shaping the future of stock trading. Using AI, companies analyze millions of data points and execute trades at the optimal price, analysts forecast markets with greater accuracy and trading firms efficiently mitigate risk to provide for higher returns.
A lot of solutions to key problems in the financial world require predicting the future patterns in data from the past to make better financial decisions right now. The evolution of modern machine learning methods and tools in recent years in the field of computer vision bring promise of the same progress in other important fields such as financial forecasting.
In this course, you'll first learn how to quickly get started with ML in finances by predicting the future currency exchange rates using a simple modern machine learning method. In this example, you'll learn how to choose the basic data preparation method and model and then how to improve them. In the next module, you'll discover a variety of ways to prepare data and then see how they influence models training accuracy. In the last module, you'll learn how to find and test a few key modern machine learning models to pick up the best performing one.
After finishing this course, you'll have a solid introduction to apply ML methods to financial data forecasting.
Who this course is for
People who are interested to use AI in finance

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[mitsumi1]

Deep House Workflow with Fred Everything
Fred Everything | Duration: 8:58 h | Video: H264 1912x1078 | Audio: AAC 44,1 kHz 2ch | 4,11 GB | Language: English

Find your flow with Fred Everything, one of the true masters of Deep House, as he takes you through his hybrid workflow that integrates hardware synths, drum machines, and sequencers with software. Over 5 days, you'll discover the tools and techniques that earned him the title of Traxsource's #1 Deep House Producer in 2016. This course will cover topics such as songwriting, sound design, mixing, arrangement and more. This is your chance to learn from a real house legend in a live, interactive environment.

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[mitsumi1]

DevOps Tools for Beginners: Starting with Python Scripts
Last updated 03/2023
Duration: 3h 44m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 1.18 GB
Genre: eLearning | Language: English[Auto]

Start automating with Python

What you'll learn
Setup Python
Scripting with OS module basics
Working with paths
Working with files
Using shutil
And more...
Requirements
It's good to have Basic Linux knowledge
Laptop or PC running Windows, Mac OS X, or any Linux
Description
This course is A Beginner's Guide to DevOps Tools, such as Python. The purpose of this course is to prepare you to use these tools from scratch. This course is aimed for IT Pros, Developers, Operators, DevOps, System administrators and Everyone and is supposed to give the viewer the information they need to know to get started with theses tools and its their concepts.
The course is targeted to help learning and getting started with Python and do your job more efficiently and to automate your tasks.
After completing this course, you will be able to
Setup Python
Scripting with OS module basics
Working with paths
Working with files
Using shutil
Writing basic scripts in Python
And more...
Who this course is for
Starting DevOps
System Administrators
IT engineers
Starting Python Developers

Download link

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[mitsumi1]

Digestive System And Vitamins Course - Gastrointestinal Sys.
Published 4/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.28 GB | Duration: 3h 27m

Important topics for the digestive system.

What you'll learn
Digestive disorders and physiology
Updated guidelines in Gastroenterology
Food poisoning causes and management
Digestive system bacteria and infections
Medications used by gastroenterologists
Vitamines review
Pain Management
Gastroenterology oncology
Digestive system hormones
Important digestive structures
Case discussions
Requirements
No prior requirements needed
Description
The importance of the gastrointestinal system stems from the abundance of its patients. These conditions are very common and affect a large portion of the population. In many cases, we can treat these diseases by simple dietary and lifestyle changes, while other conditions require certain medications. This course focuses on the management as well as the presentation of each condition.The course discusses the following topics:The causes and treatment of food poisoning. We will discuss the exact mechanism of which these microbes cause symptoms, and how we eradicate them.Symptoms of each vitamin's deficiency. These symptoms can be tricky to spot, but once you understand the mechanism of each vitamin it becomes easier to grasp the signs of deficiency.High-yield conditions like Hemochromatosis, Jaundice, Celiac disease, Crohn's disease, Liver failure, and many more.Plasma fluid manipulation and diuretics.Important medications affecting the GI system.Pain management and the use of painkillers.Essential oncology topics (colon cancer, pancreatic cancer. etc)The course covers all the important topics in the GI system. The lectures are concise and focused on the essential notes. At the end of each section, we will have a quiz to recap the important notes and topics. Testing your knowledge after we have discussed them greatly enhances the learning experience.
Overview
Lecture 0 Introduction
Section 1: Digestive conditions and diseases
Lecture 1 Celiac Disease
Lecture 2 Signs of Liver Failure
Lecture 3 Spontaneous Bacterial Peritonitis
Lecture 4 Types of Jaundice
Lecture 5 Gallbladder Stones
Lecture 6 Hyperbilirubinemia
Lecture 7 Lactose intolerance
Lecture 8 Diverticulitis
Lecture 9 Hemochromatosis
Lecture 10 Shock syndromes
Lecture 11 stones in Crohn's disease
Lecture 12 Volvulus VS Intussusception
Lecture 13 Whipple disease
Lecture 14 Wilson disease
Lecture 15 Zenker's Diverticulum
Section 2: Important digestive structures
Lecture 16 Gastric blood supply
Lecture 17 Lesser Sac and Greater
Lecture 18 Portosystemic shunts
Lecture 19 Spleen Ligaments
Lecture 20 Tongue nerves and muscles
Section 3: Digestive Physiology
Lecture 21 Autonomic Nervous System
Lecture 22 How to lower cholesterol
Lecture 23 Acids and Bases
Lecture 24 Alcohol Metabolism
Lecture 25 Chewing Muscles
Lecture 26 Esophagus
Lecture 27 Gallstones
Lecture 28 Liver diseases in pregnancy
Section 4: Diuretics and plasma fluid manipulation
Lecture 29 ACE inhibitor
Lecture 30 Angiotensin II receptor blockers
Lecture 31 Acetazolamide
Lecture 32 Fludrocortisone
Lecture 33 Loop diuretic
Lecture 34 Potassium-sparing diuretics
Lecture 35 Thiazolidinedione
Section 5: Food Poisoning
Lecture 36 Food poisoning bacteria
Lecture 37 Food poisoning part 1
Lecture 38 Food poisoning part 2
Section 6: Infections
Lecture 39 Campylobacter
Lecture 40 E coli
Lecture 41 HBV curve
Lecture 42 HBV Serology
Lecture 43 Hepatitis B virus treatment
Lecture 44 Hepatitis viruses
Lecture 45 Legionella
Lecture 46 Listeria
Lecture 47 Pseudomonas aeruginosa
Lecture 48 Staphylococcus Aureus
Lecture 49 Streptococcus
Lecture 50 vibrio vulnificus
Section 7: Oncology
Lecture 51 Colon cancer screening
Lecture 52 Colorectal Cancer
Lecture 53 Glucagonoma
Lecture 54 Cancer terminology
Lecture 55 Tumor Grades and Stages
Lecture 56 Tumor lysis syndrome
Section 8: Vitamines review
Lecture 57 Vitamin A
Lecture 58 Vitamin C
Lecture 59 Vitamin D
Lecture 60 Vitamin K
Lecture 61 Zinc deficiency
Lecture 62 Vitamin B1
Lecture 63 Vitamin B2 and Vitamin B5
Lecture 64 Vitamin B3
Lecture 65 Vitamin B6 and Vitamin B7
Lecture 66 Vitamin B9
Lecture 67 Vitamin B12
Section 9: Digestive system hormones
Lecture 68 Cholecystokinin
Lecture 69 Gastrin
Lecture 70 Glucagon
Section 10: Pain Management
Lecture 71 Opioids
Lecture 72 Acetaminophen
Lecture 73 Aspirin
Lecture 74 NSAID
Section 11: Medications used by gastroenterologists
Lecture 75 Beta blocker
Lecture 76 Bismuth
Lecture 77 Cholinergic Drug
Lecture 78 Cytochrome P-450
Lecture 79 Laxatives
Lecture 80 Metoclopramide
Lecture 81 Ondansetron
Lecture 82 Orlistat
Lecture 83 Proton pump inhibitors
Lecture 84 Sympathomimetics
Section 12: Miscellaneous topics
Lecture 85 Antidotes
Lecture 86 Autoantibodies
Lecture 87 Chromosomal Defects
Lecture 88 Ethical principle: Autonomy
Lecture 89 Ethical principle: Beneficence
Lecture 90 Ethical principle: Justice
Lecture 91 Ethical principle: Nonmaleficence
Section 13: Case discussion
Lecture 92 Case #1
Lecture 93 Case #2
Lecture 94 Case #3
Lecture 95 Case #4
Lecture 96 Case #5
Lecture 97 Case #6
Lecture 98 Case #7
Lecture 99 Case #8
Lecture 100 Case #9
Lecture 101 Case #10
Lecture 102 Case #11
Lecture 103 Case #12
Healthcare workers,Medical, nursing, or pharmaceutical students,Anyone with a passion for Gastroenterology and vitamins

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[mitsumi1]

Digital Environment Painting: Matte Painting Techniques
Raphael Lacoste | Duration: 3:04 h | Video: H264 1024x768 | Audio: AAC 22,05 kHz mono | 5,36 GB | Language: English

This title demonstrates the combined techniques required to create high quality digital illustrations or matte paintings. Raphael combines elements of photographs, textured 3D geometry, and freehand painting techniques, within Adobe Photoshop and 3DS Max to achieve a high quality illustration. You will learn how to use the right elements to create a high-end illustration, starting with rough mood sketches and finishing with a highly polished final image. The variety of techniques shown on this title are useful for Digital Illustrators, Concept Artists, Matte Painters, or anyone looking to improve their digital painting skills.

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[mitsumi1]

Economics For Business Decision Requirements
Published 4/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.98 GB | Duration: 1h 42m

Managers can use economics to strategize and solve a variety of business problems, from the mundane to the mission-criti

What you'll learn
Throughout this course we will learn the meaning and the importance of Using economics to solve business problems
Understanding price elasticity
Demand curve shifts
Economics of scale vs. scope
Break-even and what-if analysis
Profit maximization
Economics in action
Requirements
No experience needed. You will learn everything you need to know
Description
Managers can use economics to strategize and solve a variety of business problems, from the mundane to the mission-critical. In this course, we explain how to use economic theory to answer strategic questions such as.Business economics is that science upon which industries, factories and veils depend in the process of producing goods and commodities and the way that attracts the consumer and fulfills his requirements and returns to the company with profits. And although many believe that economics is about money, the stock market, and treasury bills, fortunes, an economy as it is definedWhat are customers buying? (demand theory)What should we produce? (production theory)Which costs do I need to worry about now? (cost theory)What market am I in? (competition theory)What should we charge for it? (pricing theory)To understand what managerial economics looks like in practice, we explain how Google's auction-based advertising system employs the principles of game theory and how understanding this can help decision-makers to outmaneuver their competitors.Outcomes:Throughout this course we will learn the meaning and the importance of Using economics to solve business problemsUnderstanding price elasticityDemand curve shiftsEconomics of scale vs. scopeBreak-even and what-if analysisProfit maximizationEconomics in actionAudience:ManagersBusiness OwnersEntrepreneurs
Overview
Section 1: GDP: Determines the Standard of Living
Lecture 1 Overview
Lecture 2 Gross Domestic Product (GDP) and how to calculate it
Lecture 3 World GDP
Lecture 4 GDP per Capital
Lecture 5 Economic Growth
Lecture 6 GDP is Not a Perfect Measure for Wellbeing
Lecture 7 GDP - what is in it for me
Section 2: Inflation: Determines the Cost of Living
Lecture 8 Hyperinflation & Inflation
Lecture 9 The Consumer Price Index (CPI)
Lecture 10 Effect of Inflation on Personal Decisions
Lecture 11 Unemployment
Section 3: How Does the Economy Fluctuate ?
Lecture 12 The Economic Cycle
Lecture 13 The Story of Money
Lecture 14 The Story of Money part 2
Lecture 15 Monetary Policy - Part 1
Lecture 16 Monetary Policy - Part 2
Lecture 17 Fiscal Policy - Part 1
Lecture 18 Fiscal Policy - Part 2
Managers,Business Owners,Entrepreneurs

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[mitsumi1]

Figma Simple Exercises
Published 4/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 549.40 MB | Duration: 0h 59m

UIUX Projects to Try

What you'll learn
Design a Dynamic flipcard and
Embedding maps
Basics in Figma
Vertical and horizontal scroll
Remove background of an image
Hover Effects
Slide-up Card

Requirements
Little experience
Figma
Internet

Description
User interface design(UI) and user experience design(UX) is a very crucial parts of determining the final output of software, applications, or process. User interface design and user experience design(UI/UX) has lots of benefits since they have a greater impact on influencing how users might use or uninstall an app or the retention rate of an app or software and the like. Welcome to this course future designers, in this course, we will be learning to design Interfaces using Figma as the primary design tool. Figma makes it fun and easier to get your designs up to speed with positive outcomes especially when you use a creative approach to doing what you love doing best. In this lesson, you'll learn to use shapes(components) and tools to create stunning user interfaces. The main course projects includes several steps to learning to build or design interfaces and interactive components including dynamic flip cards, text hover effects, auto scrolling of text(marquee), a music player, slide-up card component and so much more. The course is for anybody who would like to get started with User interface design. This course is in collaboration with Jacqueline Asare Dartey a UI/UX expert in using Figma and Adobe XD.

Overview
Section 1: Introduction

Lecture 1 Introduction

Section 2: Icon Design

Lecture 2 Icons

Lecture 3 Icon Design 2

Section 3: Scrolling

Lecture 4 Horizontal Scroll

Lecture 5 Vertical Scroll

Section 4: Image Background Remover

Lecture 6 Remove image background

Section 5: Embedding Maps

Lecture 7 Mapsicle Plugin

Section 6: Interesting UIUX Exercises

Lecture 8 Creating a Music Player

Lecture 9 Creating Dynamic Flipcard

Lecture 10 Create a Slide Up Card Hover Effects

Lecture 11 Creating an infinite scroll (Marquees)

Section 7: Hover Effects

Lecture 12 Create Impressive Text Hover Effects with Interactive Components

Lecture 13 Interactive Hover Effect

Section 8: Bonus

Lecture 14 Socials

Beginners and intermediates,uiux fanatics

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[mitsumi1]

Flying Fundamentals : Principals Of Flight In Small Aircraft
Published 4/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.21 GB | Duration: 1h 42m

Mastering the Basics of Flight

What you'll learn
Master the principles of flight, including lift, weight, thrust, and drag, and how they applied to flight scenarios for safe and efficient flying.
Develop a deep understanding of aerodynamics, flight instruments, and aircraft performance to enhance your skills during flight operations.
Acquire knowledge of different aircraft designs and their impact on flight performance, allowing you to make informed choices for flight training.
Gain confidence in safe, effective small aircraft handling with a solid understanding of flight principles & practical applications.
Become proficient in interpreting the core information of flight, enabling you to make informed decisions and ensure smooth and successful flights.

Requirements
There are no prerequisites for taking this course! It is designed for beginners and aviation enthusiasts alike. All you need is an eagerness to learn about flying fundamentals and a passion for aviation.
No prior skills, experience, tools, or equipment are required.
Fair Understanding of the English Language.

Description
The "Flying Fundamentals: Principles of Flight in Small Aircraft" course is a comprehensive program designed to provide students with a solid understanding of the principles of flight in small aircraft. Through a combination of theoretical concepts and practical applications, students will explore the aerodynamic principles that govern how aircraft fly, including lift, drag, thrust, and weight. Topics covered include aircraft design, aerodynamics, aircraft performance, and factors that affect performance such as altitude, and weight and balance considerations.To enhance understanding, the course offers interactive learning experiences, including simulations that allow students to grasp the principles of flight in practical scenarios. Additionally, students will have the opportunity to connect with experienced aviation instructors, engage in discussions with fellow aviation enthusiasts, and learn from real-world examples and case studies, enriching their learning experience.This course is suitable for aspiring pilots seeking to build a strong foundation in aviation, as well as aviation enthusiasts or individuals interested in gaining knowledge about the mechanics of flight in small aircraft. By the end of the course, students will have a comprehensive understanding of the principles of flight in small aircraft, enabling them to confidently pursue further aviation training or enhance their knowledge of aviation as a hobby.Join us on this exciting journey and take your first steps towards mastering the fundamentals of flight in small aircraft! Whether you're interested in pursuing a career in aviation or simply fascinated by the mechanics of flight, this course will provide you with the knowledge and skills to navigate the world of aviation with confidence. Come aboard and unlock the secrets of the skies with our engaging and informative course.

Overview
Section 1: Welcome !

Lecture 1 Welcome to this course...

Section 2: Aerodynamics in Flight

Lecture 2 Aerodynamics Basics - Overview

Lecture 3 Aerodynamic Basics - Lesson

Lecture 4 The Forces of Flight - Overview

Lecture 5 The Forces of Flight - Lesson

Lecture 6 Aerodynamic Principals - Overview

Lecture 7 Aerodynamic Principals - Lesson

Lecture 8 Aerodynamic Components - Overview

Lecture 9 Aerodynamic Components - Lesson

Lecture 10 Aircraft Performance and Aerodynamics - Overview

Lecture 11 Aircraft Performance and Aerodynamics - Lesson

Section 3: Lift, Drag, Thrust, Weight

Lecture 12 Lift Drag Thrust Weigh - Overview

Lecture 13 Lift Drag Thrust Weight - Lesson

Lecture 14 The Basics - Lift, Drag, Thrust, Weight - Overview

Lecture 15 The Basics - Lift, Drag, Thrust, Weight - Lesson

Lecture 16 Impact of - Lift, Drag, Thrust, Weight - Overview

Lecture 17 Impact of - Lift, Drag, Thrust, Weight - Lesson

Lecture 18 Calculating Lift, Drag, Thrust, Weight - Overview

Lecture 19 Calculating Lift, Drag, Thrust, Weight - Lesson

Lecture 20 Applying - Lift, Drag, Thrust, Weight - Overview

Lecture 21 Applying - Lift, Drag, Thrust, Weight - Lesson

Section 4: Aircraft - Design Mechanics & Validations

Lecture 22 Aircraft Design - Overview

Lecture 23 Aircraft Design - Section

Lecture 24 Aircraft Parts & Mechanics - Overview

Lecture 25 Aircraft Parts & Mechanics - Lesson

Lecture 26 Aerodynamic Performance - Overview

Lecture 27 Aerodynamic Performance - Section

Lecture 28 Aircraft Testing & Validation - Overview

Lecture 29 Aircraft Testing & Validation - Lesson

Lecture 30 Aircraft Maintenance & Safety - Overview

Lecture 31 Aircraft Maintenance & Safety - Lesson

Section 5: Aerodynamic Principals & Forces

Lecture 32 Aerodynamic Principals - Overview

Lecture 33 Aerodynamic Principals - Lesson

Lecture 34 Aerodynamic Forces - Overview

Lecture 35 Aerodynamic Forces - Lesson

Lecture 36 Aerodynamic Drag & Lift - Overview

Lecture 37 Aerodynamic Drag & Lift - Lesson

Lecture 38 Impact of Forces on Aircraft - Overview

Lecture 39 Impact of Forces on Aircraft - Lesson

Lecture 40 Aerodynamic Principals & Design - Overview

Lecture 41 Aerodynamic Principals & Design - Lesson

This course is perfect for aspiring pilots, aviation enthusiasts, and anyone interested in gaining a solid understanding of the principles of flight in small aircraft. Whether you're a beginner with no prior aviation experience or looking to enhance your aviation knowledge, this course is designed to provide you with comprehensive insights into aerodynamics, flight instruments, and aircraft performance.

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[mitsumi1]

From Zero To Hero: Learn Python And Gui Creation
Published 4/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.39 GB | Duration: 3h 54m

Master Python Fundamentals and Create Beautiful GUIs with PySimpleGUI

What you'll learn
Start from the basics and learn how to set up a Python development environment.
Understand the fundamentals of Python programming, including data types, variables, and control structures.
Explore object-oriented programming concepts such as classes, objects, and inheritance in a beginner-friendly way.
Gain experience building a variety of real-world applications with Python and PySimpleGUI, including calculators, text editors, and more.
Discover how to create graphical user interfaces (GUIs) using the PySimpleGUI library, even if you have no prior GUI development experience.
Practice building a variety of real-world applications with Python and PySimpleGUI, such as a weather app or a simple game.
Develop problem-solving skills and critical thinking through practical coding exercises and challenges.
Understand best practices for debugging, testing, and troubleshooting your Python code.
Build a final project, such as a fully-functional GUI-based application, to showcase your skills and apply what you've learned.

Requirements
No Programming knowledge is needed, I've taught this course to a 10yr old & they went through it like a hot knife in butter.
The only things you will need are
A Computer
Internet Connection
Discipline
Consistency

Description
Welcome to the ultimate course for beginners who want to learn how to create beautiful and functional graphical user interfaces with Python! In this course, we'll start from the very beginning, assuming zero prior programming knowledge, and guide you through everything you need to know to get started with python programming and PySimpleGUI. With our fun and engaging video lectures, interactive coding exercises, and quizzes, you'll learn to write clean and efficient Python code, and create professional-looking user interfaces for your applications.We'll cover all the basics of Python programming, from variables and data types to functions, loops, and logic statements. Then, we'll dive into pysimplegui and learn how to create GUI-based applications that are not only functional but also visually appealing. We'll show you how to design custom layouts, add buttons and text fields, handle user input, and much more.By the end of this course, you'll have a strong foundation in Python programming and PySimpleGUI, and you'll be ready to create your own GUI-based applications. Plus, you'll have a final project to work on that will showcase your newly acquired skills.With our easy-to-follow, step-by-step approach, and plenty of resources to help you along the way, this course is perfect for anyone who wants to learn Python programming and PySimpleGUI, regardless of their skill level. So why wait? Join us today and start your journey towards becoming a Python developer!

Overview
Section 1: Introduction

Lecture 1 Welcome!

Section 2: 1. Course Introduction, Python Overview & Installation

Lecture 2 Python Overview

Lecture 3 Installing Python (Anaconda)

Lecture 4[Recommended] - Installing Python (VS Code)

Section 3: Python Datatypes

Lecture 5 Python Datatypes Overview

Lecture 6 Python MATH!

Lecture 7 Variable Assignment Basics

Lecture 8 Variable Naming Rules

Lecture 9 Working with Strings

Lecture 10 Slicing & Sequencing in Strings

Lecture 11 String Interpolation

Lecture 12 Working with Lists - an Overview

Lecture 13 Lists - Telephone book Mini Project

Lecture 14 Dictionaries

Section 4: Python Operators

Lecture 15 Mathematical Operators in Python

Lecture 16 Comparison Operators in Python

Section 5: Python Statements

Lecture 17 IF Statements

Lecture 18 IF-ELSE Statements

Lecture 19 For Loops

Lecture 20 While Loops

Section 6: Inputs & Functions

Lecture 21 Python User Input

Lecture 22 Custom Functions

Section 7: Mini Project!!!!

Lecture 23 Project Overview & some Tips

Lecture 24 Mini Project #1 - Code along & Explanation

Section 8: Modules & Packages

Lecture 25 Python Modules

Lecture 26 Custom Modules

Section 9: Mini Project 2

Lecture 27 Mini Project #2 - Full Code along & Explanation - Random Password Generator

This course has been designed with beginners in mind, and requires zero prior programming experience. Whether you're a complete newbie to coding or have dabbled in other languages before, this course is perfect for anyone who wants to learn how to build powerful and functional graphical user interfaces using Python and PySimpleGUI. Throughout this course, you'll learn everything you need to know to get started with Python programming and PySimpleGUI, from the very basics of setting up a development environment to building your own GUI-based applications. You'll gain hands-on experience with Python and PySimpleGUI by building real-world applications, solving coding challenges, and working on a final project. Our aim is to make learning Python and PySimpleGUI as easy and accessible as possible, so we'll guide you through every step of the way. You'll have access to video lectures, coding exercises, quizzes, and helpful resources to reinforce your learning and build your skills. By the end of this course, you'll have the skills and confidence to create your own Python-based applications with PySimpleGUI, and you'll be ready to take on more advanced programming challenges. Join us today and start your journey towards becoming a Python developer.

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[mitsumi1]

Fundamentals Of Electric Motor Drives With Induction Motor
Published 4/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 676.53 MB | Duration: 2h 43m

Master the fundamentals of electric motor drives and revolutionize your engineering skills

What you'll learn
Principle of Electric Motor Drive
Torque Speed Characteristics of Load and Motor
How to Select an Motor for an Application
How to Select a Speed Control Method
Various Voltage Control Methods
Various Rotor Resistance Methods
Various Frequency Control Methods
Role and Responsibility of Electric Motor Drive Specialist
And more
Requirements
Basic Electrical Engineering and fundamentals of Induction Motor
Description
Electric Drive is not only about the speed control of the motors, but it is about understanding the electric motor at work. Thus, understanding the operation of an electric motor is the first step. However, mastering the electric motor drive requires the ability to select an electric motor for specific applications, understand various speed control possibilities and selecting the best one for the application, improve efficiency and performance, and so on. As a result, the topic of electric motor drive is the most important for electrical engineers.This is an online course designed to provide learners with a comprehensive understanding of electric motor drives, with a specific focus on induction motors.This course covers everything from basic principles of electric motor drive to advanced IM drive like VFD. This course also covers many important practical aspects which you may not find anywhere in the regular academic syllabus. Hello, I am Dr. Jignesh Makwana, Phd in Electrical engineering from IIT Roorkee with specialization in Electric Drive and Power Electronics. Although this course will be a great resource for the students who are studying the subject Electric Motor Drive as a part of engineering Curriculum, this course will become far more than just academic study. As I am currently associated with the Electric Motor Drive Industry, I know the real Industrial demand of Electric Motor Drive Specialists. As a result, I designed this course to produce skilled electric motor drive engineers with extensive knowledge and skill. This course is not limited to current content, but I will update it on a regular basis to include the most recent on-demand topics whenever possible. On the request of students, topics such as field oriented control, vector control drive, and direct torque control will be added to the same course. This means that any theoretical and practical topic related to AC Motor Drive will be covered in this course and is kept up to date on a regular basis. In addition, the course will cover topics such as how to select motor rating and protection for an application, how to select the speed control method for an application, and what the scope and opportunities are in the field of Electric Motor Drive.So, if you are an electrical engineer looking for an opportunity in the electric motor industry, simply enrol in the course and expand your knowledge and skills.
Overview
Section 1: Introduction
Lecture 1 Introduction to an Electric Drive
Section 2: Torque Speed Characteristics
Lecture 2 Understand Load Torque Characteristics
Lecture 3 Understand Torque Speed Charactristics of the Motor
Lecture 4 Understand Motor on Load Situation with Torque Speed Characteristics
Lecture 5 Extend understanding of Motor on load with variation in load characteristics
Section 3: Introduction to an Electric Motor Drive
Lecture 6 Role of Electric Drive Engineer
Lecture 7 Applications of Electric Motors
Lecture 8 Type of Electric Motors
Lecture 9 Electric Motor Drive
Section 4: Equivalent Circuit and Equations of 3 Phase Induction Motor
Lecture 10 Derive torque speed equation
Lecture 11 Starting torque and max torque
Lecture 12 Simplified Equation for Low slip and high slip
Section 5: Speed Control of Induction Motor Drive
Lecture 13 5.1 Introduction to Speed Control System
Lecture 14 Open-Loop and Closed Loop Speed Control System
Lecture 15 Parameters of Electric Drive
Lecture 16 Eddy Current Coupling Speed Control
Section 6: Voltage Control Methods of Induction Motor Drive
Lecture 17 Stator Voltage Control
Lecture 18 Reduced Voltage Soft Starting
Lecture 19 Soft Starting with Isolation of Power Switches
Lecture 20 AC Regulator Based Induction Motor Drive
Section 7: Rotor Resistance Control of Induction Motor Drive
Lecture 21 Rotor Resistance Method of Speed Control
Lecture 22 Phase Control Rectifier Based Rotor Resistance Control of Induction Motor
Lecture 23 Chopper Based Rotor Resistance Control of Induction Motor
Lecture 24 Closed Loop Speed Control of IM with Chopper Based Rotor Resistance Control
Electrical Engineering Students studding Electric Drive,Electrical Engineering Graduates Looking for new opportunities in the Electric Motor Industry,Research Scholars working in the field of Electric Motor Drive

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[mitsumi1]

Futures Trading Made Easy - 2023
Published 4/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 779.59 MB | Duration: 1h 22m

Learn how to become Profitable in the Market with Futures Trading

What you'll learn
Why Futures trading is better than Options trading
How to use TradingView
Learn to use Tradovate
Learn about Funded Accounts
How to have unlimited day trades under $25k
Requirements
Basic knowledge on the stock market will be helpful
Description
Welcome to 'Futures Trading Made Easy'. In this course, I*will teach you how to trade futures using Tradovate and charting with TradingView. Futures trading allows you to buy/sell oil, gold, stock indexes, currencies, livestock, etc. With futures trading, there is unlimited day trading regardless of account size. Also, no time decay*(theta), unlike option contracts. If you're unfamiliar with trading, I*recommend my absolute beginners course where I cover plenty of background on stock trading as well as charting. However, this course is still beginner friendly as I*cover everything you need to know to begin trading.You will learn:- Setting up Tradovate- Trading with Tradovate (via live trading videos)- Setting up TradingView- Setting up TradingView Indicators (free plan)- Charting with TradingView (free plan)- What funded accounts are- Evaluation vs Performance accounts- How to have unlimited day trades with under $25k in your account- How to set stop losses in Tradovate- Setting daily loss restrictions with Tradovate- Best practices trading futuresThe goal of this course is to teach only the necessary material.*Too many paid groups and courses spend countless hours overwhelming you with information. I've been trading on and off for 5+ years and have consumed endless courses and paid group material. A majority of what I've learned has proven to not be effective when making winning trades.I want to teach you to trade, not how to blindly follow stock calls.
Overview
Section 1: Introduction
Lecture 1 Intro
Lecture 2 In-Depth intro
Lecture 3 Join the Student Community
Lecture 4 Day Trading Made Easy
Section 2: Using TradingView
Lecture 5 TradingView - Link
Lecture 6 Setup
Lecture 7 Adding Indicators
Lecture 8 Most Useful but Basic Features
Section 3: Exploring Tradovate and Live Trading
Lecture 9 Navigating Tradovate
Lecture 10 Live Trading
Lecture 11 Live Trading Part 2
Section 4: Funded Accounts
Lecture 12 Funded Accounts Info
Lecture 13 Sign up
Section 5: Where to go From Here
Lecture 14 Next Steps
Lecture 15 Join the Discord
beginners and intermediate traders looking to expand their trading pallet.

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[mitsumi1]

Genetics Study, Dna, And Chromosomes Mutations
Published 4/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.25 GB | Duration: 2h 3m

Important genetics topics and discussion

What you'll learn
Genetic conditions and diseases
Updated guidelines in genetics
Important Diagnostic tests
Oncology topics
Important Microbiology topics
Familial Genetics
Case discussions
Requirements
No prior requirements needed
Description
This course covers all the important topics in genetics study. From DNA structures and mechanism to chromosomal mutations and genetic diseases. We will start by discussing some basics and move to clinical cases and patients' presentation. By understanding the function of each gene, we can easily deduce the associated diseases and their presentation.There many tests and essential investigations which we rely on daily in our clinical practice. A large number of these tests depends on deep understanding of genetics. Such as Polymerase Chain Reaction, Blotting Tests, and Flow Cytometry. These tests are very important and commonly seen in exams and in the clinical practice.Oncology is a big part of this course as we will discuss important tumors and their genetics origin. Such as Leukemia, Basal Cell Carcinoma, Melanoma, and Ewing Sarcoma. Certain microbes and carcinogens can alter our genomes are predispose cancers, we will go through these offenders and understand them.Understanding the modes of inheritance of genetic diseases is crucial for healthcare providers and genetics enthusiasts. Once you understand how genetic diseases run in families, it becomes easier to anticipate signs and symptoms and manage treatments accordingly.At the end of the course we have a quiz section to test your knowledge and refine the important information you learned.
Overview
Lecture 0 Introduction
Section 1: Familial Genetics
Lecture 1 Genetics anticipation
Lecture 2 Modes of inheretance
Lecture 3 Huntington's disease
Section 2: Important Diagnostic tests
Lecture 4 Polymerase Chain Reaction
Lecture 5 Blotting tests
Lecture 6 Flow cytometry
Section 3: Genomes
Lecture 7 mRNA
Lecture 8 Oncogenes
Lecture 9 Tumor suppressor gene
Lecture 10 Tumor marker
Section 4: Organs embryology
Lecture 11 CNS development
Lecture 12 Kidney development
Lecture 13 Oogenesis and Spermatogenesis
Section 5: Genetic conditions and diseases
Lecture 14 Chromosomal Defects
Lecture 15 Duchenne muscular dystrophy
Lecture 16 Ehlers-Danlos Syndrome
Lecture 17 Multiple Endocrine Neoplasia
Lecture 18 Shy Drager Syndrome
Lecture 19 Wilson disease
Lecture 20 Cystic fibrosis
Lecture 21 Marfan syndrome
Lecture 22 Complications of Down syndrome
Lecture 23 Diagnosis of Down syndrome
Lecture 24 Down syndrome mnemonic
Lecture 25 Edwards' syndrome
Lecture 26 Patau's syndrome
Lecture 27 Turner Syndrome
Lecture 28 Hemochromatosis
Lecture 29 Kallmann syndrome
Lecture 30 Klinefelter syndrome
Lecture 31 Phenylketonuria
Lecture 32 Polycythemia Vera
Section 6: Important Microbiology topics
Lecture 33 Conjugation
Lecture 34 Transduction
Lecture 35 Transposition
Lecture 36 viral genetics
Lecture 37 Virulence factors
Section 7: Oncology topics
Lecture 38 Acute Lymphoblastic Leukemia
Lecture 39 Basal Cell Carcinoma
Lecture 40 Cancer staging and grading
Lecture 41 Cancer terminology
Lecture 42 carcinogens
Lecture 43 Ewing Sarcoma
Lecture 44 Melanoma
Lecture 45 Multiple myeloma
Lecture 46 oncogenic microbs
Lecture 47 Pheochromocytoma
Lecture 48 Squamous Cell Carcinoma
Section 8: Miscellaneous topics
Lecture 49 Alpha and Beta Blockers
Lecture 50 Autoantibodies
Lecture 51 Biochemistry Terminology
Lecture 52 Epithelial Cell Junctions
Lecture 53 Hypersensitivity
Lecture 54 Lead poisoning
Lecture 55 Passive and Artificial Immunity
Lecture 56 RBC Changes
Section 9: Case discussion
Lecture 57 Case #1
Lecture 58 Case #2
Lecture 59 Case #3
Healthcare workers,Medical, nursing, or pharmaceutical students,Anyone with a passion for Gastroenterology and vitamins

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