Currently Empty: $0.00
AIAL
Applied Data Science & Analytics
Course Code: ADS-201
Duration: 18 Months (4 Semesters)
Mode of Delivery: In-Class / Online (Blended)
Training Approach: Highly practical, software-based, project and internship focussed
Course Goal
To equip learners with hands-on skills in data collection, processing, analysis, visualization, predictive modelling and interpretation—so they can meaningfully support data-driven decision-making in organisations, businesses and community settings in Somalia and East Africa.
Course Objectives
By the end of this program, learners will be able to:
- Understand data lifecycle (acquisition, cleaning, processing) and apply core statistical methods in a digital environment.
- Use key software/tools (Python/R, SQL, Excel, Power BI/Tableau) to perform data wrangling, analysis and visualization.
- Build and interpret predictive and classification models (machine learning) for real-world organisational problems.
- Communicate data insights effectively to non-technical stakeholders through visualizations and dashboards.
- Integrate ethical, governance and domain-specific considerations (e.g., business, health, NGO) into analytics practice.
- Design and complete a capstone project that demonstrates full end-to-end data science workflow in a live or simulated business/organisation context.
Delivery Methods
- Interactive lectures (core concepts)
- Practical software labs (hands-on)
- Case studies & real-world simulations (local & global)
- Group work & project-based assignments
- Internship/field placement and capstone project
Required Tools & Resources
- Computer/Laptop with internet access
- Programming software: Python (e.g., Jupyter notebooks) or R
- Database tools: SQL (MySQL, PostgreSQL or similar)
- Data visualization/dashboard tools: Power BI, Tableau or similar
- Microsoft Excel / Advanced Excel
- Sample datasets and case-studies aligned with Somali and East African context
- Access to cloud/Git (optional) for project work
Evaluation & Grading
Component | Weight (%) |
Continuous Assessments (Assignments, Lab Work, Class Participation) | 20% |
Mid-Semester Exams (Theory + Practical) | 20% |
Practical Projects & Presentations | 20% |
Final Exam (Comprehensive) | 30% |
Capstone Project (End-to-End Analytics Workflow) | 10% |
Total | 100% |
Program Summary
Semester | Credit Hours | Contact Hours |
Semester 1 | 10 | 150 |
Semester 2 | 11 | 165 |
Semester 3 | 11 | 165 |
Semester 4 | 11 | 165 |
Grand Total | 43 Credit Hours | 645 Contact Hours |
Certification
Upon successful completion of this program, graduates will receive the diploma:
Diploma in Applied Data Science & Analytics — awarded by the African Institute of Advanced Learning (AIL). Graduates will be prepared for roles such as Data Analyst, Junior



Code: ADS-201-S1
Semester 1: Foundations of Data Science & Tools
Code: ADS-201-S2
Semester 2: Data Wrangling, Visualization & Business Analytics
Code: ADS-201-S3
Semester 3: Predictive Modelling & Machine Learning
Code: ADS-201-S4
