Below are my favorite and recommended Python courses in various fields. I'll add more resources to this list as I discover.
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Learn ethical hacking with Python by building a wide variety of tools used in cybersecurity, such as keyloggers, harvesters, and more.
Learn How To Build 36 Ethical Hacking Tools from Scratch using Python
From simple port scanners to advanced reverse shells, you'll be amazed how such tools can be made with Python!
Python is one of the best programming languages for building automation scripts, Infosec tools, and even malware!
This EBook is made by us! It's a practical hands-on for Python programmers that hope to expand their knowledge in Cyber security and Python by building their own tools for information gathering, penetration testing, digital forensic investigation, and more!
This course is highly practical, but it won't neglect the theory. It starts with the basics of ethical hacking and Python programming and installing the needed software. Then you'll dive and start programming straight away. You'll learn everything by example, by writing useful hacking programs, such as backdoors, keyloggers, credential harvesters, network hacking tools, website hacking tools, and more with Python.
Since I'm a self-taught Python programmer, I've taken the below courses years back to learn Python programming language, and I still recommend them today as they're still relevant and are updated frequently!
This course is aimed at complete beginners who have never programmed before and existing programmers who want to increase their career options by learning Python.
This one is the first that I recommend to any starter, as you'll acquire the Python skills that allow you to move into specific branches such as Machine Learning, Web scraping, etc. Tim Buchalka knows well how to teach beginners. It has about 65 hours of content, starting from the very basics to complex concepts.
Learn Python from a software developer. If you want to master Python and write efficient, elegant, and simple code, this is the course you've been looking for!
Even if you have no programming experience, this course will give you a super-strong foundation and teach you how to use Python to achieve any goal.
This was a complementary course for me, but you can also start with it. Many topics not covered in the above course are covered here, such as Python decorators, unit testing, and even doing web development and web scraping projects.
The course is rich with content, with more than 60 hours of Python. It is also a learn-by-doing course where you build fantastic projects in the fields of web scraping and automation, web development using Flask, GUI programming with Tkinter, handling databases and APIs, and much more.
I personally did not take this course, but I took Angela's web development course, which is totally worth it!
I suggest anyone getting started with Machine learning, Deep learning and neural networks take the below courses and playlists.
The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online organizations. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI apps.
This specialization is mainly taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.
It is a 3-course Specialization and is the updated version of Andrew's pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012.
This course will teach you how to build and train deep neural networks and apply them to real-world applications. You'll also build CNNs and RNNs to work with computer vision and NLP applications.
This specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology.
The instructor of this course is Andrew Ng; he is one of the world's most famous and influential computer scientists, he won various best paper awards at academic conferences and has had an enormous impact on the field of AI, computer vision, and robotics.
In this playlist, you will learn the foundations of Deep Learning, how to build neural networks, and how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, etc.
Explore our recommended computer vision courses and classes using the OpenCV library and other Deep Learning libraries such as Keras and TensorFlow.
The course teaches you everything you need to know to become an expert in Computer Vision with Python.
You start learning about numerical processing with the NumPy library and opening and manipulating images with NumPy. Then, you'll move on to using the OpenCV library to open and work with image basics. After that, you'll start to understand how to process images and apply various effects, including color mappings, blending, thresholds, gradients, and more.
After you've known OpenCV basics, you'll move to an entire course section devoted to the latest deep learning topics such as object detection, object tracking, custom image classification with YOLO, and others.
If you're a beginner in Computer Vision, I'll recommend Jose Portilla (the instructor of this course).