- Understand the basic concepts of genetic algorithm and its applications.
- Understand the basic concepts of advanced machine learning algorithms.
- Apply the basic principles of advanced machine learning algorithms on example data.
Bachelor in CS
Data will be available soon!
| content serial | Description |
|---|
| 1 | Introduction |
| 2 | Genetic Algorithms |
| 3 | Genetic Programming Applications |
| 4 | Principal Component Analysis |
| 5 | Supervised Learning (Naive Bayes, K Nearest Neighbors) |
| 6 | Supervised Learning (Decision Trees, Random Forests, SVM) |
| 7 | Unsupervised Learning (Partitioning Clustering) |
| 8 | Unsupervised Learning (Hierarchical Clustering) |
| 9 | Unsupervised Learning (Density Based Clustering) |
| 10 | Recommendation Engines |
| 11 | Introduction to Deep Learning |
| 12 | Convolutional Neural Networks |
| 13 | New Trends in AI |
| 14 | Research Activities |
| 15 | Revision |
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