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Jooi Centre - Kikuyu Town

Data Analysis

Fast-track your Data Analysis career with hands-on projects, real-world data, and in-demand skills. Learn to collect, clean, analyze, and visualize data to uncover insights and drive data-driven decisions.

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Program Highlights

Key details at a glance — here’s what you can expect from our Software Engineering course.

Learning Format:

Hybrid: Online and Physical classes

Next Intake:

Intake Ongoing

Duration:

4 Months

About the Course

This immersive program introduces you to the world of professional Data Analysis — from collecting and cleaning raw data to creating compelling visualizations and reports. You’ll learn essential tools like SQL, Python, and modern visualization software. By the end, you’ll be able to transform complex data sets into clear, actionable insights and build a portfolio of impactful projects.

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Sneak Peek of the Course

Course Details

This course is a practical, career-focused path into the world of data. You’ll work through structured modules that combine theory with applied labs and projects, producing a portfolio of analyses that demonstrate your ability to turn raw data into actionable insights.

What is Data Analysis? ▼

Data Analysis is the process of inspecting, cleaning, transforming, and modeling data to discover useful information, inform conclusions, and support decision-making. In this course, you'll learn how to ask the right questions, prepare data for analysis, and communicate your findings to a variety of audiences.

Who is this course for? ▼
  1. Students: Build a strong foundation in data literacy and analytical thinking.
  2. Aspiring Analysts: Transition into a data-focused role with a professional portfolio.
  3. Business Professionals: Upskill to make data-driven decisions and improve business outcomes.
  4. Curious Minds: Anyone who wants to understand how to interpret and use data effectively.
What are the course prerequisites? ▼
  1. Basic Computer Literacy: Comfortable using a computer and navigating the web.
  2. Access to a Computer & Internet: A modern browser and stable internet connection for labs.

We welcome beginners — the course starts with fundamentals and scales up to professional practice.

Why learn this course? ▼
  1. Practical Analytical Skills: Master tools like SQL, Python, and Tableau used by industry professionals.
  2. Build a Professional Portfolio: Create projects you can showcase to employers.
  3. Make Data-Driven Decisions: Learn to translate data into actionable business intelligence.
  4. High-Demand Career: Prepare for a versatile, in-demand role across all industries.
  5. Problem-Solving: Strengthen your ability to identify patterns and solve complex problems.
Why study at Lio College? ▼
  1. Hands-On Projects: A majority of the course is practical labs and collaborative analyses.
  2. Industry-Experienced Instructors: Learn from data professionals and analysts.
  3. Career Support: Guidance on building a portfolio, preparing CVs, and interview practice.
What is the mode of study? ▼

Choose between in-person on campus or online attendance. Classes are live and interactive, supported by an online learning platform with data labs, resources, and mentor support to reinforce learning.

Curriculum Overview

Our curriculum is structured into three progressive phases, ensuring you build strong data foundations before moving to advanced analysis and data storytelling. Each phase blends theory with projects to prepare you for real-world data roles.

Phase 1 – Data Fundamentals & Tools ▼
  1. Core Concepts: Learn the basics of data types, structures, and statistical thinking.
  2. Spreadsheet Mastery: Use Excel/Google Sheets for data cleaning, analysis, and visualization.
  3. Database Essentials: Master SQL for querying, manipulating, and managing data in relational databases.
  4. Data Pipelines: Understand how to gather and process data from various sources.
Phase 2 – Advanced Analysis & Python ▼
  1. Programming for Data: Learn Python fundamentals and libraries like Pandas and NumPy for data manipulation.
  2. Statistical Analysis: Apply statistical methods to analyze data and uncover insights.
  3. Data Cleaning & Wrangling: Develop skills to handle messy, real-world data sets.
  4. Introduction to Machine Learning: Understand the basics of predictive modeling and algorithms.
Phase 3 – Data Storytelling & Portfolio Project ▼
  1. Data Visualization: Create impactful charts, dashboards, and reports using tools like Tableau or Power BI.
  2. Communication & Storytelling: Learn to present your findings clearly to technical and non-technical audiences.
  3. Capstone Project: Deliver a complete data analysis project from start to finish for your portfolio.
  4. Career Preparation: Receive guidance on your job search, interviews, and professional network.

Career Pathways


Completing this course opens doors to high-demand roles across a variety of industries. Select a pathway below to explore how you can apply your skills.

Data Analyst

Collect, clean, and analyze data to solve business problems and provide actionable insights for decision-makers across various industries.

Business Intelligence (BI) Analyst

Focus on using data to improve business processes and operational efficiency by creating interactive reports and dashboards.

Marketing Analyst

Analyze market trends and customer behavior data to help companies make informed decisions about product offerings and marketing campaigns.

Financial Analyst

Use financial data to evaluate a company’s performance, assess risks, and guide investment decisions.

Ready to Launch Your Career in Data Analysis?

Join the next intake and gain practical, in-demand skills that will make you a key player in any data-driven organization.

Apply Now