Beginners & Enthusiasts

Data Analysis
Cohort

Become a Data Analyst in just 12 weeks. Learn to collect, clean, analyze, and visualize data to uncover insights and drive decision-making. You’ll work on real-world datasets, gain hands-on experience with analytical workflows, and graduate with a professional portfolio showcasing dashboards, reports, and actionable insights — ready for the job market.

Data

Data Analysts

5.0

Start your Data Analysis
Bootcamp Journey TODAY!

What the brochure show

About the Data Analysis Program
The modules for the mastery
Jekacode's distinguishing project

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💳 Flexible Payment Options

Choose the plan that works for you — pay in Full, Half, or split into 3 Easy Installments.

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Price

₦200,000

Course Overview

Here’s What You’ll Master

Module 1: Data Literacy
  • Understanding what data is and why data literacy matters
  • Key components of data literacy (reading, working with, analysing, and communicating data)
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    Module 2: Excel Fundamentals
  • Introduction to Excel interface and basic functions
  • Data entry, formatting, and organization
  • Basic formulas and functions (SUM, AVERAGE, COUNT, etc.)
  • Basic charts and visualizations
  • Introduction to conditional formatting and pivot tables
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    Module 3: Data Cleaning in Excel
  • Removing duplicates and blanks
  • Handling missing values
  • Text-to-columns and trimming spaces
  • Standardizing data formats (dates, text case, etc.)
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    Module 4: SQL for data retrieval and analysis
  • Introduction to databases and SQL syntax
  • SELECT statements and basic queries
  • Filtering results with WHERE clause
  • Sorting and limiting results
  • Using aggregate functions (COUNT, SUM, AVG, MIN, MAX)
  • Introduction to JOINs
  • Introduction to Subqueries and nested SELECT statements
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    Module 5: Power BI
  • Introduction to Power BI and its components
  • Importing and connecting to data sources
  • Data cleaning with Power Query editor
  • Introduction to Data modelling concepts
  • Creating calculated columns and measures with DAX
  • Designing interactive reports and dashboards
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    Module 6: Dashboard creations in Power BI and Excel
    • Principles of effective data visualization
    • Choosing the right chart types for different data
    • Building dynamic dashboards in Excel
    • Creating interactive dashboards in Power BI
    • Designing layouts for readability
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    Module 7: Descriptive Statistics and data distributions
  • Introduction to descriptive statistics
  • Measures of central tendency: mean, median, mode
  • Measures of dispersion: range, variance, standard deviation
  • Data distribution types (normal, skewed, uniform, etc.)
  • Using charts to visualize data distributions
  • Interpreting descriptive statistics in context
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    Module 8: Hypothesis Testing
  • Introduction to hypothesis testing concepts
  • Null hypothesis vs. alternative hypothesis
  • Types of errors (Type I & Type II)
  • Common statistical tests
  • Real-world applications of hypothesis testing
    • Module 9: Data Storytelling and Exploratory Data Analysis
  • Importance of storytelling in data analysis
  • Choosing the right visuals to communicate insights
  • Basics of exploratory data analysis (EDA)
  • Identifying patterns, trends, and outliers
  • Combining visuals and narratives for stakeholders presentations
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    Module 10: AI in Data Analysis
  • Overview of AI in analysis
  • Using AI-powered tools in Power BI
  • Introduction to AI for predictive analytics

    • E JEKA CODE

    After Completion, You Will Be Able To:

    Identify trends, patterns, and anomalies
    Using Excel, SQL, and Python (Pandas, NumPy) to process raw data
    Create insightful dashboards and reports with Power BI and Tableau
    Apply descriptive and inferential statistics for decision-making
    Work on real-world datasets and case studies from multiple industries
    CV building, portfolio creation, and interview readiness
    Access to experienced analysts and a supportive data community
    Apply now!
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