Online Courses: Discover a variety of online courses covering AI fundamentals, machine learning, deep learning, natural language processing, computer vision, and more. These courses, offered by renowned educational platforms, provide a structured learning experience to enhance your understanding and proficiency in AI.
Introduction to Artificial Intelligence
- Introduction to Artificial Intelligence (AI)by IBM on Coursera: In this course you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, understand AI concepts and terms like machine learning, deep learning and neural networks. You will be exposed to various issues and concerns surrounding AI such as ethics and bias, & jobs, and get advice from experts about learning and starting a career in AI. You will also demonstrate AI in action with a mini project.
- AI For Everyone by deeplearning.ai on Coursera: This beginner-friendly course offers a non-technical introduction to AI. It covers essential AI concepts, such as machine learning, neural networks, and AI ethics, while focusing on their practical implications for businesses and society.
Machine Learning with Python
- Machine Learning Specialization by deeplearning.ai on Coursera: The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications.
- “Applied Data Science with Python” by University of Michigan on Coursera: This specialization offers a hands-on approach to machine learning using Python. It covers topics such as data cleaning and preprocessing, model evaluation, and building predictive models using popular libraries like scikit-learn and pandas.
Deep Learning Specialization
- “Deep Learning Specialization” by deeplearning.ai on Coursera: This specialization consists of five courses that cover various aspects of deep learning. It starts with an introduction to neural networks and progresses to advanced topics such as convolutional networks, recurrent networks, and sequence models.
- “Deep Learning” on Udacity: Join the next generation of deep learning talent that will help define a highly beneficial AI-powered future for our world. In this program, you’ll study cutting-edge topics such as neural networks, convolutional neural networks, recurrent neural networks, and generative adversarial networks.
Natural Language Processing
- “Natural Language Processing” by deeplearning.ai on Coursera: This course provides an introduction to NLP and covers fundamental concepts and techniques, including text classification, sequence models, and attention mechanisms. It also includes hands-on programming assignments using popular NLP libraries.
- “Natural Language Processing on Google Cloud” on Coursera: This course introduces the products and solutions to solve NLP problems on Google Cloud. Additionally, it explores the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow.
Computer Vision
- “Deep Learning Applications for Computer Vision” by University of Colorado Boulder on Coursera: In this course, you’ll be learning about Computer Vision as a field of study and research. First we’ll be exploring several Computer Vision tasks and suggested approaches, from the classic Computer Vision perspective.
- “Convolutional Neural Networks” by deeplearning.ai on Coursera: Explore the world of computer vision with this intermediate-level course, delving into convolutional neural networks, visual detection, recognition tasks, and neural style transfer to transform images and videos.
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Tutorials and Guides: Access a range of tutorials, guides, and walkthroughs that offer step-by-step instructions and practical examples. These resources can help you gain hands-on experience with AI tools, frameworks, and libraries, enabling you to apply AI techniques to real-world problems.
Python for AI
- Python.org: The official website for the Python programming language offers comprehensive documentation and tutorials for learning Python. It provides resources for beginners, including tutorials on Python basics, data structures, and more.
- DataCamp: DataCamp offers an interactive platform with Python for AI tutorials. They provide hands-on coding exercises and projects that cover Python fundamentals, data manipulation, and AI-specific topics like machine learning and deep learning.
Introduction to Machine Learning
- Scikit-learn Documentation: Scikit-learn is a widely-used machine learning library in Python. Their official documentation provides a comprehensive guide to machine learning concepts, algorithms, and usage examples. You can find introductory guides, tutorials, and API references on their website.
- Towards Data Science: Towards Data Science is an online publication that features a variety of tutorials, articles, and guides related to machine learning and data science. They offer introductory guides to machine learning concepts, algorithms, and practical implementation using Python.
Deep Learning with TensorFlow
- TensorFlow.org: The official website for TensorFlow provides extensive documentation and tutorials for learning deep learning with TensorFlow. It offers a comprehensive guide to TensorFlow’s features, architecture, and practical examples of building deep learning models.
- TensorFlow Tutorials on GitHub: The TensorFlow Tutorials repository on GitHub contains a wide range of hands-on tutorials and guides on deep learning with TensorFlow. It covers various topics such as image classification, natural language processing, and generative models.
Natural Language Processing (NLP) Tutorial
- Natural Language Processing with Python and NLTK: Learn how to pre-process your text data and build topic modeling, text summarization and sentiment analysis applications.
- spaCy Documentation: spaCy is another widely-used Python library for NLP. The spaCy documentation offers a detailed tutorial that walks you through the key features of spaCy, including tokenization, POS tagging, dependency parsing, and entity recognition.
Computer Vision Basics
- OpenCV Documentation: OpenCV (Open Source Computer Vision) is a widely-used computer vision library. The OpenCV documentation provides a detailed tutorial that covers the basics of computer vision, including image processing, feature extraction, and object detection using OpenCV.
- PyImageSearch: PyImageSearch is an online platform dedicated to computer vision tutorials and guides. It offers a range of tutorials, including beginner-friendly guides to computer vision basics, image processing, and object detection using Python and popular libraries like OpenCV.