diff --git a/python/Modulo-09-Data-IA/81-numpy/reto.py b/python/Modulo-09-Data-IA/81-numpy/reto.py
new file mode 100644
index 0000000..f6d9649
--- /dev/null
+++ b/python/Modulo-09-Data-IA/81-numpy/reto.py
@@ -0,0 +1,8 @@
+# Copyright (C) 2026 Alenia Studios
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import numpy as np
+
+precios_base = np.array([50, 120, 300, 45])
+precios_descuento = precios_base - 20
+print(precios_descuento)
diff --git a/python/Modulo-09-Data-IA/82-pandas/reto.py b/python/Modulo-09-Data-IA/82-pandas/reto.py
new file mode 100644
index 0000000..48f2e68
--- /dev/null
+++ b/python/Modulo-09-Data-IA/82-pandas/reto.py
@@ -0,0 +1,13 @@
+# Copyright (C) 2026 Alenia Studios
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import pandas as pd
+
+boleta_calificaciones = {
+    "Alumno": ["Juan", "Maria", "Pedro"],
+    "Matematicas": [85, 95, 70],
+    "Historia": [90, 88, 75]
+}
+
+registro_oficial = pd.DataFrame(boleta_calificaciones)
+print(registro_oficial)
diff --git a/python/Modulo-09-Data-IA/83-limpieza-datos/reto.py b/python/Modulo-09-Data-IA/83-limpieza-datos/reto.py
new file mode 100644
index 0000000..be87917
--- /dev/null
+++ b/python/Modulo-09-Data-IA/83-limpieza-datos/reto.py
@@ -0,0 +1,13 @@
+# Copyright (C) 2026 Alenia Studios
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import pandas as pd
+
+inventario_sucio = {
+    "Zapato": ["Tenis", "Bota", "Sandalia", "Mocasín"],
+    "Precio": [50, None, 15, None]
+}
+
+tabla_inventario = pd.DataFrame(inventario_sucio)
+tabla_salvada = tabla_inventario.fillna(10)
+print(tabla_salvada)
diff --git a/python/Modulo-09-Data-IA/84-matplotlib/reto.py b/python/Modulo-09-Data-IA/84-matplotlib/reto.py
new file mode 100644
index 0000000..940d3c7
--- /dev/null
+++ b/python/Modulo-09-Data-IA/84-matplotlib/reto.py
@@ -0,0 +1,10 @@
+# Copyright (C) 2026 Alenia Studios
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import matplotlib.pyplot as plt
+
+meses = ["Enero", "Febrero", "Marzo", "Abril"]
+pesos = [2, 4, 7, 11]
+
+plt.plot(meses, pesos)
+plt.show()
diff --git a/python/Modulo-09-Data-IA/85-scikit-learn/reto.py b/python/Modulo-09-Data-IA/85-scikit-learn/reto.py
new file mode 100644
index 0000000..6b4735e
--- /dev/null
+++ b/python/Modulo-09-Data-IA/85-scikit-learn/reto.py
@@ -0,0 +1,14 @@
+# Copyright (C) 2026 Alenia Studios
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import sklearn
+from sklearn.linear_model import LinearRegression
+
+grados_pasado = [[10], [20], [30]]
+ventas_pasado = [20, 40, 60]
+
+modelo = LinearRegression()
+modelo.fit(grados_pasado, ventas_pasado)
+
+prediccion = modelo.predict([[40]])
+print(prediccion)
diff --git a/python/Modulo-09-Data-IA/86-regresion/reto.py b/python/Modulo-09-Data-IA/86-regresion/reto.py
new file mode 100644
index 0000000..fdc1734
--- /dev/null
+++ b/python/Modulo-09-Data-IA/86-regresion/reto.py
@@ -0,0 +1,17 @@
+# Copyright (C) 2026 Alenia Studios
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+from sklearn.linear_model import LinearRegression
+import matplotlib.pyplot as plt
+
+temperaturas = [[15], [20], [25], [30]]
+vasos_reales = [10, 22, 35, 48]
+
+modelo = LinearRegression()
+modelo.fit(temperaturas, vasos_reales)
+
+predicciones = modelo.predict(temperaturas)
+
+plt.scatter(temperaturas, vasos_reales)
+plt.plot(temperaturas, predicciones)
+plt.show()
diff --git a/python/Modulo-09-Data-IA/87-clasificacion/reto.py b/python/Modulo-09-Data-IA/87-clasificacion/reto.py
new file mode 100644
index 0000000..2311e2d
--- /dev/null
+++ b/python/Modulo-09-Data-IA/87-clasificacion/reto.py
@@ -0,0 +1,13 @@
+# Copyright (C) 2026 Alenia Studios
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+from sklearn.tree import DecisionTreeClassifier
+
+X = [[0, 2], [1, 5], [10, 50], [15, 80]]
+y = ["Normal", "Normal", "Spam", "Spam"]
+
+modelo = DecisionTreeClassifier()
+modelo.fit(X, y)
+
+prediccion = modelo.predict([[12, 60]])
+print(prediccion)
diff --git a/python/Modulo-09-Data-IA/88-nlp/reto.py b/python/Modulo-09-Data-IA/88-nlp/reto.py
new file mode 100644
index 0000000..9b5b287
--- /dev/null
+++ b/python/Modulo-09-Data-IA/88-nlp/reto.py
@@ -0,0 +1,14 @@
+# Copyright (C) 2026 Alenia Studios
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+from sklearn.feature_extraction.text import CountVectorizer
+
+resenas = [
+    "La comida es excelente",
+    "La comida es terrible",
+    "Excelente servicio"
+]
+
+traductor = CountVectorizer()
+matriz_numeros = traductor.fit_transform(resenas)
+print(matriz_numeros.toarray())
diff --git a/python/Modulo-09-Data-IA/89-llms/reto.py b/python/Modulo-09-Data-IA/89-llms/reto.py
new file mode 100644
index 0000000..49238b3
--- /dev/null
+++ b/python/Modulo-09-Data-IA/89-llms/reto.py
@@ -0,0 +1,25 @@
+# Copyright (C) 2026 Alenia Studios
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import time
+
+def oraculo_clima(prompt):
+    time.sleep(1)
+    prompt_limpio = prompt.lower()
+    if "madrid" in prompt_limpio:
+        return "En Madrid hará sol, 25 grados."
+    elif "londres" in prompt_limpio:
+        return "En Londres lloverá, no olvides tu paraguas."
+    else:
+        return "Lo siento, mis satélites no llegan ahí aún."
+
+print("Consultando a los astros por Madrid...")
+print(f"🤖 Oráculo: {oraculo_clima('Madrid')}")
+print()
+
+print("Consultando a los astros por Londres...")
+print(f"🤖 Oráculo: {oraculo_clima('Londres')}")
+print()
+
+print("Consultando a los astros por Bogotá...")
+print(f"🤖 Oráculo: {oraculo_clima('Bogotá')}")
diff --git a/python/Modulo-09-Data-IA/90-RETO-predictor/reto.py b/python/Modulo-09-Data-IA/90-RETO-predictor/reto.py
new file mode 100644
index 0000000..0fdff40
--- /dev/null
+++ b/python/Modulo-09-Data-IA/90-RETO-predictor/reto.py
@@ -0,0 +1,17 @@
+# Copyright (C) 2026 Alenia Studios
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+from sklearn.linear_model import LinearRegression
+
+print("Entrenando al tasador automático...")
+tamaños = [[50], [80], [100], [150]]
+precios = [100, 160, 200, 300]
+
+modelo = LinearRegression()
+modelo.fit(tamaños, precios)
+print("¡Entrenamiento completado!")
+
+print("Calculando precio para una casa de 120 metros cuadrados...")
+prediccion = modelo.predict([[120]])
+
+print(f"🔮 El precio sugerido es: ${prediccion[0]} miles de dólares.")