Free AI Courses by Topic JUN 2025
- Venkata Pagadala
- Jun 17
- 6 min read
Free AI Courses by Topic
A comprehensive collection of free AI courses organized by topics and subtopics.
About This Collection:
Venkata Pagadala has curated this comprehensive collection of free AI courses to help you navigate the rapidly evolving field of artificial intelligence. All links have been verified as active and free to access as of June 2025.
The collection is organized hierarchically from broader concepts to specific subtopics, covering both foundational AI knowledge and the hottest trending topics in 2025. Each course entry includes a description, topics covered, key features, and verification of link status.
Whether you're a beginner looking to start your AI journey or an experienced practitioner wanting to stay updated with the latest trends, this collection provides valuable resources to enhance your skills and knowledge. Last updated: June 2025
Overview of Topics
Machine Learning: Technology that enables computers to learn patterns from data and make predictions without being explicitly programmed.
Deep Learning: Advanced machine learning using neural networks with multiple layers to process complex patterns in data.
Natural Language Processing (NLP): An AI field focused on enabling computers to understand, interpret, and generate human language.
Computer Vision: AI technology that allows computers to gain a high-level understanding from digital images and videos.
Reinforcement Learning: A Learning approach where AI agents take actions to maximize rewards in a specific environment.
AI Fundamentals: Core concepts and principles that form the foundation of artificial intelligence systems.
Generative AI: AI systems that create new content like images, text, audio, or video based on training data.
AI Agents: Autonomous software entities that perceive their environment and take actions to achieve goals.
Multimodal AI: Systems that process and understand multiple types of data (text, images, audio) simultaneously.
AI-Powered Social Media Tools: Applications using AI to enhance content creation, scheduling, and analytics for social platforms.
Generative AI: AI systems that create new content like images, text, audio, and video
Augmented Reality + AI: The combination of AR technology with AI to create intelligent, context-aware experiences that understand and respond to the physical world. This enables more natural interactions between digital content and real environments.
Quantum AI: The intersection of quantum computing and artificial intelligence, using quantum algorithms to potentially solve complex problems beyond classical computing capabilities. This emerging field could revolutionize machine learning with exponential speedups.
AI Ethics and Responsible AI: The practice of designing, developing, and deploying AI systems with consideration for fairness, transparency, privacy, and societal impact. This ensures AI benefits humanity while minimizing potential harms.
AI for Sustainability: Applications of AI to address environmental challenges like climate change, resource conservation, and biodiversity loss. These systems optimize energy use, predict environmental changes, and support sustainable decision-making.
Edge AI and Decentralized Intelligence: AI processing that happens directly on local devices rather than in the cloud, enabling faster responses, enhanced privacy, and operation without constant internet connectivity. This approach distributes intelligence across networks of devices.
FOUNDATIONAL AI TOPICS
Machine Learning
Google - Machine Learning Crash Course
URL:https://developers.google.com/machine-learning/crash-course
Description: A self-study guide for aspiring machine learning practitioners with video lectures, real-world case studies, and hands-on practice exercises.
Topics Covered: ML concepts, TensorFlow, feature engineering, classification, regression, neural networks
Features: Interactive visualizations, coding exercises, real-world examples
Harvard - Data Science: Machine Learning
URL:https://pll.harvard.edu/course/data-science-machine-learning
Description: Learn popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system.
Topics Covered: K-nearest neighbors, linear regression, logistic regression, random forests, regularization
Features: Free audit option, Harvard faculty instruction, real-world projects
MIT - Introduction to Machine Learning
URL:https://openlearninglibrary.mit.edu/courses/course-v1:MITx+6.036+1T2019/about
Description: An introductory course covering the basic theory, algorithms, and machine learning applications.
Topics Covered: Supervised learning, unsupervised learning, deep learning, reinforcement learning
Features: MIT course materials, programming assignments, lecture videos
Deep Learning
Fast.ai - Practical Deep Learning for Coders
Description: A course designed for people with coding experience who want to learn how to apply deep learning and machine learning to practical problems.
Topics Covered: CNNs, RNNs, computer vision, NLP, tabular data, collaborative filtering
Features: Top-down teaching approach, practical coding exercises, state-of-the-art techniques
DeepLearning.AI - Deep Learning Specialization
Description: A foundational program that helps you understand deep learning, apply it effectively, and build a career in AI.
Topics Covered: Neural networks, optimization algorithms, CNN, RNN, LSTM, transformers
Features: Free audit option, taught by Andrew Ng, programming assignments
MIT - Introduction to Deep Learning
Description: An introductory course covering the foundations of deep learning methods with applications to computer vision, natural language processing, biology, and more.
Topics Covered: Neural networks, CNN, RNN, self-supervised learning, generative models
Features: MIT course materials, lecture videos, coding tutorials
Natural Language Processing
Stanford - CS224N: Natural Language Processing with Deep Learning
Description: A course on the cutting-edge research in deep learning applied to NLP, focusing on neural networks and their applications.
Topics Covered: Word vectors, dependency parsing, RNNs, machine translation, transformers, BERT
Features: Stanford course materials, lecture videos, assignments
Great Learning - Free NLP Courses
Description: A collection of free courses covering various aspects of natural language processing.
Topics Covered: Text preprocessing, sentiment analysis, language models, chatbots, transformers
Features: Free certification, hands-on projects, beginner-friendly
Computer Vision
OpenCV - Free Computer Vision Courses
Description: A collection of free courses covering computer vision fundamentals and applications using OpenCV.
Topics Covered: Image processing, object detection, feature extraction, tracking, OpenCV programming
Features: Hands-on tutorials, practical examples, industry-standard library
Hugging Face - Computer Vision Course
URL:https://huggingface.co/learn/computer-vision-course/en/unit0/welcome/welcome
Description: A comprehensive course on modern computer vision techniques using transformers and pre-trained models.
Topics Covered: Image classification, object detection, segmentation, transformers for vision
Features: Interactive notebooks, practical examples, state-of-the-art models
Reinforcement Learning
Hugging Face - Deep Reinforcement Learning Course
URL:https://huggingface.co/learn/deep-rl-course/en/unit0/introduction
Description: A free course designed to learn deep reinforcement learning in a hands-on way.
Topics Covered: Q-Learning, policy gradients, actor-critic methods, PPO, SAC
Features: Interactive environments, coding exercises, community challenges
Stanford - CS234: Reinforcement Learning
Description: A course covering the fundamentals of reinforcement learning and its applications.
Topics Covered: MDPs, dynamic programming, Monte Carlo methods, TD learning, function approximation
Features: Stanford course materials, lecture videos, assignments
AI Fundamentals
Elements of AI - University of Helsinki
Description: A series of free online courses created by Reaktor and the University of Helsinki to demystify AI.
Topics Covered: AI basics, problem solving, real-world applications, machine learning, neural networks
Features: No coding required, interactive exercises, university certificate
Microsoft - AI for Beginners
Description: A 12-week curriculum about artificial intelligence basics.
Topics Covered: Symbolic AI, neural networks, computer vision, NLP, reinforcement learning
Features: Lesson slides, code examples, quizzes, assignments
TRENDING AI TOPICS 2025
Generative AI
Google Cloud - Introduction to Generative AI
URL:https://www.cloudskillsboost.google/course_templates/536
Description: An introductory level microlearning course explaining what Generative AI is, how it's used, and how it differs from traditional machine learning methods.
Topics Covered: Generative AI fundamentals, use cases, Google tools for Gen AI app development
Duration: 45 minutes
Features: Completion badge, introductory level content
Microsoft - Generative AI for Beginners
URL:https://microsoft.github.io/generative-ai-for-beginners/
Description: A comprehensive 21-lesson course teaching everything needed to start building Generative AI applications.
Topics Covered: LLMs, prompt engineering, text generation, chat applications, image generation, RAG, AI agents, fine-tuning
Features: Video lessons, code samples in Python and TypeScript, multi-language support
AI Agents and Autonomous Systems
Hugging Face - AI Agents Course
URL:https://huggingface.co/learn/agents-course/en/unit0/introduction
Description: A comprehensive free course taking you from beginner to expert in understanding, using, and building AI agents.
Topics Covered: Agent fundamentals, frameworks (smolagents, LangGraph, LlamaIndex), use cases, observability and evaluation
Features: Hands-on exercises, certification option, community challenges, Discord study groups
Multimodal AI
Simplilearn - Free Multimodal RAG Course
URL:https://www.simplilearn.com/free-multimodal-rag-course-skillup
Description: An introduction to integrating text, images, and audio data into retrieval-augmented generation (RAG) systems.
Topics Covered: Designing multimodal AI models, data integration, building and training RAG models, evaluation techniques
Duration: 2 hours of self-paced video lessons
Features: Completion certificate, 90 days of access, beginner-friendly content
AI-Powered Social Media Tools
Great Learning - Basics of Social Media Automation
URL:https://www.mygreatlearning.com/academy/learn-for-free/courses/basics-of-social-media-automation
Description: Learn to streamline content creation, management, and engagement with AI-powered social media automation tools.
Topics Covered: AI tools for content creation, social media management tools, email marketing automation, workflow optimization
Duration: 1.5 hours
Features: Free course content, completion certificate option, self-paced learning
Augmented Reality + AI
Unity - Mobile AR Development
Description: A comprehensive learning pathway to create augmented reality applications compatible with iOS and Android devices.
Topics Covered: AR development fundamentals, visual scripting, Unity's AR tools, mobile deployment
Duration: Approximately 1h 45m
Features: Free access, hands-on tutorials, project-based learning
Quantum AI
openHPI - Quantum Machine Learning with IBM Quantum Research
Description: An interdisciplinary course exploring the intersection of quantum computing and machine learning.
Topics Covered: Parameterized quantum models, training algorithms, quantum support vector machines, variational quantum classifiers
Duration: 2 weeks
Features: Free online course, certificate available, advanced-level content
AI Ethics and Responsible AI
University of Helsinki - Ethics of AI
Description: A comprehensive free course exploring the ethical aspects of artificial intelligence for anyone interested in AI ethics.
Topics Covered: Ethical frameworks, AI transparency, fairness, privacy, accountability, sustainable AI development
Features: Self-paced learning, accessible to all backgrounds, practical ethical thinking skills
AI for Sustainability
LinkedIn Learning - An Introduction to AI and Sustainability
URL:https://www.linkedin.com/learning/an-introduction-to-ai-and-sustainability
Description: A course exploring how AI can help achieve sustainability targets like net zero emissions while protecting and restoring nature.
Topics Covered: AI for carbon emission reduction, renewable energy access, waste reduction, biodiversity protection
Duration: 41 minutes
Features: Free course content, exercise files, completion certificate option
Edge AI and Decentralized Intelligence
Intel - Edge AI Fundamentals with OpenVINO
URL:https://www.classcentral.com/course/udacity-intel-edge-ai-fundamentals-with-openvino-19456
Description: Learn practical skills for deploying edge AI using Intel's OpenVINO toolkit for computer vision applications.
Topics Covered: Pre-trained models, model optimization, inference engine, edge application deployment
Duration: 4 weeks
Features: Free online course, hands-on projects, industry-relevant skills
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