Introduction to Data Science

A beginner-friendly course designed for university students/graduates, and working professionals curious about Data Science. You will learn skills in Python and Google Colab from scratch, building a foundation to join our Data Science Bootcamp. No prior programming experience is required.

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2026 Intakes in Progress

Full-time Remote

Start Date:
April 6th, 2026
Course Duration:
6 Weeks
Mode of Learning:
100% Online Classes | Mon - Fri 8 am - 5 pm E.A.T
Tuition Fee:
Ksh 55,000
Brochure:

Part-time Remote

Start Date:
April 6th, 2026
Course Duration:
9 Weeks
Mode of Learning:
Part Time & Online Classes | Mon - Fri 6 pm - 9 pm E.A.T
Tuition Fee:
Ksh 60,000
Brochure:

A Beginner-Friendly Launchpad to Data Science

From tech to business, healthcare to government, data is driving smarter decisions everywhere. This beginner-friendly course offers a hands-on introduction to the essential tools and concepts of data science. You’ll learn to use Google Colab and beginner-friendly Python libraries, such as pandas, matplotlib, and seaborn, to analyze and visualize real-world data.

By the end of the course, you’ll be able to perform basic statistical analysis, build visualisations, and confidently draw data-driven conclusions — all with no prior coding experience required. This course is the ideal starting point for anyone interested in joining the Data Science Bootcamp. Start here, build your confidence, and take the first step toward a data career.

Start here | Build Confidence | Your career in Data Awaits

Course Details

Data Science is the process of using data to make smart decisions. It combines skills from math, statistics, and computer science to collect, clean, analyse, and interpret data into valuable insights. In simple terms, data scientists find patterns in data to answer questions for professionals in sales/marketing/health/traffic/customer-care, supermarkets etc

This course is designed for complete beginners with no prior programming or math experience. If you have computer literacy skills, this is for you.

You don’t need to be a math genius or a coding expert to get started. With a technical mentor’s guidance, anyone can learn the basics of data science.

  1. Have basic computer literacy skills.
  2. Proficiency in English – both spoken and written.
  3. Must have a computer or laptop with the following specs (Core i5 – i7, 8GB RAM, 500GB memory).
  4. Must have a desire and curiosity to learn.

No prior experience in programming, math, or statistics is required.

You’ll build practical, hands-on skills to kickstart your data journey — no experience needed.

  • Understand what data science is and the roles in the field
  • Learn to write simple Python code to explore and clean data
  • Use tools like pandas, matplotlib, and seaborn to analyse and visualise data
  • Write basic SQL queries in databases
  • Practice through weekly quizzes and lab exercises after each module
  • Apply everything in a final capstone project, where you’ll solve a real problem using data

We guarantee you will learn market-aligned skills through our practical and comprehensive curriculum.

  1. Project-based learning with access to large data sets & real-world business case studies
  2. Technical Mentor Support
  3. Instructor-led lectures
  4. A certificate of completion from Moringa
  5. Dedicated support to join the Data Science Bootcamp after completion.

Learn Data Science From Scratch

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Curriculum Overview

Objective: Understand what data science is, what data scientists do, and get comfortable using Google Colab to run basic Python commands.

  • What is Data Science? Overview & lifecycle 
  • Roles in DS (Analyst vs Scientist) & Tools Overview
  • Python Syntax: Variables, print(), data types (int, str, float, bool)
  • Introduction to datasets 
  • More explorations

Objective: Learn basic programming logic and control structures in Python.

  • Lists and indexing
  • Loops (for, While )
  • Conditional logic (if, elif, else)
  • Functions: defining, calling, parameters
  • Error messages + debugging basics

Objective: Learn how to read, clean, and manipulate datasets using pandas.

  • Review: Loading CSVs & viewing (.head(), .columns)
  • Cleaning data: removing nulls, renaming columns
  • Selecting rows/columns: df[‘col’], df.query(), df[ condition ]
  • Changing data types (astype) and formatting strings
  • Exporting clean data to CSV

Objective: Learn to describe and visualise data using Python.

  • Central tendency: Mean, Median, Mode
  • Spread: Standard deviation, variance, range
  • Outliers and skew
  • Introduction to matplotlib and seaborn
  • Chart storytelling: titles, axes, labels

Objective: Use SQL to explore tabular data with simple queries.

  • What is a database? Tables, records, columns
  • SELECT, FROM, WHERE
  • Sorting and limiting: ORDER BY, LIMIT
  • Logical filters: AND, OR, IN, LIKE
  • Practice query scenarios

 

  • Project Brief + Dataset Selection
  • Data Exploration + Cleaning
  • Data Analysis: Stats + Visualisations
  • Final Presentation

Curious about Data Science?

This course is designed for complete beginners.

Career Opportunities

Are you ready to jumpstart your journey in Data Science?