Not necessarily.
Basic programming experience is helpful, but it isn’t a strict requirement. We start from the fundamentals and gradually build up your skills in Python, Power BI, Excel, and data tools—even if you’ve never coded before. What matters most is your commitment to learning.

By the time you complete the program, you’ll confidently write production-level code for data pipelines, automation scripts, and analytics workflows.

Hybrid & Virtual Combined

Yes – Data Analysts are in high demand globally. Companies rely on data-driven decisions, dashboards, and insights to improve performance and guide strategy.

What Careers Can I Pursue?
You can qualify for roles such as:

• Data Analyst
• Business Analyst
• Reporting Analyst
• BI Analyst
• Operations/Strategy Analyst
• Product Analyst
• Marketing Analyst

Do You Help With Job Placement?
Yes – we provide full support, including:

• Interview prep and mock interviews
• Portfolio/GitHub dashboard projects
• CV and LinkedIn optimization
• Job alerts and application guidance
• Real industry analytics capstone projects

1. Problem Definition
Identifying business questions and determining what data, metrics, and analyses are needed to provide actionable insights.

2. Data Collection & Preparation
Gathering data from various sources, cleaning it, handling missing values, and preparing datasets for analysis.

3. Exploratory Data Analysis (EDA)
Examining patterns, trends, and relationships in the data using statistical methods and visualization tools.

4. Data Visualization & Reporting
Creating dashboards, reports, and visual stories using tools like Power BI, Excel, or Tableau to help teams understand insights quickly.

5. Business Insights & Decision Support
Turning analytical findings into clear recommendations that guide business strategy, operations, and performance improvement.

6. Performance Tracking & KPI Analysis
Building and maintaining KPIs, tracking business performance, and monitoring the impact of decisions over time.

7. Data Quality & Documentation
Ensuring accuracy, consistency, and reliability of data while maintaining clear documentation for future analysis.

8. Collaboration with Teams
Working with managers, product teams, marketing, finance, and engineers to deliver insights that support goals across the organization.

Banking:
A Data Analyst identifies unusual transaction patterns and builds dashboards that help detect potential fraud or risky customer behavior.

Healthcare:
A Data Analyst examines patient data, hospital records, or treatment outcomes to support better diagnosis, planning, and resource allocation.

Retail & E-commerce:
A Data Analyst studies customer behavior, sales trends, and product performance to improve recommendations, pricing, and marketing strategies.

By the end of the program, you’ll be able to collect, analyze, and interpret data to deliver actionable business insights. You will gain skills in:

1. Programming & Scripting

• Python for data analysis and workflows

• Writing clean, reusable code

• Automating tasks using scripts and APIs

2. Data Cleaning & Preparation

• Handling missing or inconsistent data

• Transforming raw data into analysis-ready datasets

• Preparing datasets for visualization and reporting

3. Exploratory Data Analysis (EDA)

• Identifying patterns, trends, and outliers

• Statistical analysis and correlation insights

• Using Python libraries like Pandas, NumPy, and Matplotlib

4. Data Visualization & Reporting

• Building dashboards with Power BI, Tableau, or Excel

• Visual storytelling and presenting insights to stakeholders

5. Business Insights & KPI Analysis

• Translating data into actionable business recommendations

• Defining and tracking KPIs for business performance

6. Real-World Analytics Projects

• End-to-end projects using real datasets

• Building reports and dashboards that simulate industry scenarios

• Documenting findings and presenting insights professionally

7. Collaboration & Communication

• Working with business teams, product managers, and engineers

• Communicating insights effectively for decision-making

Yes. You’ll receive a recognized and verifiable certificate of completion that can be shared with employers, added to LinkedIn, or used in startup pitches.

1. Data is the foundation of every data-driven business
Successful businesses rely on accurate, clean, and organized data. With Data Analytics skills, you’ll know how to:

• Collect and clean data

• Prepare datasets for analysis

• Ensure data quality and reliability

• Organize and document insights for decision-making

2. You can build analytics-powered products
With strong Data Analytics skills, you can develop:

• Dashboards and reporting tools

• Customer insights and recommendation systems

• Predictive analytics for business forecasting

• Industry-specific analytics solutions

3. You can offer freelance or consulting services
Companies often need help with:

• Building dashboards and reports

• Automating analysis workflows

• Interpreting data to support business decisions

• Analytics strategy and consulting

4. You can provide end-to-end analytics solutions
Combining data preparation, visualization, and insight generation allows you to deliver complete analytics solutions, making your business highly valuable to clients.

5. You will develop problem-solving and product-building skills
During the course, you’ll work on:

• Real-world analytics projects

• End-to-end reporting and dashboards

• Data-driven insights for practical business applications
  These skills are essential for launching a data-focused startup or consultancy.

• Hands-on learning: Work with real-world datasets, analysis workflows, and projects.

• African context: Learn from case studies of local data-driven success stories like M-KOPA, Flutterwave, Branch, Twiga Foods, Kobo360, and Apollo Agriculture.

• Expert mentorship: Guidance from experienced Data Analysts and tech startup founders who have built scalable analytics systems in Africa.