Data Science
Overview
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Duration
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Program Description
Data Science teaches you how to collect, clean, analyze and present data to solve real problems with technology. In simple terms, you will study mathematics and statistics, programming (Python or R), databases and data visualization, plus basics of machine learning and project work. The program trains you to turn numbers into clear answers that guide decisions in businesses, government and engineering projects. Career paths include data analyst, junior data scientist, business intelligence roles, software engineering support roles, and technical roles in engineering firms that use data for design and planning. This course opens doors to internships, tech jobs and further study in computing, engineering and analytics. Stay curious and persistent, and you can build a strong technology career.
Aims & Objectives
Develop ability to collect and clean datasets using common tools, measured by completion of at least three real-data projects.
Master core programming for data tasks, demonstrated by writing reproducible scripts in Python or R for data analysis.
Understand and apply basic statistical methods and model evaluation, shown by correctly interpreting test results and model metrics.
Create clear visualizations and reports, evidenced by producing dashboards or presentations that explain data findings to non-technical audiences.
Why Choose This Program?
Strong job demand
Employers across Ghana and globally seek people who can turn data into decisions, giving graduates many entry-level roles.
Wide industry application
Skills apply in business, healthcare, banking, agriculture and engineering, so you can work in sectors you care about.
Hands-on learning and internships
Coursework focuses on projects, and schools often connect students with local companies or labs for practical experience.
Pathway to higher study and innovation
Provides a foundation for university programs, tech entrepreneurship, or specialised AI and analytics careers.
Skills & Tools
Skills You'll Develop
Use Python or R to load, clean and manipulate data, write scripts, and automate analysis using libraries like pandas or tidyverse.
Extract and store data using SQL and tools for cleaning, merging and preparing datasets for analysis.
Apply descriptive statistics, hypothesis testing and simple predictive models using scikit-learn or caret, and evaluate model performance.
Create charts and dashboards with Matplotlib, Seaborn, ggplot2 or beginner BI tools to communicate findings clearly.
Tools & Resources
Python with Jupyter Notebook and pandas
R with RStudio
SQLite or MySQL for basic databases
Challenges & Tips
Challenges
Difficulty with mathematics and statistics
Steep learning curve for programming
Tips & Advice
Start with basic algebra and descriptive statistics, use visual examples, and practice with simple datasets to build confidence.
Learn by doing small projects, follow guided tutorials, and pair up with classmates for practice and code review.
Video Guide
Frequently Asked Questions
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