Data Analyst Internship

Data Analyst or Analytics internship involves in-depth training in 4 essential tools: SQL, Power BI, Python and Advanced Excel (same as Data Science to give all-around experience to our trainees). Each tool plays a pivotal role in the realm of data and business intelligence. Your training will take place at our esteemed data school, renowned for producing exceptional data professionals both in Nigeria and internationally. This program is designed to take you from a foundational understanding to becoming an advanced user of SQL, Power BI, Python and Advanced Excel.

This program is ONLY available in Abuja for now and Uses a HYBRID MODE OF LEARNING (A Mix of Online and in-class sessions).

What you will Gain from the Data Analyst Internship

  • ● Supportive and innovative teaching environment
  • ● Extra support session weekly
  • ● World-class data analytics books and resources in our Office
  • ● Practical teaching from resourceful and internationally trained instructors
  • ● Certification and Solid Project Portfolio
  • ● Employability skills
  • ● Job coaching and vacancies newsletter for job seekers
  • ● Course content that aligns with the data analytics industry internationally.

Technology Tools in this Internship

  • ● Advanced Excel
  • ● Microsoft Power BI
  • ● SQL, Python and Machine Learning

Course Outlines

Basic to Advanced Excel

This Excel fundamental to advanced course will equip you with the skills needed for data analysis and decision-making in various real-office scenarios. You will master using Excel for various use cases.

Module 1: Excel Fundamentals

  • Introduction to Excel
    • Understanding the Excel interface and basic navigation.
    • Entering and formatting data.
    • Basic calculations using Excel formulas.
  • Working with Functions
    • Exploring common Excel functions (SUM, AVERAGE, COUNT, etc.).
    • Using functions for basic data analysis.
    • Absolute and relative cell references.
  • Data Management and Visualization
    • Sorting and filtering data.
    • Creating basic charts (bar, line, pie).
    • Data validation and conditional formatting.
  • Advanced Formatting and Efficiency
    • Advanced formatting techniques.
    • Introduction to PivotTables.
    • Tips and tricks for working efficiently in Excel.

Module 2: Intermediate Excel Techniques

  • Advanced Functions
    • Using logical functions (IF, AND, OR).
    • Lookup functions (VLOOKUP, HLOOKUP, INDEX-MATCH).
    • Text functions for data manipulation.
  • Data Analysis Tools
    • Introduction to Excel’s What-If analysis tools.
    • Goal Seek and Scenario Manager.
    • Data Tables and Solver.
  • PivotTables and PivotCharts
    • In-depth PivotTable creation and customization.
    • PivotCharts for visual data analysis.
    • Slicers and Timelines.
  • Data Automation
    • Introduction to Macros and VBA (Visual Basic for Applications).
    • Recording and running macros.
    • Creating simple automation scripts.

Module 3: Advanced Excel Techniques

  • Advanced Data Analysis
    • Array formulas and advanced formula nesting.
    • Building complex calculations.
    • Introduction to Power Query for data transformation.
  • Data Models and Power Pivot
    • Creating data models in Excel.
    • DAX (Data Analysis Expressions) functions.
    • Combining multiple data sources.
  • Advanced Charting and Visualization
    • Advanced chart types (scatter, bubble, radar, etc.).
    • Customizing charts for meaningful insights.
    • Building interactive dashboards.
  • Excel Efficiency and Best Practices
    • Excel tips for efficiency and productivity.
    • Collaboration and data sharing in Excel.

Microsoft Power BI

Microsoft power bi training will equip you with powerful skills for visualizing data from various sources by aggregating them on a dashboard for data-driven insights. You will build a fully interactive business intelligence dashboard for real-life use cases.

Introduction to Power BI for Decision Intelligence:
– Overview of Power BI and its significance in decision-making.
– Understanding the Power BI interface and its core features.
– Exploring data visualization concepts and best practices.
Introduction to Power BI for Decision Intelligence:
– Overview of Power BI and its significance in decision-making.
– Understanding the Power BI interface and its core features.
– Exploring data visualization concepts and best practices.
Data Preprocessing and Transformation in Power BI:
– Importing data from various sources into Power BI.
– Data cleaning, formatting, and handling missing values.
– Applying data transformation techniques to optimize data for analysis.
Introduction to Relationships and Model:
– Understanding the importance of data relationships in Power BI.
– Creating and managing relationships between different data tables.
– Designing an efficient data model for enhanced analysis capabilities.
More on Data Preprocessing and Transformation:
– Advanced data shaping techniques using Power Query Editor.
– Combining and merging data from multiple sources.
– Handling complex data transformations and calculations.
Introduction to DAX, Measures, and Calculated Columns:
– Introduction to the Data Analysis Expressions (DAX) language
– Creating measures and calculated columns for data analysis.
– Applying DAX functions to perform advanced calculations and aggregations.
Creating Data-Intelligent Visualization Reports and Dashboards:
– Designing visually appealing and interactive reports.
– Implementing various types of visualizations, such as charts, tables, and maps.
– Utilizing advanced features, such as slicers, drill-through, and bookmarks.

Foundational Statistics

Understanding Statistics in Plain English
When to Use a Particular Statistical Test

Python And Application Programming

You Will Learn To Understand Decision Support Systems Using Data Insights. You Will Work Your Way Up From Learning To Code, And Application Development To Leveraging Data To Automate Decision-Making Processes Across Various Industries And Fully Understand The End-To-End Process Of It.


Introduction to Python Programming
Git and GitHub for Version Control
Data Types, Arithmetic Operations, Python Lists, and List Comprehension
Conditional Statements (If Else, Elif, For Loops and While Loops)
Python Function Basics to Advanced
Project Design
Building and Deploying your First Python Application
Working with Numpy
Working with Pandas 1 & 2
Data Quality Assessment, Cleaning, Transformation and Reduction 1 & 2
Exploratory Data Analysis (EDA)
Data Visualization
Reading Data from SQL Databases using Python
Data Science in Industries
Introduction to Machine Learning and Machine Learning Algorithms
Introduction to Deep Learning and Advances in Deep Learning
Machine Learning with Regression
Machine Learning with Classification
Time Series Modeling
Final Industry Project


SQL is the language of databases. This course will equip you with practical skills in working with a popular database. You will learn how to query databases, extract data and transform data for further analysis.

Introduction to Relational Database Management System:
– Understanding the fundamentals of relational databases.
– Exploring the components and structure of a database.
– Getting familiar with key database concepts, such as tables, columns, and relationships.
Hands-on MySQL Database:
– Setting up and configuring a MySQL database for practical exercises.
– Navigating and interacting with the MySQL command-line interface.
– Executing basic SQL queries to retrieve and manipulate data.
Creating SQL Database:
– Designing and creating a SQL database using appropriate data types and constraints.
– Defining primary keys, foreign keys, and relationships between tables.
– Ensuring data integrity and normalization principles.
Grouping and Summarizing Data with SQL:
– Using SQL’s aggregate functions (e.g., SUM, AVG, COUNT) to summarize data.
– Grouping data based on specific criteria for meaningful analysis.
– Applying filters and conditions to aggregate data effectively.
Using SQL to Select Data from More Than One Table:
– Understanding the concept of table joins in SQL.
– Utilizing different join types (e.g., INNER JOIN, LEFT JOIN, RIGHT JOIN) to combine data from multiple tables.
– Writing complex queries involving multiple tables to extract relevant information.
Using SQL Views:
– Creating and utilizing SQL views to simplify complex queries.
– Understanding the benefits and practical applications of views.
– Modifying and updating data through views.
Using SQL Sub-Queries:
– Leveraging sub-queries to perform nested and correlated queries.
– Incorporating sub-queries in various parts of a SQL statement.
– Applying sub-queries for advanced filtering and data manipulation.
Using SQL to Insert, Update, and Delete Data:
– Inserting new records into a database using SQL’s INSERT statement.
– Updating existing data using SQL’s UPDATE statement.
– Deleting unwanted data using SQL’s DELETE statement.
Using SQL Transactions:
– Understanding the concept of transactions in database operations.
– Implementing transaction control statements (BEGIN, COMMIT, ROLLBACK) to ensure data consistency and integrity.
– Handling errors and managing transactional operations effectively.


  • Wednesdays: Online class from 8 pm to 10 pm
  • Saturdays: Physical class at our office in Abuja from 10 am to 3 pm
  • Program Duration: 3 Months
  • Program Fee: N200,000 (Payable in full or in 2 equal installments).
  • Enjoy: Free High-Speed Internet, Free Space to Work in our Office and meet Professionals.
  • LOCATION: Our High Tech Training Center at Karu Site Abuja.

Note: No prior experience is required, we deliver training from the ground up.

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