AI stands for Artificial Intelligence. It refers to the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions), and self-correction. AI encompasses various subfields, such as machine learning, natural language processing, computer vision, robotics, and more. The goal of AI is to create systems that can perform tasks that would typically require human intelligence, such as understanding natural language, recognizing patterns in data, making decisions, and even learning from experience.

Torch, and scikit-learn that simplify AI development. Additionally, its syntax is easy to learn and understand, making it an excellent choice for those new to programming.

Machine Learning with scikit-learn: If you're just starting with AI, diving into machine learning using scikit-learn can be a straightforward approach. Scikit-learn provides simple and efficient tools for data mining and data analysis. It includes various algorithms for classification, regression, clustering, dimensionality reduction, and model selection.

Deep Learning with TensorFlow or PyTorch: Once you're comfortable with machine learning, you can explore deep learning using libraries like TensorFlow or PyTorch. These libraries provide tools for building and training neural networks, which are essential for tasks like image recognition, natural language processing, and more.

Natural Language Processing (NLP) with NLTK or spaCy: If you're interested in working with text data, NLP is a fascinating field. Libraries like NLTK (Natural Language Toolkit) or spaCy offer tools and resources for text processing, tokenization, part-of-speech tagging, named entity recognition, and more.

Computer Vision with OpenCV: If you're interested in working with images and videos, computer vision is an exciting area within AI. OpenCV (Open Source Computer Vision Library) provides a comprehensive set of tools for image processing, object detection, face recognition, and more.

Remember, while Python is often recommended for beginners due to its simplicity and extensive libraries, other programming languages like R and Julia also have robust ecosystems for AI and machine learning. It's essential to choose the language and approach that align with your interests and goals. Additionally, online tutorials, courses, and resources can help you get started and progress in your AI journey.

Geeks for Geeks has a course for studying AI based on Python, and below link will be helpful if you have interest in AI Programming

https://www.geeksforgeeks.org/python-ai/