Today’s Free Udemy Courses are; Modern React JS Hooks and Context with Most Recent Edition, Reverse Engineering – Debugging and Malware Analysis, Practical Reinforcement Learning using Python – 8 AI Agents and Machine Learning – Regression and Classification (math Inc.)
Coupons are limited. So It may run out early
Free Udemy Course – 23 April 2021
Modern React JS Hooks and Context with Most Recent Edition
In this course, we will take you through everything you need to know to master web development using ReactJS by providing a powerfull knowledge through a mixture of diagrams and the creation of a simple application.
Learn by doing!
So we have made this course as simple as possible in order to take you through step by step so you can feel confident and get a truly good understanding of how to utilize ReactJS. In this course, we will be teaching React by creating various projects.
Fresh Content
It’s no secret how technology is advancing at a rapid rate. New tools are released every day, and it’s crucial to stay on top of the latest knowledge for being a better React developer. You will always have up-to-date content for this course at no extra charge.
All my students will have a chance to learn not only the whats but also learn the whys and hows.
What you will learn?
- Creating Context with Class Component
- Access to Context with Consumer
- Access to Context with Context Type
- To manipulate the data in Context
- useState, useEffect, useReducer, and useContext Hooks
- Reducer, Action and Dispatch concepts
- And you will learn much more about React Hooks
Why would you want to take this course?
Our answer is simple: The quality of teaching.
When you enroll, you will feel the OAK Academy`s seasoned developers expertise.
No prior knowledge is needed!
It doesn’t need any prior knowledge to learn it and the React is easy to understand for the beginners.
This course starts with very basics. First, you will learn how to install the tools, some terminology. Then the show will start and you will learn everything with hands-on practices. I’ll also teach you the best practices and shortcuts.
Step-by-Step Way, Simple and Easy With Exercises
By the end of the course, you’ll have a firm understanding of the React and valuable insights on how things work under the hood and you’ll also be very confident in the basics of coding and game development, and hungry to learn more. The good news is since the Free and popular tools are used you don’t need to buy any tool or application.
Video and Audio Production Quality
All our videos are created/produced as high-quality video and audio to provide you the best learning experience.
You will be,
- Seeing clearly
- Hearing clearly
- Moving through the course without distractions
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Reverse Engineering, Debugging and Malware Analysis
Breaking something down and putting it back together is a process that helps people understand how things were made.
A person would be able to redo and reproduce an origami by unfolding it first. Knowing how cars work requires understanding each major and minor mechanical part and their purposes. The complex nature of the human anatomy requires people to understand each and every part of the body. How? By dissecting it. Reverse engineering is a way for us to understand how things were designed, why is it in its state, when it triggers, how it works, and what its purpose is. In effect, the information is used to redesign and improve for better performance and cost. It can even help fix defects.
Imagine if the Trojan Horse was thoroughly inspected and torn down before it was allowed to enter the gates of a city. This would probably cause a few dead soldiers outside the gate fighting for the city. The next time the city is sent another Trojan Horse, archers would know where to point their arrows. And no dead soldiers this time. The same is true for malware analysis—by knowing the behaviors of a certain malware through reverse engineering, the analyst can recommend various safeguards for the network. Think of it as the Trojan Horse being the malware, the analyst being the soldier who initially inspected the horse, and the city being the network of computers.
Anyone seeking to become a reverse engineer or an analyst should have the trait of being resourceful. Searching the internet is part of reverse engineering. An analyst would not plainly rely on the tools and information we provide in this udemy course. There are instances that an analysis would even require reverse engineer to develop their own tools. Software auditing may require reverse engineering. Besides high-level code review processes, some software quality verification also involves implementing reverse engineering. The aim of these test activities is to ensure that vulnerabilities are found and fixed. There are a lot of factors that are not taken into consideration during the design and development of a piece of software. Most of these are random input and external factors that may cause leaks, leading to vulnerabilities. These vulnerabilities may be used for malicious intents that not only disrupt the software, but may cause damage and compromise the system environment it is installed in. System monitoring and fuzzing tools are commonly used when testing software. Today’s operating systems have better safeguards to protect from crashing. Operating systems usually report any discrepancies found, such as memory or file corruption. Additional information, such as crash dumps, are also provided in this course. From this information, a reverse engineer would be able to pinpoint where exactly in the software they have to inspect.
In the software security industry, one of the core skills required is reverse engineering. Every attack, usually in the form of malware, is reversed and analyzed. The first thing that is usually needed is to clean the network and systems from being compromised. An analyst determines how the malware installed itself and became persistent. Then, they develop steps for uninstalling the malware. In the anti-malware phase, these steps are used to develop the clean-up routine, once the anti-malware product is able to detect that the system has been compromised. The analysis provides information about how the malware was able to compromise the system. With this information, network administrators are able to impose policies to mitigate the attack. If the malware was able to enter the system because of a user opening an email attachment that contains JavaScript code, the network administrator would implement the blocking of emails that contain a JavaScript attachment.
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Practical Reinforcement Learning using Python – 8 AI Agents
Join the most comprehensive Reinforcement Learning course on Udemy and learn how to build Amazing Reinforcement Learning Applications!
Do you want to learn how to build cutting edge trading algorithms that leverage todays technology? Or do you want to learn the tools and skills that are considered the state of the art of Artificial Intelligence? Or do you just want to learn Reinforcement Learning in a Highly practical way?
After completing this course you will be able to:
- Build any reinforcement learning algorithm in any environment
- Use Reinforcement Learning for your own scientific experiments
- Solve problems using Reinforcement Learning
- Leverage Cutting Edge Technologies for your own project
- Master OpenAI gym’s
Why should you choose this course?
This course guides you through a step-by-step process of building state of the art trading algorithms and ensures that you walk away with the practical skills to build any reinforcement learning algorithm idea you have and implement it efficiently.
Here’s what’s included in the course:
- Atari Reinforcement Learning Agent
- Build Q-Learning from scratch and implement it in Autonomous Taxi Environment
- Build Deep Q-Learning from scratch and implement it in Flappy Bird
- Build Deep Q-Learning from scratch and implement it in Mario Bird
- Build a Stock Reinforcement Learning Algorithm
- Build a intelligent car that can complete various environments
- And much more!
This course is for you if …
- You’re interested in cutting edge technology and applying it in practical ways
- You’re passionate about Deep Learning/AI
- Want to learn about cutting-edge technologies!
- Want to learn reinforcement learning by doing cool projects!
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Machine Learning – Regression and Classification (math Inc.)
Machine learning is a branch of artificial intelligence (AI) focused on building applications that learn from data and improve their accuracy over time without being programmed to do so.
In data science, an algorithm is a sequence of statistical processing steps. In machine learning, algorithms are ‘trained’ to find patterns and features in massive amounts of data in order to make decisions and predictions based on new data. The better the algorithm, the more accurate the decisions and predictions will become as it processes more data.
Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts.
Google’s AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning.
Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever. Imagine a world with drastically reduced car accidents, simply by removing the element of human error.
Topics covered in this course:
1. Lecture on Information Gain and GINI impurity [decision trees]
2. Numerical problem related to Decision Tree will be solved in tutorial sessions
3. Implementing Decision Tree Classifier in workshop session [coding]
4. Regression Trees
5. Implement Decision Tree Regressor
6. Simple Linear Regression
7. Tutorial on cost function and numerical implementing Ordinary Least Squares Algorithm
8. Multiple Linear Regression
9. Polynomial Linear Regression
10. Implement Simple, Multiple, Polynomial Linear Regression [[coding session]]
11. Write code of Multivariate Linear Regression from Scratch
12. Learn about gradient Descent algorithm
13. Lecture on Logistic Regression [[decision boundary, cost function, gradient descent…..]]
14. Implement Logistic Regression [[coding session]]
