AI and ML have gained a lot of popularity in 2025. Every company wants to stay ahead of the curve and introduce AI in its daily operations. Although we have multiple models from ChatGPT, Claude, Cursor, DeepSeek, and other models available in the market today, which amaze the world with their knowledge and data that they share.
However, to learn and grow, we need resources that can help us understand the basics, the technicalities, and most importantly, how to apply these concepts in real-world scenarios.
Below are multiple free resources I’ve gathered to help you master AI/ML concepts effortlessly.
AI Engineer Roadmap
An AI Engineer roadmap is a step-by-step guide to becoming an AI Engineer in 2025. It provides a curated list of learning paths starting from Introducing AI concepts, to LLMs, OpenAI, AI safety and ethics, MCP servers, and AI development tools. It guides the learner to choose the correct path for easy learning of the concepts.
Elements of AI
Created by MinnaLearn in partnership with the University of Helsinki, The Elements of AI is a free online course series designed with accessibility in mind. It offers learners practical insight into what’s possible with AI, what isn’t, and how to begin developing AI applications. The curriculum blends theoretical foundations with real-world exercises, designed to fit the schedule rather than dictate it.
MIT 6.034 Artificial Intelligence
This course, offered by MIT, equips students with a strong foundation in how AI systems think, reason, and learn. It covers core concepts such as knowledge representation, problem-solving strategies, and machine learning techniques. By the end of the program, learners gain the ability to design intelligent systems that solve real computational challenges. They also develop a deeper understanding of how structuring knowledge, building reasoning workflows, and enabling learning shape the engineering of AI-driven applications.
AI for Beginners
The AI for Beginners GitHub repository offered by Microsoft is a 2-week, 24-lesson curriculum. It includes practical lessons, quizzes, and labs. The curriculum is beginner-friendly and covers tools such as TensorFlow and PyTorch, as well as ethics in AI.
Generative AI Course by Google
Discover the latest generative AI training courses by Google, from beginner to advanced. Start with an introduction or dive into advanced training for application developers or data scientists.
Learn AI Engineering
The Learn AI Engineering GitHub repository provides a comprehensive list of free resources to learn everything about AI/ML, LLMs, and Agents. A plethora of information is available in the repository to build a solid foundation in AI.
Generative AI for Beginners
The Generative AI for Beginners is a GitHub repository created by Microsoft offering 21 Lessons to get started and build with Generative AI.
AI Agents for Beginners
The AI Agents for Beginners is a GitHub repository created by Microsoft offering 12 Lessons to get started with building AI Agents.
Awesome Artificial Intelligence
The Awesome artificial intelligence GitHub repository offers a well-organized and carefully curated collection of AI courses, books, video lectures, and research papers.
It serves as a valuable resource for learners aiming to build a stronger foundation of core AI concepts, problem-solving approaches, and modern application areas such as machine learning, deep learning, computer vision, and natural language processing.
Machine Learning Roadmap
The Machine Learning Roadmap offers a step-by-step guide to becoming a Machine Learning Engineer in 2025. It helps to map out everything from fundamentals to advanced topics, making it an excellent starting point whether you’re new to ML or strengthening your existing skills.
Machine Learning Crash Course by Google
The Machine Learning Crash Course by Google offers a free, hands-on introduction to machine learning, covering core concepts like regression, classification, neural networks, and modern topics such as large language models, AutoML, and responsible AI.
Whether you’re new to ML or revisiting the fundamentals, the course uses interactive lessons, real-world exercises, and intuitive visuals to build a solid conceptual and practical foundation.
Foundations of Machine Learning and Artificial Intelligence
This course by FreeCodeCamp combines clear, structured lessons with real-world case studies and insights from industry experts. It’s designed to help learners master both AI fundamentals and hands-on implementation, ensuring a balanced understanding of theory and practice.
In addition to technical training, the course includes a detailed career roadmap, whether your goal is to grow in data science, build an AI-driven startup, or confidently prepare for interviews in the AI industry.
Awesome Machine Learning
The Awesome Machine Learning GitHub repository provides a curated list of awesome Machine Learning frameworks, libraries, and software. It offers links to free ML courses, books, events, and meetups.
LLM4SoftwareTesting
The LLM4SoftwareTesting GitHub repository provides a curated collection of papers and resources on the utilization of large language models (LLMs) in software testing.
Final Words
Artificial Intelligence and Machine Learning are evolving at a rapid pace, making continuous learning a key differentiator for every modern technologist. The resources shared in this blog are designed to help you build real expertise, grounded in fundamentals and strengthened through hands-on practice.
No single tool or course will define your success, but a consistent commitment to learning and applying your skills certainly will.
Happy Learning!!
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