📊 Data Science & Analytics
Levels: Beginner | Intermediate | Advanced
Course Overview
The Data Science & Analytics course is designed to equip learners with the tools and techniques for collecting, analyzing, visualizing, and interpreting data to support data-driven decision-making. This hands-on, multi-level course blends statistics, programming, and business insight—preparing learners for modern roles in data analysis and science across industries.
Whether you’re new to data or looking to advance into machine learning and predictive modeling, this course provides a solid foundation and professional skill development.
Beginner Level
(Introduction to Data & Analytical Thinking)
What You Will Learn
Understanding types of data and data life cycle
Basics of statistical thinking and descriptive analytics
Introduction to Microsoft Excel/Google Sheets for data work
Visualizing data using charts, tables, and dashboards
Introduction to data ethics and interpretation
Basic introduction to databases and data structures
Target Audience
Beginners, business professionals, students, and anyone curious about data.
Course Duration
6 weeks (3 sessions per week, 2 hours per session)
Prerequisites
None
Intermediate Level
(Applied Data Analytics with Python & SQL)
What You Will Learn
Data manipulation using Python (Pandas, NumPy)
Introduction to SQL and querying relational databases
Exploratory data analysis and statistical inference
Data cleaning, formatting, and transformation
Building and customizing visualizations using Matplotlib/Seaborn
Working with real-world datasets and analytics projects
Target Audience
Graduates of the Beginner level, or professionals looking to apply coding to data tasks.
Course Duration
6 weeks (3 sessions per week, 2 hours per session)
Prerequisites
Completion of Beginner Level or prior basic programming knowledge
Advanced Level
(Machine Learning & Predictive Analytics)
What You Will Learn
Introduction to machine learning concepts and algorithms
Supervised vs. unsupervised learning techniques
Model building using Scikit-learn (regression, classification, clustering)
Evaluating model performance and fine-tuning
Introduction to AI, predictive analytics, and big data basics
Capstone project: Build and present a real-world data science project
Target Audience
Aspiring data scientists, analysts, and professionals looking to advance in tech, finance, health, or business.
Course Duration
6 weeks (3 sessions per week, 2 hours per session)
Prerequisites
Completion of Intermediate Level or solid understanding of Python & statistics
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
Data Analyst
Business Intelligence Analyst
Junior Data Scientist
Machine Learning Assistant
Research & Evaluation Associate
Reporting & Analytics Officer