What does the Artificial Intelligence Mastery course cover?
Artificial Intelligence Mastery is covered here in 10 modules: Introduction to Artificial Intelligence: History of AI, Python for AI: Python Libraries for AI: NumPy, Pandas, and Matplotlib, Deep Learning Fundamentals: Backpropagation and Optimization Algorithms and 7 more. The outline lists 39 specific topics, opening with What is Artificial Intelligence? and closing with Certificate of Completion : Issued by The Art of Service.
How do you approach Artificial Intelligence Mastery step by step?
The work is sequenced in 10 stages. It starts with Introduction to Artificial Intelligence: History of AI, moves through Python for AI: Python Libraries for AI: NumPy, Pandas, and Matplotlib and Deep Learning Fundamentals: Backpropagation and Optimization Algorithms, and ends at Final Project and Course Wrap-Up: Course Wrap-Up: Review and Q&A.
What is in Module 1 of the Artificial Intelligence Mastery course?
Module 1 is Introduction to Artificial Intelligence: History of AI. It works through What is Artificial Intelligence?, history of AI, Types of AI: Narrow, General, and Superintelligence and 1 more. It sets the vocabulary the remaining 9 modules build on.
How is the Artificial Intelligence Mastery course delivered?
The Artificial Intelligence Mastery course is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. It can be taken on any device, and a certificate of completion is issued by The Art of Service when you finish.
How much does the Artificial Intelligence Mastery course cost?
The Artificial Intelligence Mastery course is $199 as a one time payment. There is no subscription, no per seat licence and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.
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Artificial Intelligence Mastery: Build and Deploy Scalable AI Models with Deep Learning and Python
Course Overview
This comprehensive course is designed to help you master the concepts of Artificial Intelligence (AI) and Deep Learning (DL) using Python. You will learn how to build and deploy scalable AI models, and gain hands-on experience with real-world applications. Upon completion, you will receive a certificate issued by The Art of Service.Course Curriculum
Module 1. Introduction to Artificial Intelligence: History of AI
- What is Artificial Intelligence?
- History of AI
- Types of AI: Narrow, General, and Superintelligence
- AI Applications: Computer Vision, Natural Language Processing, and Robotics
Module 2. Python for AI: Python Libraries for AI: NumPy, Pandas, and Matplotlib
- Introduction to Python
- Python Basics: Variables, Data Types, Loops, and Functions
- Python Libraries for AI: NumPy, Pandas, and Matplotlib
- Hands-on Project: Building a Simple AI Model using Python
Module 3. Deep Learning Fundamentals: Backpropagation and Optimization Algorithms
- What is Deep Learning?
- Types of Neural Networks: Feedforward, Recurrent, and Convolutional
- Activation Functions: Sigmoid, ReLU, and Softmax
- Backpropagation and Optimization Algorithms
Module 4. Convolutional Neural Networks (CNNs): Pooling Layers: Max Pooling and Average Pooling
- Introduction to CNNs
- Convolutional Layers: Filters, Stride, and Padding
- Pooling Layers: Max Pooling and Average Pooling
- Hands-on Project: Building a CNN for Image Classification
Module 5. Recurrent Neural Networks (RNNs): Simple RNNs: Architecture and Training
- Introduction to RNNs
- Simple RNNs: Architecture and Training
- Long Short-Term Memory (LSTM) Networks
- Hands-on Project: Building an RNN for Time Series Forecasting
Module 6. Natural Language Processing (NLP): Word Embeddings: Word2Vec and GloVe
- Introduction to NLP
- Text Preprocessing: Tokenization, Stopwords, and Stemming
- Word Embeddings: Word2Vec and GloVe
- Hands-on Project: Building an NLP Model for Sentiment Analysis
Module 7. Transfer Learning and Fine-Tuning: Pre-trained Models: VGG16, ResNet50, and InceptionV3
- Introduction to Transfer Learning
- Pre-trained Models: VGG16, ResNet50, and InceptionV3
- Fine-Tuning: Adapting Pre-trained Models to Your Dataset
- Hands-on Project: Fine-Tuning a Pre-trained Model for Image Classification
Module 8. Deploying AI Models: Introduction to Model Deployment, Containerization: Docker and Kubernetes
- Introduction to Model Deployment
- Model Serving: TensorFlow Serving and AWS SageMaker
- Containerization: Docker and Kubernetes
- Hands-on Project: Deploying an AI Model using TensorFlow Serving
Module 9. Real-World Applications of AI: Hands-on Project: Building a Real-World AI Application
- Computer Vision: Object Detection, Segmentation, and Generation
- NLP: Chatbots, Sentiment Analysis, and Text Summarization
- Robotics: Autonomous Vehicles and Human-Robot Interaction
- Hands-on Project: Building a Real-World AI Application
Module 10. Final Project and Course Wrap-Up: Course Wrap-Up: Review and Q&A
- Final Project: Building a Scalable AI Model
- Course Wrap-Up: Review and Q&A
- Certificate of Completion: Issued by The Art of Service
Course Features
- Interactive and Engaging: Quizzes, Games, and Hands-on Projects
- Comprehensive: Covers AI, DL, and Python Fundamentals
- Personalized: Tailored to Your Learning Style and Goals
- Up-to-date: Latest AI and DL Techniques and Tools
- Practical: Real-World Applications and Case Studies
- Expert Instructors: Industry Practitioners with Real-World Experience
- Certification: Receive a Certificate upon Completion
- Flexible Learning: Self-Paced and Mobile-Accessible
- Community-Driven: Discussion Forums and Live Support
- Actionable Insights: Hands-on Projects and Real-World Examples
- Bite-Sized Lessons: Easy to Digest and Retain
- Lifetime Access: Learn at Your Own Pace
- Gamification: Track Your Progress and Compete with Peers