1. Artificial Intelligence Fundamentals
This course introduces the basic concepts of Artificial Intelligence, including how AI works, its applications, and common AI techniques. Students learn about machine learning, neural networks, data processing, and real-world uses of AI. It is suitable for beginners who want to build a strong foundation in AI.
2. Machine Learning
This course focuses on teaching computers to learn from data and make predictions or decisions. Topics typically include supervised and unsupervised learning, regression, classification, clustering, model evaluation, and practical projects using Python.
3. Deep Learning
This course covers advanced machine-learning techniques based on artificial neural networks. Students learn about neural networks, CNNs, RNNs, training models, and applications such as image recognition, natural-language processing, and computer vision.
4. Generative AI
This course introduces AI systems that can generate new content such as text, images, code, and other media. Students learn about large language models, prompt engineering, AI tools, and practical applications of Generative AI in business and everyday work.