Data Science

Data science course

Course Summary

The Data Science Program at Ruqtec is a focused 6-month curriculum designed to equip you with the knowledge and skills needed to excel in data science. Covering data manipulation, analysis, and visualization, as well as machine learning and SQL, this program is ideal for those passionate about leveraging data for insights and decision-making. Participants will master Python and SQL for data manipulation, explore diverse datasets, and build predictive models. By course end, they'll be adept at data analysis, visualization, and machine learning, primed for data science roles in various industries, contributing to data-driven innovation.

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Price

₦333,000 40% off

₦200,000

Payment Mode

  • One Time Payment
  • Installment Payment

Duration

6 months

Next Cohort

Starts by August 13th, 2026

Requirement & Prerequisite

  • No coding experience required
  • Laptop (minimum of 4GB RAM)
  • Access to internet

Classes Delivery Mode

Live, instructor-led classes online (Google Meet/Zoom) — not pre-recorded videos. 2-3 sessions per week, 2 hours per session, with recordings and class resources shared after each one.

What You'll Cover in Live Classes

Data Science Fundamentals and Basic Python

Introduction to Python; Operators in Python and Control Flow; Lists and Loops in Python; Python Functions; Setting up a Python virtual environment; Dictionaries in Python; Working with Files in Python.

Object Oriented Programming

Fundamentals of Object Oriented Programming; Classes in Python; Methods and attributes of a Python class; Methods with arguments; Class constructor; Instance and class variables in OOP.

Relational Database Management System

Introduction to Database for Data Science; Understanding Relational Database Management Systems; Data Manipulation using SQL; Intermediate SQL; Python with Database; Aggregates in SQLite.

The Data Analysis Process

Programming workflow for Data Analysis; Use cases; Exploratory Data Analysis (EDA); Using Pandas and Seaborn for EDA.

Data Manipulation & Visualization in Python

Data Cleaning in Python; Python Lambda Functions; Basic statistics in Python; Introduction to Pandas & Numpy; Introduction to Data Visualization; Data Visualization with Matplotlib & Seaborn; Version Control & Exploratory Data Analysis.

Introduction to Machine Learning

Types of machine learning: supervised, unsupervised & reinforcement learning; Applications of machine learning; Machine learning use cases; Machine learning models & algorithms.

Capstone Project, Portfolio Building and Deployment

Final Project using AI tools to accelerate exploratory data analysis and scripting (not to replace understanding of the models); Portfolio Building; LinkedIn and CV Optimization; Deployment Strategies and Best Practices; Course Conclusion and Graduation.

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