Artificial Intelligence & Machine LearningCurated Directory — Courses, Videos,  Books & Websites

MECHANISMS AND MOTION - ROBOTICS FOCUS

This course teaches the mechanical building blocks—linkages, gear trains, belt drives, bearings and actuators—and the practical calculations (torque, speed, gear ratios, load) needed to choose and size components for specific robotic tasks. Through project-focused modules and prototyping exercises you'll learn to translate functional requirements into mechanism layouts, iterate with simple materials and CAD, and diagnose common motion failures like binding, backlash, and motor overheating. If you want quickly actionable skills to design reliable motion systems for competition or classroom robots—balancing performance, weight, and cost—this course provides step-by-step methods and checklists to take a concept to a field-tested prototype.

Robotics with Python - Think, Code and Move!

This hands-on course teaches core robotics principles through Python by guiding you to write code that makes robots perceive, plan, and act—covering practical implementations of sensing, state estimation, motion planning, and control. Project-based labs with simulator and hardware examples emphasize debugging, system integration, and algorithmic trade-offs, so you finish with runnable demos and reusable code rather than only theory. If you want a code-first pathway to prototype behaving robots and evaluate real-world toolchains and design decisions, this course will quickly show whether to deepen into robotics engineering or specialize in perception, control, or planning.

Artificial Intelligence: A Guide for Thinking Humans

Mitchell demystifies how modern AI systems actually work—using clear explanations of neural networks, pattern recognition, training-data pitfalls, and vivid examples—so you gain practical insight into when models will succeed or fail. She pinpoints measurable limitations (brittleness, lack of common sense, dataset bias, adversarial vulnerability) and connects them to real-world risks and realistic expectations for deployment in areas like healthcare, hiring, and governance. Read this if you want an accessible, skeptical toolkit for evaluating AI claims, asking the right technical and ethical questions, and deciding when to adopt, regulate, or mistrust specific AI applications.

Robotics for Kids : Learn coding while building Robots

Master the fundamentals of Arduino hardware and programming. Learn to design circuits, control LEDs, motors, and explore the fascinating world of sensors and ...

50+ Best AI Tools for Productivity in 2025 (ChatGPT, Canva, Notion & More!)

50+ Best AI Tools for Productivity in 2025 (ChatGPT, Canva, Notion & More!) Unlock your peak productivity in 2025 with the top ...

Robotics Introductory Course

This Udemy course teaches hands-on integration of sensors, motors, and controllers—practical wiring, motor driver setup, sensor interfacing, and controller tuning (e.g., PID) to implement closed-loop behaviors. It introduces ROS fundamentals by walking you through building ROS nodes and messages, using simulation tools (such as Gazebo), and assembling basic perception-to-action pipelines for real-time control. By completing guided projects like line-following and obstacle avoidance, you'll be able to prototype and debug simple autonomous robots and understand the hardware/software workflow needed to scale to more advanced systems.

Robotics & Mechatronics 1: Machine Theory & Production ...

This theoretical primer teaches practical machine theory and production-focused analysis—covering mechanical elements and kinematics, sensor/actuator selection and basic control principles, and how common manufacturing processes constrain design choices. You’ll learn to calculate load and torque requirements, model simple electromechanical systems, select components based on performance–cost tradeoffs, and anticipate production issues like tolerances and cycle-time impacts. If you plan to specify, prototype, or manage robotic/mechatronic equipment, the course shortens development time by giving a clear framework to translate functional specs into manufacturable designs and make informed procurement or prototyping decisions before tackling the hands‑on follow-ups.

Industrial Robotics

Learn all the theoretical and practical details to master industrial robotics: solve kinematic models; plan geometrical paths and dynamic trajectories.

Robotics for Everyone: Learn, Create, and Control

Apply robotics to real-world projects in automation and AI. Design, test, and troubleshoot robotic systems step by step.

KUKA.Sim Tutorials - Beginner Level Part 1

The course is designed for robotics engineers, students studying robotics and simulation, and enthusiasts eager to get into the simulation world of robotics.

HCIA - AI V3.0 (H13-311) Practice Test

Learned Knowledge:The cutting-edge AI technologies and development trends, the full-stack all-scenario AI strategy， and the algorithms and development practices related to traditional machine learning, deep learning, and development frameworks.Passing the HCIA-AI V3.0 certification will indicate that you: 1) Have mastered the AI development history, the Huawei Ascend AI system, the full-stack all-scenario AI strategy， and algorithms related to traditional machine learning and deep learning.2) Are able to build, train, and deploy neural networks by using development frameworks TensorFlow and MindSpore. 3) Competent in sales, marketing, product manager, project management, technical support, and other AI positions.Knowledge ContentAI OverviewMachine Learning OverviewDeep Learning OverviewMainstream Development Frameworks for AIHuawei AI Development Framework MindSporeHuawei AI Computing Platform AtlasHuawei Open AI Platform for Smart DevicesHUAWEI CLOUD Enterprise Intelligence Application PlatformComprehensive AI ExperimentHCIA-AIExam Code: H13-311Exam Type: Written examinationExam Format: Single-answer Question, Multiple-answer Question, True or false, Short Response Item, Drag and Drop ItemTime: 90minPassing Score/Total Score: 600/1000Language: Chinese,English, SpanishThe tests course was prepared for all those candidates who are planning of taking the HCIA-AI exam in the near future.This is an Unofficial course and this course is not affiliated, licensed, or trademarked with Huawei Technologies Co. Ltd in any way.

What are Generative AI models?

Learn more about watsonx → https://ibm.biz/BdvxDz Generative AI has stunned the world with its ability to create realistic images, ...

The Complete Machine Learning Roadmap

Go from zero to a machine learning engineer in 12 months. This step-by-step roadmap covers the essential skills you must learn ...

An Introduction to Generative Adversarial Networks (GANs)

In this video we look at some of the impressive applications of GANs and really understand why these networks are awesome.

20 Amazing Robot Animals That Will Blow Your Mind

Ultimate Fact presents Top 20 Amazing Robot Animals That Will Blow Your Mind. Millions of years of evolution have allowed ...

A Friendly Introduction to Generative Adversarial Networks (GANs)

Code: http://www.github.com/luisguiserrano/gans What is the simplest pair of GANs one can build? In this video (with code ...

We Built a Robot to Clean Our Whiteboard

This robot works as a waiter at a restaurant and is hilarious 😂

The Math Behind Generative Adversarial Networks Clearly Explained!

GAN is considered as one of the greatest breakthroughs in the field of Artificial Intelligence. In this video, I've tried my best to ...

AI, Machine Learning, Deep Learning and Generative AI Explained

Want to learn more about Agentic AI + Data? Register here → https://ibm.biz/BdeGLe Want to play with the technology yourself?

What are Generative Adversarial Networks (GANs) and how do they work?

Generative Adversarial Networks (GANs) are a powerful type of neural network used for unsupervised machine learning. They are ...

I Built a Neural Network from Scratch

Don't click this: https://tinyurl.com/bde5k7d5 Link to Code: https://www.patreon.com/greencode How I Learned This: ...

What Are GANs? | Generative Adversarial Networks Tutorial | Deep Learning Tutorial | Simplilearn

"️ Michigan Engineering - Professional Certificate in AI and Machine Learning ...

Large Language Models explained briefly

A light intro to LLMs, chatbots, pretraining, and transformers. Dig deeper here: ...