🤖 Artificial Intelligence (AI) & Machine Learning
Levels: Beginner | Intermediate | Advanced
Course Overview
The AI & Machine Learning course introduces learners to the exciting world of intelligent systems and algorithms that can learn from data. Designed for both aspiring tech professionals and curious learners, this program moves from fundamental concepts to hands-on application using industry tools like Python, Scikit-learn, and TensorFlow.
By the end of the course, learners will be equipped to build, train, and deploy basic AI/ML models for real-world scenarios in business, health, finance, and beyond.
Beginner Level
(Foundations of AI & Machine Learning)
What You Will Learn
What is AI? History, impact, and future trends
Fundamentals of machine learning and data science
Basics of statistics and probability for ML
Introduction to Python for AI (Jupyter Notebooks, Numpy, Pandas)
Data preparation and visualization techniques
Understanding datasets, features, and labels
Target Audience
Beginners, students, and professionals with an interest in AI and data but no prior experience required.
Course Duration
6 weeks (3 sessions per week, 2 hours per session)
Prerequisites
Basic computer skills. No coding background required.
Intermediate Level
(Supervised & Unsupervised Machine Learning)
What You Will Learn
Supervised learning: regression & classification
Unsupervised learning: clustering & dimensionality reduction
Model evaluation: accuracy, precision, recall, confusion matrix
Hands-on with Scikit-learn for model building
Data splitting, cross-validation, and overfitting management
Working with real datasets (CSV, APIs)
Target Audience
Learners with basic programming and data handling knowledge, or graduates of the Beginner level.
Course Duration
6 weeks (3 sessions per week, 2 hours per session)
Prerequisites
Completion of Beginner Level or basic knowledge of Python and data analysis
Advanced Level
(Deep Learning & AI Applications)
What You Will Learn
Neural networks and deep learning fundamentals
Building and training models using TensorFlow/Keras
Convolutional Neural Networks (CNNs) for image recognition
Introduction to Natural Language Processing (NLP)
Deploying AI models on web or cloud platforms
Capstone project: develop a full AI/ML solution
Target Audience
Advanced learners, developers, data scientists, and professionals pursuing AI/ML careers or research.
Course Duration
6 weeks (3 sessions per week, 2 hours per session)
Prerequisites
Completion of Intermediate Level or strong background in Python and ML concepts
Fees
Application Fee: UGX 30,000/=
Tuition Fee: UGX 550,000/= (Per Level)
Certification
Certificate of Completion awarded at each level by Billbrain Institute of Technology
Career Pathways
Machine Learning Engineer
AI Developer
Data Scientist
AI Research Assistant
AI/ML Product Analyst
Robotics & Automation Support Roles