AI & Machine Learning

Course Syllabus

Module 1 — Python for Data Science & Classical ML

• Python fundamentals for AI and machine learning
• NumPy, pandas, matplotlib, and scikit-learn
• Data preprocessing and visualisation
• Linear and logistic regression
• Decision trees and model evaluation

Module 2 — Neural Networks & Deep Learning

• Perceptron and neural network fundamentals
• Forward propagation and backpropagation
• Activation functions and optimisation
• TensorFlow and Keras introduction
• Build MLP models using the MNIST dataset

Module 3 — Computer Vision with CNNs

• Fundamentals of computer vision
• Convolution, pooling, and feature extraction
• CNN architectures and image classification
• Data augmentation techniques
• Transfer learning with ResNet models

Module 4 — NLP with RNNs & Transformers

• Text preprocessing and tokenisation
• Word embeddings and sequence modelling
• RNNs, LSTMs, and attention mechanisms
• Transformer architectures and BERT
• NLP applications and fine-tuning techniques

Module 5 — Unsupervised Learning & Generative AI

• Clustering and dimensionality reduction
• K-Means and PCA techniques
• Autoencoders and representation learning
• Introduction to GANs and Generative AI
• Ethical considerations in generative systems

Module 6 — MLOps & Capstone Project

• Introduction to MLOps and ML lifecycle
• Model tracking with MLflow
• Deploy AI apps using Gradio
• Responsible AI and model monitoring
• Final AI/ML capstone project presentation

Tools & Technologies

• Python
• NumPy
• pandas
• scikit-learn
• TensorFlow
• Keras
• OpenCV
• Hugging Face Transformers
• MLflow
• Gradio
• Google Colab

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Starting Date: 11th July 2026

Course Fee: £2990.00

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