Data Analytics
Master Excel, SQL, Power BI, and Python to uncover insights and communicate them through compelling data stories. Build the skills and confidence to support smarter, insight-led decisions in any organization.
2026 Intakes Ongoing
Full Time | Hybrid
- Start Data: 5th October, 2026
- Course Duration: 12 Weeks + Up to 6 months of internship
- Mode of Learning: Hybrid | 3 Days Online, 1 Day In-Person
- Class Schedule: Tues – Fri | 9:00 AM – 4:00 PM
- Tuition Fee: GHC 10,350 - GHC 14,000
- Download fee installment plans here
Part-Time | Remote
- Start Data: 5th October, 2026
- Course Duration: 24 Weeks + Freelance Support
- Mode of Learning: Online
- Class Schedule: Mon, Wed & FrI | 7:00 PM – 9:00 PM
- Tuition Fee: GHC 9,350 - GHC 12,000
- Download fee installment plans here
Sponsored Fellowship
- **For individuals from low-income backgrounds.
- Start Data: 21st September, 2026
- Mode of Learning: 12 Weeks | Hybrid [3 Days Online, 1 Day In-Person]
- Class Schedule: Mon – Thurs | 9:00 AM – 4:00 PM
- Location: Accra & Kumasi
Course Overview
This is a beginner-friendly course, that will teach you how to use large data sets to make critical decisions. You’ll use industry tools: Excel, SQL, Power BI, and Python programming to analyze large real-world data sets and create dashboards to share your findings.
What Does a Data Analyst Do?
A data analyst collects, cleans, and interprets data to help organizations make informed decisions. By identifying trends and patterns, data analysts provide insights that guide business strategies and improve performance.
Who Is This Program For?
This program is ideal for individuals who:
- Are interested in starting a career in data analytics or data science
- Enjoy problem-solving and working with data
- Want to gain practical, job-ready digital skills
- Have little or no prior experience in data analysis
What You Need to Participate
To participate successfully in the programme, applicants should have:
- 1. A good working laptop (8gb RAM or above, 1TB HDD or 256 SSD)
- 2. A stable internet connection
- 3. A serene environment for virtual sessions
- 4. Ability to pursue the program on a full-time basis
- 5. Prior expression of leadership potential
Skills You Will Learn
Technical Skills
- Data analysis and interpretation
- Statistical analysis
- Data visualization
- SQL and database management
- Python programming
- Dashboard creation (Power BI)
Professional & Mindset Skills
- Communication
- Time management
- Critical thinking
- Team collaboration
- Problem-solving
- Adaptability and growth mindset
What jobs can I do after completing the programme?
Job opportunities you can apply for at the end of the training includes:
- 1. Data Analyst
- 2. Financial Analyst
- 3. Business Analyst
- 4. Health Analyst
- 5. Database Administrator
- 6. Data Engineer
- 7. Market Research Analyst, etc.
Testimonials
Our Three Pillars
Peer-to-Peer Learning
You will be placed in small groups to work together as a team and complete academic goals in real-time virtual classrooms and during in-person sessions; which has goals at the individual and group level.
Mentor-Based Learning
A mentor will be available at all times during office hours to provide help and evaluate your work. We offer you a supportive and engaging work environment, where you can feel free to make mistakes and learn.
Projects-Based Learning
Our learning methodology focuses 100% on the needs of today’s market. You will work on real-world projects similar to those you’ll find on the job and complete them using the same tools used by professionals.
Our Admission Process
Submit your application. Share a bit about yourself and what's driving you to start a career in data science.
Complete a short critical thinking and problem-solving assessment. This allows us to assess your aptitude for data.
Speak with an Admissions representative in a non-technical interview. This is an opportunity for us to get to know each other a little better. Nothing technical - just a friendly conversation.
Receive your acceptance decision from Admissions. This usually happens within 3 business days.
If accepted, you'll begin course pre-work to prepare for the first day of class. Our data courses pre-work consists of 20-40 hours of lessons and labs covering the basics of Python (including loops and functions), statistical measures such as central tendency and dispersion, and building data visualizations using matplotlib and seaborn
** Steps 2 and 3 apply only to applicants seeking a Scholarship-Supported Fellowship. Applicants enrolling in the paid fellowship are not required to complete these steps.
