Description

This comprehensive course provides learners with a structured path to understanding and mastering the fundamental principles of Artificial Intelligence (AI). The curriculum is designed for beginning and intermediate learners and includes core knowledge, hands-on experience, and industry-relevant skills. By the end of this course, participants will be well-prepared to create AI-powered solutions and pursue higher certifications in the industry.

1. Introduction to Artificial Intelligence

This module introduces the concept of AI, its history, and its transformative impact on industries. Students will explore various types of AI and its ethical implications. By the end, learners will have a clear understanding of how AI fits into the broader technological landscape.

2. Foundations of Artificial Intelligence

The foundation module covers the essential mathematical and programming skills required for AI. Learners will gain proficiency in data representation, optimization techniques, and logic reasoning. This module builds the groundwork necessary for advanced AI topics.

3. Machine Learning of Artificial Intelligence

Focused on machine learning, this module dives into supervised, unsupervised, and reinforcement learning techniques. Participants will learn how to build predictive models, evaluate their performance, and apply machine learning to real-world datasets.

4. Deep Learning

This advanced module explores the architecture and functioning of deep learning models, including neural networks, CNNs, and RNNs. Participants will use frameworks like TensorFlow and PyTorch to develop and train models for complex tasks like image recognition and sequence processing.

5. AWS Certified AI Practitioner

Learners will explore cloud-based AI solutions, focusing on AWS tools like SageMaker and Rekognition. This module emphasizes practical implementation, scalability, and certification preparation for AWS AI Practitioner.

Requirements

• Basic knowledge of programming concepts like variables, loops, and functions.
• Basic understanding of linear algebra (matrices, vectors).
• Basic knowledge of programming concepts like variables, loops, and functions.