Course Curriculum
Detailed breakdown of topics and learning materials
Artificial Intelligence concepts
Introduction to Artificial Intelligence - Session 1
Introduction to Artificial Intelligence - Session 2
Introduction to Artificial Intelligence - Session 3
Introduction to Artificial Intelligence - Session 4
Introduction to Artificial Intelligence - Session 5
Introduction to Artificial Intelligence - Session 6
Introduction to Artificial Intelligence - Session 7
Introduction to Artificial Intelligence - Review session
Overview of AI, what it is, examples, and applications in healthcare, business, education, autonomous vehicles, and more
No learning materials available for this topic yet.
Definition of ML, types of machine learning (supervised, unsupervised, semi-supervised, reinforcement learning), key terms and definitions
No learning materials available for this topic yet.
Labeled data training, classification and regression algorithms, cost functions, and practical applications
No learning materials available for this topic yet.
Clustering, association, recommendation systems, and working with unlabeled data
No learning materials available for this topic yet.
Neural network architecture, CNNs for image processing, RNNs for sequential data, and LSTMs for long-term dependencies
No learning materials available for this topic yet.
NumPy, Pandas, Matplotlib, and Scikit-learn for data manipulation, visualization, and machine learning
No learning materials available for this topic yet.
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