Description
The 'Artificial Intelligence with Python' course offers a comprehensive introduction to AI using Python. It covers the fundamentals of machine learning, AI concepts, and Python programming. Participants will learn about neural networks, including their history, the relationship between biological and artificial neurons, and the mechanics of perceptrons and ANN architecture. The course also delves into activation functions, softmax, forward propagation, and loss functions, providing insights into how neural networks process data, make predictions, and measure error in classification and regression tasks.
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Learners will explore back propagation and gradient descent to understand how neural networks improve model performance during training. Practical implementation is a key focus, with hands-on experience using Keras and TensorFlow 2.0 to build neural network models. A demo using the MNIST dataset in Jupyter Notebook helps solidify these concepts. By the end of the course, participants will be able to explain neural network structures and training processes, build basic ANN models, and apply deep learning concepts to real-world tasks.
The course is free and self-paced, making it accessible to a wide audience, including aspiring data scientists, Python developers, computer science students, and tech professionals. It offers an industry-recognized certificate upon completion, enhancing career prospects. With over 91.6K learners enrolled and 10,000+ certificates claimed, this course is globally recognized and provides valuable skills in AI fundamentals, Python for AI, and neural networks.
- CategoryEducation & Research
- Pricing ModelFree
Artificial Intelligence with Python Course's Core Features
Covers machine learning fundamentals
Explains AI concepts and Python programming
Teaches neural networks and ANN architecture
Includes practical demos with Keras and TensorFlow
Offers hands-on experience with MNIST dataset
Provides industry-recognized certificate
Free and self-paced learning
Suitable for beginners with Python knowledge
Focuses on real-world AI applications
Explores back propagation and gradient descent
Teaches activation and loss functions
Includes quizzes and practice exercises
Guided projects for practical learning
Access to complete curriculum upon enrollment
Lifetime access to course materials
How to use Artificial Intelligence with Python Course?
Enroll: Sign up with your email
Access: Log in to the course platform
Learn: Follow the structured curriculum
Practice: Complete quizzes and exercises
Implement: Work on guided projects
Certify: Earn your course certificate
Artificial Intelligence with Python Course's Use Cases
- AI Fundamentals
- Python for AI
- Neural Networks Basics
- Model Training
- Real-world Applications
