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SCHOOLVILLE BOOTCAMP PROGRAM (BCP)

Data Analysis & Data Science

Course Code: BCP-DDS-101

12 Weeks Beginner / Intermediate ₦600,000

Course Description

Data analysis, visualization, and business intelligence to drive data-informed decisions.

Course Overview

Data Analysis & Data Science skills are in high demand, as organisations increasingly rely on data to guide decisions. This BootCamp provides participants with practical, hands-on skills in SQL, Python, R, and modern BI tools - delivered through Project-Based Learning (PBL) combining instructor-led training, guided labs, and industry mentorship.

Course Prerequisite

No previous data analysis experience is required.

RECOMMENDED REQUIREMENTS:

  • Basic computer literacy
  • Comfort with spreadsheets (preferred but not mandatory)
  • Logical and analytical thinking
  • Personal laptop computer
  • Reliable internet connection

Course Delivery Method

Instructor-Led

  • • Physical Classroom
  • • Virtual Live Classroom
  • • Hybrid Learning

Course Language: English Language

Course Outcomes

Upon successful completion, participants will be able to:

Clean, transform, and analyse datasets using Excel, Python, and R.

Write SQL queries to extract and join data across tables.

Apply exploratory data analysis techniques to uncover insights.

Build interactive dashboards in Tableau and Power BI.

Design meaningful KPIs and metrics for a business context.

Communicate data-driven insights clearly to stakeholders.

Build and present a professional data analysis portfolio.

Course Duration

DURATION

12 Weeks

Intensive Study

FREQUENCY

5 Days / Week

Regular Tracks

SESSION LENGTH

6 Hours / Day

Accelerated Format

TOTAL LEARNING

360 Hours

Practical & Theory

Daily Schedule Breakdown

3 Hours Guided Instructor-Led Practical Training

3 Hours Independent (Unguided) Practical Session

Course Structure

The course is delivered through three progressive learning modules. Each module builds on the last - from foundations, to applied practice, to advanced work and a capstone project.

Module 1: Foundations Module (SBM)

Duration: 2 Weeks (60 Hours)

Data Analysis Concepts

Excel for Data Analysis

Data Cleaning Techniques

Writing SQL Queries

Joins & Aggregations

Working with Real Datasets

Module 2: Core Practice Module (SIM)

Duration: 2 Weeks (60 Hours)

Data Analysis with Python (Pandas)

Statistical Analysis with R

Exploratory Data Analysis

Visualization Principles

Building Dashboards in Tableau

Building Dashboards in Power BI

Module 3: Advanced & Capstone Module (SAM)

Duration: 2 Weeks (60 Hours)

Data Storytelling Techniques

KPI & Metric Design

Presenting Insights to Stakeholders

Capstone Planning

Building the Data Capstone Project

Presentation Preparation

Total Lessons Summary

Module

Lessons

Foundations Module (SBM)

6

Core Practice Module (SIM)

6

Advanced & Capstone Module (SAM)

6

Total Lessons

18

Practical Laboratory Activities

Daily Guided Data Labs Independent Practical Exercises SQL Query Workshops Dashboard Building Labs Statistical Analysis Exercises Data Storytelling Workshops Portfolio Development

Assessments, Capstone Project & Project Presentation

Assessment is competency-based and measures technical knowledge, analytical ability, practical skills, documentation, and professional communication.

Assessment Component

Weight

Foundations Module (SBM)

10%

Core Practice Module (SIM)

20%

Advanced & Capstone Module (SAM)

30%

Capstone Project

30%

Project Presentation

10%

Total

100%

Capstone Project

Each participant or project team will complete a practical data analysis project, turning a real dataset into actionable business insight.

Capstone Planning & Proposal

Requirements & Needs Analysis

Solution Design & Architecture

Technical Implementation

Testing & Quality Assurance

Documentation & Reporting

Stakeholder Presentation

Portfolio Packaging

Peer & Mentor Review

Projects should include:

Problem identification and analysis

Solution design

Technical implementation or demonstration

Testing and validation

Recommendations

Professional documentation

Project Presentation (Demo Day)

Participants will present their completed projects before a panel comprising:

Industry Professionals Subject Matter Experts Technical Leads Academic Experts Industry Mentors Schoolville Leadership

Projects will be evaluated based on:

Technical competence Best practices Problem-solving approach Innovation Practical applicability Documentation quality Presentation skills Overall impact

Certification

Participants who successfully complete all programme requirements will receive the Schoolville BootCamp Certificate in Data Analysis & Data Science, with classifications of Pass, Credit, Merit, or Distinction based on overall performance.

Graduates will also complete the programme with a professional portfolio demonstrating practical laboratory work, applied projects, and a capstone project suitable for employment, consulting engagements, or further professional certification pathways.

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