Machine Learning Programming
Duration
10 Weeks
Level
Not Specified
Total Credits
N/A
SAQA ID
Pending
Delivery Mode
Online
Qualification Details
Introduction
Learners develop practical machine learning programming skills, mastering data preparation, model training, evaluation, and deployment. The focus is on building functional AI models that solve actual business problems, fostering the ability to collaborate effectively with AI systems in professional settings.
Rules & Curriculum
Curriculum Breakdown
Module 0: Introduction & Orientation
Absolute Beginner Foundation Python & Math
Linear Algebra and Calculus refresh for ML.
Data Engineering for ML
ETL pipelines and feature engineering.
Advanced Supervised Learning
Ensemble methods, Random Forests, and SVMs.
Unsupervised Learning and Clustering
K-Means, DBSCAN, and PCA.
Deep Learning & CNNs
Convolutional Neural Networks for Image Recognition.
RNNs & NLP
Recurrent Neural Networks for Text and Time Series.
Reinforcement Learning
Q-Learning and Agents.
MLOps Principles
Model deployment, versioning, and monitoring.
Cloud ML Services
Using AWS SageMaker and Azure ML.
Final Architecture Project
Designing a scalable ML system.
Mentorship Catch-Up Sessions
Total Investment