diff --git a/.gitignore b/.gitignore
index 7cffbf3..9d939e3 100644
--- a/.gitignore
+++ b/.gitignore
@@ -2,3 +2,5 @@
 venv/
 .venv/
 
+subject_embeddings/categories_embeddings_full.csv
+subject_embeddings/courses_embeddings_full.csv
diff --git a/requirements.txt b/requirements.txt
index 209b006..c9aff45 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -41,3 +41,4 @@ tzdata==2024.1
 urllib3==2.2.1
 wasabi==1.1.2
 weasel==0.3.4
+sentence-transformers
diff --git a/subject_embeddings/categories.csv b/subject_embeddings/categories.csv
new file mode 100644
index 0000000..eed0070
--- /dev/null
+++ b/subject_embeddings/categories.csv
@@ -0,0 +1,21 @@
+architecture
+area and gender studies
+business
+communication and information sciences
+education
+fine and performing arts
+history
+interdisciplinary
+language and literature
+law and legal studies
+philosophy and religious studies
+social sciences
+agriculture
+behavioural sciences
+biological sciences
+ecosystem sciences
+engineering
+environmental sciences
+geosciences
+health and medical sciences
+mathematical and physical sciences
\ No newline at end of file
diff --git a/subject_embeddings/categories_embeddings.csv b/subject_embeddings/categories_embeddings.csv
new file mode 100644
index 0000000..4e77344
--- /dev/null
+++ b/subject_embeddings/categories_embeddings.csv
@@ -0,0 +1,21 @@
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diff --git a/subject_embeddings/courses_embeddings.csv b/subject_embeddings/courses_embeddings.csv
new file mode 100644
index 0000000..0c3a0e6
--- /dev/null
+++ b/subject_embeddings/courses_embeddings.csv
@@ -0,0 +1,8258 @@
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diff --git a/subject_embeddings/embeddings.py b/subject_embeddings/embeddings.py
new file mode 100644
index 0000000..de91e5d
--- /dev/null
+++ b/subject_embeddings/embeddings.py
@@ -0,0 +1,33 @@
+import csv
+import numpy as np
+from sentence_transformers import SentenceTransformer
+
+# Load the model
+model = SentenceTransformer("paraphrase-MiniLM-L6-v2")
+
+# Load the courses
+with open("../courses.csv", newline="") as f:
+    courses = [row for row in csv.reader(f)]
+print(len(courses))
+
+# Compute the embeddings
+embeddings = []
+for course in courses:
+    embeddings.append(model.encode(course)[0])
+embeddings_array = np.array(embeddings)
+print(embeddings_array.shape)
+np.savetxt("courses_embeddings_full.csv", embeddings_array, delimiter=",")
+
+# Load the categories
+with open("categories.csv", newline="") as f:
+    reader = csv.reader(f)
+    categories = list(reader)
+print(len(categories))
+
+# Category embeddings
+embeddings = []
+for category in categories:
+    embeddings.append(model.encode(category)[0])
+embeddings_array = np.array(embeddings)
+print(embeddings_array.shape)
+np.savetxt("categories_embeddings_full.csv", embeddings_array, delimiter=",")
diff --git a/subject_embeddings/embeddings_pca.py b/subject_embeddings/embeddings_pca.py
new file mode 100644
index 0000000..7329f5e
--- /dev/null
+++ b/subject_embeddings/embeddings_pca.py
@@ -0,0 +1,38 @@
+import numpy as np
+from sklearn.decomposition import PCA
+from scipy.spatial.distance import cdist
+import pandas as pd
+import csv
+
+# Load the courses
+with open("../courses.csv", newline="") as f:
+    courses = [row[0] for row in csv.reader(f)]
+print(len(courses))
+
+# Load the categories
+with open("categories.csv", newline="") as f:
+    categories = [row[0] for row in csv.reader(f)]
+print(len(categories))
+
+# Embeddings
+embeddings_array = np.loadtxt("courses_embeddings_full.csv", delimiter=",")
+categories_embeddings_array = np.loadtxt(
+    "categories_embeddings_full.csv", delimiter=","
+)
+
+# PCA
+pca = PCA(n_components=8)
+pca_embeddings = pca.fit_transform(embeddings_array)
+print(pca_embeddings.shape)
+
+# Category PCA
+pca_categories = pca.transform(categories_embeddings_array)
+
+# Save the embeddings
+np.savetxt("courses_embeddings.csv", pca_embeddings, delimiter=",")
+np.savetxt("categories_embeddings.csv", pca_categories, delimiter=",")
+
+# Distances
+subject_distances = cdist(embeddings_array, categories_embeddings_array)
+df = pd.DataFrame(subject_distances, columns=categories, index=courses)
+df.to_csv("subject_distances.csv")
diff --git a/subject_embeddings/subject_distances.csv b/subject_embeddings/subject_distances.csv
new file mode 100644
index 0000000..9f48285
--- /dev/null
+++ b/subject_embeddings/subject_distances.csv
@@ -0,0 +1,8259 @@
+,architecture,area and gender studies,business,communication and information sciences,education,fine and performing arts,history,interdisciplinary,language and literature,law and legal studies,philosophy and religious studies,social sciences,agriculture,behavioural sciences,biological sciences,ecosystem sciences,engineering,environmental sciences,geosciences,health and medical sciences,mathematical and physical sciences
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+politics and tourism,10.404288966214468,9.638579808534143,9.143130820188498,9.526183759270378,10.593659237385074,9.913223029238452,8.734578540552567,10.22610876604146,8.939003593377258,9.879556475863769,9.107574154736703,9.627888156746751,10.601617416193962,10.460476524442907,10.997917489439555,10.30211555775772,10.718776521408994,10.244148311349166,9.141442079435565,10.313555654174698,10.528809386677457
+spanish and philosophy,9.805568471044062,9.270564410812206,9.796206628244448,9.54934711767369,9.914535847212699,8.904093602875731,8.918039475624505,9.497338490070321,7.07154328309514,9.537701676836445,6.936960124617916,9.315850424581583,10.576521476238325,9.355136000629814,10.116440086002683,10.247178688822482,9.980211907304032,9.985323583252715,9.429872654533163,9.644262241761776,9.520856679794026
+global business,10.47904518197532,9.97978050760422,5.972396830476709,9.166215499373221,10.36110655796623,10.445574608119342,9.729093915667985,9.707081434919903,9.470049034479311,10.474987785226473,9.857380496040669,9.619589186811872,10.057872362282504,9.871842541010631,10.038230536637553,10.244546997069076,9.5345868387692,9.603476494448609,9.538486239853436,9.361707071873036,9.870574835315157
+french and norwegian,10.945192358531903,9.50157696053136,10.044652039357107,10.019795302012641,10.661907148794349,10.053238384865624,8.898953310706135,9.813076109879523,7.923883495594992,9.988031057917935,9.200198903288046,9.78073635770765,10.859383059010936,10.424183161592303,10.257210201003039,10.943637740502135,10.847010854435599,10.251854292785925,10.189820020450998,9.559961385195397,9.76204699169565
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