Curious how AI models learn, think, and make decisions? This FREE AI Course for Beginners by Intellipaat is your one-stop learning path to master the fundamentals of Artificial Intelligence - no prior experience required! From understanding the topology of neural networks and core concepts like backpropagation and gradient descent, to diving deep into Convolutional Neural Networks (CNNs) and activation functions like ReLU, Sigmoid, and Tanh - this course walks you through it all with clear explanations and hands-on coding sessions.

You’ll build and validate custom neural network models, explore EDA for data visualization, use Keras and Python for model tuning, and end with real-world AI project ideas to showcase your skills. Perfect for beginners aiming to break into AI or upskill for data science and machine learning roles.

📖 Below are the concepts covered in the video on 'Artificial Intelligence Full Course '
00:00:00 - Introduction to FREE AI Course For Beginners
00:04:37 - Topology of Neural Network  
01:33:42 - Back Propagation  
01:56:48 - Gradient Descent Neural Network  
02:29:58 - Input Nodes Neural Networks  
02:53:16 - Convolutional Neural Network  
03:04:45 - Activation Function Neural Network  
03:15:04 - Sigmoid Activation Function  
03:21:24 - ReLU Activation Function  
03:24:51 - Leaky ReLU Activation Function  
03:31:20 - Tanh Activation Function  
03:35:27 - Synthetic Data  
03:41:31 - Create Custom Model Neural Network  
03:55:36 - Loss Activation Function  
04:00:28 - History Model Validation Verbose Function  
04:13:11 - Overall Text Dataset Loss Model  
04:15:47 - Validation Explain  
04:37:00 - Moto Pilot  
04:42:38 - Sample Data Build  
05:00:36 - Simple Neural Network  
05:17:40 - EDA Visualization  
06:07:41 - RFF Neural Network  
06:30:51 - Start Building Our Model  
06:37:49 - Initial Model  
06:59:42 - Multiple Layers Array  
07:15:58 - Hyperparameter  
07:56:26 - Loss of Accuracy  
08:04:55 - Plot Visual Data  
09:04:03 - Python Basic Model  
09:12:24 - Keras Tuner Function  
09:17:04 - Building Decision Tree  
09:20:13 - Hyperparameter Tuning Build Model  
10:40:28 - Top 10 AI Projects  

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🔥Enroll for Data Science & Artificial Intelligence: https://intellipaat.com/epgc-data-science-ai-ihubds-iit-roorkee/

➡️ About the Course
Become an expert in Data Science, Machine Learning and Artificial Intelligence with iHUB DivyaSampark, IIT Roorkee & Intellipaat! Build a strong foundation in data science by learning in-demand skills, solving real-world challenges, and working on real-world projects. A flexible learning environment and 24/7 support makes this course perfect for beginners and professionals alike. Join now and accelerate your career to new heights in the cutting-edge fields of data science, machine learning, and artificial intelligence!

✅ Key Features - (Course Features)
👉🏼620 Hrs of Applied Learning
👉🏼90+ Live Sessions Across 11 months
👉🏼218 Hrs of Self-Paced Learning
👉🏼Learn from IIT Faculty & Industry Practitioners
👉🏼50+ Industry Projects & Case Studies
👉🏼One-on-One with Industry Mentors
👉🏼24*7 Support
👉🏼Dedicated Learning Management Team
👉🏼1:1 Mock Interview
👉🏼No-Cost EMI Option
👉🏼iHUB DivyaSampark, IIT Roorkee Certification
👉🏼Designed for Working Professionals and Freshers
👉🏼2 Days Campus Immersion at iHUB, IIT Roorkee
👉🏼Up to Rs. 50 Lakhs startup Incubation Support*
👉🏼3 Guaranteed Job Interviews upon movement to Placement Pool

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📚For more information, please write back to us at sales@intellipaat.com or call us at IND: +91-7022374614 / US : 1-800-216-8930

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A comprehensive beginner's course covering artificial intelligence fundamentals, focusing on neural networks from basic concepts to practical implementation. The course explains neural network architecture including input layers, hidden layers, and output layers, along with concepts like weights, biases, and activation functions. It covers the mathematical foundations behind neural networks, forward and backward propagation, and practical examples using tools like Python, PyTorch, and TensorFlow. The content includes hands-on examples such as predicting productivity scores based on sleep, coffee consumption, and travel time, demonstrating how neural networks can approximate complex data relationships.

Artificial Intelligence Full Course (2025) | FREE AI Course For Beginners | Intellipaat