COMPUTATIONAL AI
EXPERIMENTS

Gain practical experience in implementing machine learning algorithms using Scikit-Learn.

Understand the process of data preprocessing, model training, evaluation, and validation.

Develop critical thinking and problem-solving skills through hands-on machine learning projects.

Understand the architecture and function of convolutional neural networks.

Gain practical experience in building and training a CNN with real-world data.

Learn to evaluate model performance and understand basic image classification techniques.

Understand the concept of patterns and sequences.

Develop cognitive skills in identifying and continuing patterns.

Introduce the idea that machines like computers can also recognize patterns.

Develop critical thinking and observational skills by categorizing items based on their properties.

Enhance fine motor skills through the manipulation of small objects.

Learn vocabulary related to describing objects.

Learn basic programming concepts such as sequences, loops, conditional statements, and events.

Develop problem-solving and logical thinking skills.

Enhance creativity through digital storytelling and game design.

Understand basic concepts of NLP and machine learning.

Gain hands-on experience in coding and data analysis using Python.

Develop critical thinking skills through model evaluation and refinement.

Understand the basics of NLP and its application in chatbot development.

Gain hands-on experience in coding and algorithmic design using Python.

Develop problem-solving and critical thinking skills through chatbot implementation and testing.

Learn the fundamentals of computer vision and facial recognition.

Understand how to integrate and use various Python libraries for image processing.

Develop skills in real-time image processing and machine learning model integration.