Enroll Course: https://www.udemy.com/course/python-per-ml-e-ai/
In the rapidly evolving world of technology, Artificial Intelligence (AI) and Machine Learning (ML) stand at the forefront, shaping our present and future. At the heart of these transformative disciplines lies a single, powerful programming language: Python. Currently ranking as the third most utilized programming language globally, Python’s applications are vast, spanning web development (Django/Flask), mobile development (KIVY), cybersecurity (Scapy), data analysis (Pandas), scientific analysis (SciPy), and numerical computation (Numpy).
It is precisely this potent combination of simplicity and computational power that has established Python as the go-to language for Machine Learning and Artificial Intelligence. The majority of the most popular and widely used AI and ML libraries, such as Scikit-Learn, Keras, Tensorflow (Google), and PyTorch (Facebook), are built upon Python.
This Udemy course, ‘Python per Machine Learning e Artificial Intelligence,’ aims to equip you with the essential Python programming knowledge to embark on your AI and ML journey. The course is thoughtfully structured into four main parts, culminating in a final project where you’ll build an Artificial Neural Network from scratch, using only Numpy for vector and matrix calculations.
**Course Breakdown:**
* **Part 1: Programming with Python:** This section lays the groundwork, guiding you through executing Python code and setting up your development environment with Anaconda. You’ll dive into programming fundamentals, covering variables, data types, collections, conditional statements, and loops.
* **Part 2: Programming Paradigms:** Python’s multi-paradigm nature is explored here. You’ll learn about Procedural Programming, focusing on organizing code into reusable functions, and Object-Oriented Programming, understanding how to encapsulate logic within classes.
* **Part 3: Advanced Python:** With a solid foundation in place, this part tackles more complex topics. You’ll master exception handling, file operations, code modularization, utilizing standard library modules (OS, Time, Datetime, Math, CSV), installing new modules with PIP, and creating virtual environments with Virtualenv and Conda.
* **Part 4: Python and Scientific Computing:** This crucial section delves into Numpy, the de facto Python module for scientific computing and the backbone of libraries like Scikit-Learn, Tensorflow, and Pandas. Understanding Numpy is key to unlocking the full potential of ML and AI in Python.
**Final Project: Developing an Artificial Neural Network from Scratch:** The course culminates in a practical project. After a brief introduction to Machine Learning and how Artificial Neural Networks function, you’ll build your own Neural Network from the ground up. This hands-on experience will be used to recognize handwritten digits.
**Bonus Section: Recognizing Malignant Tumors:** As an exciting bonus, the course concludes with training the developed Neural Network to identify malignant breast tumors from radiological scans. This showcases a real-world application of the learned concepts.
**Recommendation:**
This course is an excellent starting point for anyone looking to enter the fields of Machine Learning and Artificial Intelligence through Python. The structured approach, from basic Python programming to advanced concepts and a practical project, makes complex topics accessible. The inclusion of hands-on exercises and a bonus real-world application further enhances its value. Whether you’re a beginner programmer or looking to transition into AI/ML, this course provides a robust foundation. Highly recommended!
Enroll Course: https://www.udemy.com/course/python-per-ml-e-ai/