diff --git a/README.md b/README.md
index 3fcc9c90..d0392011 100644
--- a/README.md
+++ b/README.md
@@ -43,49 +43,49 @@ For a gentle introduction to *AI in the Cloud* topics you may consider taking th
 <tr><td>1</td><td>Introduction and History of AI</td><td><a href="/lessons/1-Intro/README.md">Text</a></td><td></td><td></td><td></td></tr>
 
 <tr><td>II</td><td colspan="4"><b>Symbolic AI</b></td><td>PAT</td></tr>
-<tr><td>2 </td><td>Knowledge Representation and Expert Systems</td><td><a href="2-Symbolic/README.md">Text</a></td><td colspan="2"><a href="2-Symbolic/Animals.ipynb">Expert System</a>, <a href="2-Symbolic/FamilyOntology.ipynb">Ontology</a>, <a href="2-Symbolic/MSConceptGraph.ipynb">Concept Graph</a></td><td></td></tr>
-<tr><td>III</td><td colspan="4"><b><a href="3-NeuralNetworks/README.md">Introduction to Neural Networks</a></b></td><td>PAT</td></tr>
+<tr><td>2 </td><td>Knowledge Representation and Expert Systems</td><td><a href="/lessons/2-Symbolic/README.md">Text</a></td><td colspan="2"><a href="/lessons/2-Symbolic/Animals.ipynb">Expert System</a>, <a href="/lessons/2-Symbolic/FamilyOntology.ipynb">Ontology</a>, <a href="/lessons/2-Symbolic/MSConceptGraph.ipynb">Concept Graph</a></td><td></td></tr>
+<tr><td>III</td><td colspan="4"><b><a href="/lessons/3-NeuralNetworks/README.md">Introduction to Neural Networks</a></b></td><td>PAT</td></tr>
 <tr><td>3</td><td>Perceptron</td>
-   <td><a href="3-NeuralNetworks/03-Perceptron/README.md">Text</a>
-   <td colspan="2"><a href="3-NeuralNetworks/03-Perceptron/Perceptron.ipynb">Notebook</a></td><td><a href="3-NeuralNetworks/03-Perceptron/lab/README.md">Lab</a></td></tr>
-<tr><td>4 </td><td>Multi-Layered Perceptron and Creating our own Framework</td><td><a href="3-NeuralNetworks/04-OwnFramework/README.md">Text</a></td><td colspan="2"><a href="3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb">Notebook</a><td><a href="3-NeuralNetworks/04-OwnFramework/lab/README.md">Lab</a></td></tr> 
+   <td><a href="/lessons/3-NeuralNetworks/03-Perceptron/README.md">Text</a>
+   <td colspan="2"><a href="/lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb">Notebook</a></td><td><a href="/lessons/3-NeuralNetworks/03-Perceptron/lab/README.md">Lab</a></td></tr>
+<tr><td>4 </td><td>Multi-Layered Perceptron and Creating our own Framework</td><td><a href="/lessons/3-NeuralNetworks/04-OwnFramework/README.md">Text</a></td><td colspan="2"><a href="/lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb">Notebook</a><td><a href="/lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md">Lab</a></td></tr> 
 <tr><td>5</td>
    <td>Intro to Frameworks (PyTorch/TensorFlow)<br/>Overfitting</td>
-   <td><a href="3-NeuralNetworks/05-Frameworks/README.md">Text</a><br/><a href="3-NeuralNetworks/05-Frameworks/Overfitting.md">Text</a></td>
-   <td><a href="3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb">PyTorch</td>
-   <td><a href="3-NeuralNetworks/05-Frameworks/IntroKerasTF.md">Keras/TensorFlow</td>
-   <td><a href="3-NeuralNetworks/05-Frameworks/lab/README.md">Lab</a></td></tr>
-<tr><td>IV</td><td colspan="2"><b><a href="4-ComputerVision/README.md">Computer Vision</a></b></td>
+   <td><a href="/lessons/3-NeuralNetworks/05-Frameworks/README.md">Text</a><br/><a href="/lessons/3-NeuralNetworks/05-Frameworks/Overfitting.md">Text</a></td>
+   <td><a href="/lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb">PyTorch</td>
+   <td><a href="/lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.md">Keras/TensorFlow</td>
+   <td><a href="/lessons/3-NeuralNetworks/05-Frameworks/lab/README.md">Lab</a></td></tr>
+<tr><td>IV</td><td colspan="2"><b><a href="/lessons/4-ComputerVision/README.md">Computer Vision</a></b></td>
   <td><a href="https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-57639-dmitryso">MS Learn</a></td>
   <td><a href="https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-57639-dmitryso">MS Learn</a></td>
   <td>PAT</td></tr>
 <tr><td>6</td><td>Intro to Computer Vision. OpenCV</td><td>Text<td colspan="2">Notebook</td><td></td></tr>
-<tr><td>7</td><td>Convolutional Neural Networks<br/>CNN Architectures</td><td><a href="4-ComputerVision/07-ConvNets/README.md">Text</a><br/><a href="4-ComputerVision/07-ConvNets/CNN_Architectures.md">Text</a></td><td><a href="4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb">PyTorch</a></td><td><a href="4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb">TensorFlow</a></td><td><a href="4-ComputerVision/07-ConvNets/lab/README.md">Lab</a></td></tr>
-<tr><td>8</td><td>Pre-trained Networks and Transfer Learning<br/>Training Tricks</td><td><a href="4-ComputerVision/08-TransferLearning/README.md">Text</a><br/><a href="4-ComputerVision/08-TransferLearning/TrainingTricks.md">Text</a></td><td><a href="4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb">PyTorch</a></td><td><a href="4-ComputerVision/08-TransferLearning/TransferLearningTF.ipynb">TensorFlow</a><br/><a href="4-ComputerVision/08-TransferLearning/Dropout.ipynb">Dropout sample</a></td><td><a href="4-ComputerVision/08-TransferLearning/lab/README.md">Lab</a></td></tr>
-<tr><td>9</td><td>Autoencoders and VAEs</td><td><a href="4-ComputerVision/09-Autoencoders/README.md">Text</a></td><td><a href="4-ComputerVision/09-Autoencoders/AutoEncodersPytorch.ipynb">PyTorch</td><td><a href="4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb">TensorFlow</a></td><td></td></tr>
-<tr><td>10</td><td>Generative Adversarial Networks</td><td><a href="4-ComputerVision/10-GANs/README.md">Text</a></td><td><a href="4-ComputerVision/10-GANs/GANPyTorch.ipynb">PyTorch</td><td><a href="4-ComputerVision/10-GANs/GANTF.ipynb">TensorFlow</a></td><td></td></tr>
+<tr><td>7</td><td>Convolutional Neural Networks<br/>CNN Architectures</td><td><a href="/lessons/4-ComputerVision/07-ConvNets/README.md">Text</a><br/><a href="/lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md">Text</a></td><td><a href="/lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb">PyTorch</a></td><td><a href="/lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb">TensorFlow</a></td><td><a href="/lessons/4-ComputerVision/07-ConvNets/lab/README.md">Lab</a></td></tr>
+<tr><td>8</td><td>Pre-trained Networks and Transfer Learning<br/>Training Tricks</td><td><a href="/lessons/4-ComputerVision/08-TransferLearning/README.md">Text</a><br/><a href="/lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md">Text</a></td><td><a href="/lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb">PyTorch</a></td><td><a href="/lessons/4-ComputerVision/08-TransferLearning/TransferLearningTF.ipynb">TensorFlow</a><br/><a href="/lessons/4-ComputerVision/08-TransferLearning/Dropout.ipynb">Dropout sample</a></td><td><a href="/lessons/4-ComputerVision/08-TransferLearning/lab/README.md">Lab</a></td></tr>
+<tr><td>9</td><td>Autoencoders and VAEs</td><td><a href="/lessons/4-ComputerVision/09-Autoencoders/README.md">Text</a></td><td><a href="/lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPytorch.ipynb">PyTorch</td><td><a href="/lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb">TensorFlow</a></td><td></td></tr>
+<tr><td>10</td><td>Generative Adversarial Networks</td><td><a href="/lessons/4-ComputerVision/10-GANs/README.md">Text</a></td><td><a href="/lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb">PyTorch</td><td><a href="/lessons/4-ComputerVision/10-GANs/GANTF.ipynb">TensorFlow</a></td><td></td></tr>
 <tr><td>11</td><td>Object Detection</td><td>Text</td><td>PyTorch</td><td>TensorFlow</td><td></td></tr>
-<tr><td>12</td><td>Semantic Segmentation. U-Net</td><td><a href="4-ComputerVision/12-Segmentation/README.md">Text</a></td><td><a href="4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb">PyTorch</td><td><a href="4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb">TensorFlow</td><td></td></tr>
-<tr><td>V</td><td colspan="2"><b><a href="5-NLP/README.md">Natural Language Processing</a></b></td>
+<tr><td>12</td><td>Semantic Segmentation. U-Net</td><td><a href="/lessons/4-ComputerVision/12-Segmentation/README.md">Text</a></td><td><a href="/lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb">PyTorch</td><td><a href="/lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb">TensorFlow</td><td></td></tr>
+<tr><td>V</td><td colspan="2"><b><a href="/lessons/5-NLP/README.md">Natural Language Processing</a></b></td>
    <td><a href="https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-57639-dmitryso">MS Learn</a></td>
    <td><a href="https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-57639-dmitryso">MS Learn</a></td>
    <td>PAT</td></tr>
-<tr><td>13</td><td>Text Representation. Bow/TF-IDF</td><td><a href="5-NLP/13-TextRep/README.md">Text</a></td><td><a href="5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb">PyTorch</a></td><td><a href="5-NLP/13-TextRep/TextRepresentationTF.ipynb">TensorFlow</td><td></td></tr>
-<tr><td>14</td><td>Semantic word embeddings. Word2Vec and GloVe</td><td><a href="5-NLP/14-Embeddings/README.md">Text</td><td><a href="5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb">PyTorch</a></td><td><a href="5-NLP/14-Embeddings/EmbeddingsTF.ipynb">TensorFlow</a></td><td></td></tr>
-<tr><td>15</td><td>Language Modeling. Training your own embeddings</td><td><a href="5-NLP/15-LanguageModeling">Text</a></td><td>PyTorch</td><td>TensorFlow</td><td></td></tr>
-<tr><td>16</td><td>Recurrent Neural Networks</td><td><a href="5-NLP/16-RNN/README.md">Text</a></td><td><a href="5-NLP/16-RNN/RNNPyTorch.ipynb">PyTorch</a></td><td><a href="5-NLP/16-RNN/RNNTF.ipynb">TensorFlow</a></td><td></td></tr>
-<tr><td>17</td><td>Generative Recurrent Networks</td><td><a href="5-NLP/17-GenerativeNetworks/README.md">Text</a></td><td><a href="5-NLP/17-GenerativeNetworks/GenerativePyTorch.md">PyTorch</a></td><td><a href="5-NLP/17-GenerativeNetworks/GenerativeTF.md">TensorFlow</a></td><td></td></tr>
-<tr><td>18</td><td>Transformers. BERT.</td><td><a href="5-NLP/18-Transformers/README.md">Text</a></td><td><a href="5-NLP/18-Transformers/TransformersPyTorch.md">PyTorch</a></td><td><a href="5-NLP/18-Transformers/TransformersTF.md">TensorFlow</a></td><td></td></tr>
+<tr><td>13</td><td>Text Representation. Bow/TF-IDF</td><td><a href="/lessons/5-NLP/13-TextRep/README.md">Text</a></td><td><a href="/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb">PyTorch</a></td><td><a href="/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb">TensorFlow</td><td></td></tr>
+<tr><td>14</td><td>Semantic word embeddings. Word2Vec and GloVe</td><td><a href="/lessons/5-NLP/14-Embeddings/README.md">Text</td><td><a href="/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb">PyTorch</a></td><td><a href="/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb">TensorFlow</a></td><td></td></tr>
+<tr><td>15</td><td>Language Modeling. Training your own embeddings</td><td><a href="/lessons/5-NLP/15-LanguageModeling">Text</a></td><td>PyTorch</td><td>TensorFlow</td><td></td></tr>
+<tr><td>16</td><td>Recurrent Neural Networks</td><td><a href="/lessons/5-NLP/16-RNN/README.md">Text</a></td><td><a href="/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb">PyTorch</a></td><td><a href="/lessons/5-NLP/16-RNN/RNNTF.ipynb">TensorFlow</a></td><td></td></tr>
+<tr><td>17</td><td>Generative Recurrent Networks</td><td><a href="/lessons/5-NLP/17-GenerativeNetworks/README.md">Text</a></td><td><a href="/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md">PyTorch</a></td><td><a href="/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md">TensorFlow</a></td><td></td></tr>
+<tr><td>18</td><td>Transformers. BERT.</td><td><a href="/lessons/5-NLP/18-Transformers/README.md">Text</a></td><td><a href="/lessons/5-NLP/18-Transformers/TransformersPyTorch.md">PyTorch</a></td><td><a href="/lessons/5-NLP/18-Transformers/TransformersTF.md">TensorFlow</a></td><td></td></tr>
 <tr><td>19</td><td>Named Entity Recognition</td><td>Text</td><td>PyTorch</td><td>TensorFlow</td><td></td></tr>
 <tr><td>20</td><td>Large Language Models, Prompt Programming and Few-Shot Tasks</td><td>Text</td><td>PyTorch</td><td>TensorFlow</td><td></td></tr>
 <tr><td>VI</td><td colspan="4"><b>Other AI Techniques</b></td><td>PAT</td></tr>
-<tr><td>21</td><td>Genetic Algorithms</td><td><a href="6-Other/21-GeneticAlgorithms/README.md">Text</a><td colspan="2"><a href="6-Other/21-GeneticAlgorithms/Genetic.ipynb">Notebook</a></td><td></td></tr>
-<tr><td>22</td><td>Deep Reinforcement Learning</td><td><a href="6-Other/22-DeepRL/README.md">Text</a></td><td>PyTorch</td><td>TensorFlow</td><td></td></tr>
-<tr><td>23</td><td>Multi-Agent Systems</td><td><a href="6-Other/23-MultiagentSystems/README.md">Text</a></td><td></td><td></td><td></td></tr>
+<tr><td>21</td><td>Genetic Algorithms</td><td><a href="/lessons/6-Other/21-GeneticAlgorithms/README.md">Text</a><td colspan="2"><a href="/lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb">Notebook</a></td><td></td></tr>
+<tr><td>22</td><td>Deep Reinforcement Learning</td><td><a href="/lessons/6-Other/22-DeepRL/README.md">Text</a></td><td>PyTorch</td><td>TensorFlow</td><td></td></tr>
+<tr><td>23</td><td>Multi-Agent Systems</td><td><a href="/lessons/6-Other/23-MultiagentSystems/README.md">Text</a></td><td></td><td></td><td></td></tr>
 <tr><td>VII</td><td colspan="4"><b>AI Ethics</b></td><td>PAT</td></tr>
-<tr><td>24</td><td>AI Ethics and Responsible AI</td><td><a href="7-Ethics/README.md">Text</a></td><td></td><td></td><td></td></tr>
+<tr><td>24</td><td>AI Ethics and Responsible AI</td><td><a href="/lessons/7-Ethics/README.md">Text</a></td><td></td><td></td><td></td></tr>
 <tr><td></td><td colspan="4"><b>Extras</b></td><td></td></tr>
-<tr><td>1</td><td>Multi-Modal Networks, CLIP and VQGAN</td><td><a href="X-Extras/1-MultiModal/README.md">Text</a></td><td></td><td></td><td></td></tr>
+<tr><td>1</td><td>Multi-Modal Networks, CLIP and VQGAN</td><td><a href="/lessons/X-Extras/X1-MultiModal/README.md">Text</a></td><td></td><td></td><td></td></tr>
 </table>
 
 **[Mindmap of the Course](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
@@ -113,7 +113,7 @@ However, if you would like to take the course as a self-study project, we sugges
 
 > For further study, we recommend following these [Microsoft Learn](https://docs.microsoft.com/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-15963-cxa) modules and learning paths.
 
-**Teachers**, we have [included some suggestions](etc/for-teachers.md) on how to use this curriculum.
+**Teachers**, we have [included some suggestions](/etc/for-teachers.md) on how to use this curriculum.
 
 ---