Data Engineering - 2025
This program is a structured learning journey designed for both beginners and professionals looking to deepen their expertise in Data Engineering. With a focus on hands-on experience, participants will engage in live classes, practical case studies, and projects to develop key skills in Python, SQL, data pipeline automation, and cloud engineering technologies such as Azure and GCP. The course aims to bridge the gap between theoretical knowledge and real-world applications, empowering learners to transition smoothly into Data Engineering roles.
2 Course instructors
Instructor led course
8 month duration
2 Month Internship
Course Duration
6 Months of Instructor-led classes with an option of 2 Months Internship
Projects
8 Projects
(20% Discount ongoing - Limited slots)
Program fee payment can be in instalments
Course Description
This cutting-edge Data Engineering programme is designed to provide learners with the essential skills needed to excel in the rapidly growing field of data engineering. Whether you're a beginner with no prior experience or an experienced data scientist/analyst looking to pivot into data engineering, this course offers a comprehensive curriculum that equips you with both foundational knowledge and advanced technical expertise.
Over the course of six months, you will master industry-leading tools and technologies such as Python, SQL, Apache PySpark, and cloud platforms like Azure and Google Cloud (GCP). The programme emphasizes practical, hands-on learning through live classes, interactive workshops, and real-world case studies. You'll learn to build and automate robust data pipelines, efficiently manage and store vast amounts of data, and leverage cloud computing to solve complex engineering problems.
By the end of the programme, you will have completed 8 industry-relevant projects, adding a significant body of work to your portfolio. You will also gain access to a two-month internship, personalized career coaching, and job preparation support, ensuring you're fully prepared to land high-demand roles in data engineering and cloud computing.
This programme isn’t just about learning — it’s about making you job-ready and giving you the confidence to thrive in a competitive job market.
Course Curriculum
Week 0
Week 0 - Introduction
The Week 0 - Introduction is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Installation Videos
How to download and Install VS Code
How to download and Install Draw.io
How to download and Install Anaconda
How To Download And Install PostgreSQL
How To Download And Install VS Code
How to download and Install GitHub
Module 2: Introduction to Data Engineering
About Facilitators with Learning Structure and Roadmap
Engineering Roles Explained with Tech Stack
Real-life application of How Data Engineering works
Module 3: Understanding Data Engineering
What is Data
What is Big Data
5v's of Big Data (Twitter or X)
What is Data Engineering
Data Engineering Concepts
Data Storage and Management
Database vs Data Warehouse vs Data Lake vs Data Mart
OLTP vs OLAP
SQL vs NoSQL
ACID or BASE
Data Formats
Data Ingestion
ETL vs ELT vs ELTL
Data Pipeline Design and Orchestration
Cloud Computing
Types of Cloud Computing
Module 4: Portfolio Creation
Portfolio Checklist
Experiencing VScode
Editing the HTML Template
Uploading your portfolio on GitHub Pages
Module 5: Optimize your LinkedIn Profile
Introduction
Creating your LinkedIn Profile
Uploading your Profile Picture and Cover
Crafting your headline
Your About Section
Work Experience
Education
Skills - Endorsements - Recommendations
Always Refer to your LinkedIn Pack
LinkedIn X JobAlytics
UK Visa Sponsorship LinkedIn Extension
Modifying LinkedIn Settings
Week 1
Python Data Types/Structures
The Python Data Types/Structures is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Python Data Types/Structures
Getting Started in Python
Integer and Float
Variable Assignment
String
Print Formatting
List
Dictionary
Tuples
Set
Boolean
Bring all Data Types Together
Module 2: Writing Clean codes with PEP8 guidelines
Introduction to clean coding - managing imports
Managing Indentation
Utilizing Comments
Documenting with Docstrings
Utilizing blank lines and managing line length
Adhering to naming convention and managing white spaces
Week 3
Comparison Operators, Loops and Functions
The Comparison Operators, Loops and Functions is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Comparison Operators, Loops and Functions
If, Elif, Else Statement
And / Or Statement
If, Elif, Else (And / Or)
For Loop
While Loop
Break, Continue and Pass
For Loop (Extra Example)
While Loop (Extra Example)
Function
Function (Extra Examples)
Filter, Map, and Lambda Function
Module 2: Debugging/Using the debugger to properly troubleshoot
Introduction to Data Engineering and Common Challenges
Types of Errors in Data Engineering - Syntax Error
Types of Errors in Data Engineering - Logical Error
Types of Errors in Data Engineering - Runtime Error
Types of Errors in Data Engineering - Data Related Error
Debugging Techniques - understanding Error Messages
Week 5
SQL (Structured Query Language)
The SQL (Structured Query Language) is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: SQL Fundamentals
SQL Introduction
Premier Case Study
Entity Relationship Diagram
Primary vs Foreign Key & Fact vs Dimension Tables
SQl Commands
Module 2: MetroBank SQL Case Study
Metrobank Case Study
Metrobank Case Study
Create Statement
Alter Statement
Insert / Update / Delete / Truncate Statement
Data Upload and Select Statement
Module 3: Bonga Ecommerce SQL Case Study
Overview of Bonga ecommerce sql case study
Installing PostgresSQL (PGadmin)
Using Data Definition Languages ]
Data Manipulation Languages
Data querying Languages- Part 1
Data querying languages- Part 2
Data Querying Languages (DQL)- Part 3
Week 8
Data Modelling, Github and Database with Python
The Data Modelling, Github and Database with Python is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Database and Data Warehouse
Introduction to data modelling
Normalization
Using Lucid charts to draw ER Diagrams
Star Schema
Snowflake Schema
Case Study Introduction- Database Modelling
Case Study- Data Warehouse Modelling
Module 2: Introduction to GitHub with a Case Study
Introduction- Git and Github Overview
Overview of Github Deskstop
Week 9
SQL, Python, Pandas, and GitHub
The SQL, Python, Pandas, and GitHub is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Working with Numpy
Introduction to Numpy
Accessing Numpy Arrays
Modifying Numpy Array
Functions on Numpy Arrays
Module 2: Working with Pandas
Introduction to Pandas
Creating Pandas Series & Dataframes
Basic Pandas Operations- Projecting & Filtering
Joins- Inner, left, Right, Outer
Advanced Dataframe Operations
Slicing & Indexing using Pandas
Module 3: SQL, Python and Pandas - (GitHub)
Case study Overview - Yanki Ecommerce
Github Setup-Reading csv data to Pandas Dataframe
Building the data model
Data Cleaning, Creating the Normalised table and writing to CSV file
Loading data into PostgreSQL server
Week 10
Accessing Database with Python, Intermediate SQL, and GitHub
The Accessing Database with Python, Intermediate SQL, and GitHub is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Accessing Databases with Python
Introduction and Overview of the case study
Explanation of serverless vs server-based
Creating a serverless database file
Data Definition Languages (DDL)
Data Manipulation Language (DML)
Data Querying Languages (DQL)- Part 1(Basics, Like operator, Between)
Data Querying Languages (DQL)- Part 2(Group BY, Order BY, Having)
Data Querying Languages (DQL)- Part 3(Joins, Unions, Concatenation)
Using PostgresSQL Server on PgAdmin to Create tables and run queries
Module 2: Intermediate SQL - Case Study
Introduction- Windows Function
Joins (Inner, Left, Right, Outer)
Case, Rank Functions- Case Study Overview
Case Study- Windows Functions
Case Study- Rank Functions
Case Study- Case Function
Case Study- Joins
Module 3: GitHub and Data Modelling Case Study
Case study Overview- Introduction
Database Modelling- Normalization- Denormalise
Database Modelling- Normalization- 1NF to 2NF
Database Modelling- Normalization- 2NF to 3NF
Transaction DWH Schema
Loan DWH Model
Loading data into PostgreSQL DB- Creating Schemas and Tables
Loading Data into PostgreSQL DB - Loading data into Tables
Week 13
Working with API and Web Scraping (Static Website)
The Working with API and Web Scraping (Static Website) is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Working with API
Overview of APIs
Case study Introduction
Data Extraction from the API
Data Transformation- Cleaning the data
Data Transformation- Building the database mode
Loading to PostgreSql DB
Loading to PostgreSql DB part 2
Module 2: Web Scraping (Static Website)
Introduction to Web scraping
Tags, Attributes & workflow of a web scrapping
Case study overview
Assessing tags, attributes and navigable string
find, find_all and regular expressions
Juno ecommerce Data Extraction
Juno ecommerce Data Transfomation & Loading
Week 14
Web Scrapping (Dynamic Website)
The Web Scrapping (Dynamic Website) is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Web Scraping (Dynamic Website)
Introduction to webscraping for dynamic pages
Case study introduction
Installing Selenium and its setup
Data extraction using selenium and beautifulsoup
Data Transformation
Data loading into a PostgreSQL database
Week 16
Data Exploration & Cleaning using PySpark
The Data Exploration & Cleaning using PySpark is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Installing Pyspark
How to manually install pyspark
Module 2: Data Exploration & Cleaning using PySpark
Introduction to PySpark
PySpark Architecture and Uses
Case Study Introduction
Data Extraction and GitHub Setup
Data Cleaning with PySpark
Data Transformation with Pyspark
Data Loading into the PostgreSQL server
Week 18
End-to-End Data Engineering project (On-Premise)
The End-to-End Data Engineering project (On-Premise) is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Installing Linux
How To Install Linux (Windows OS ) PRT 1
How To Install Linux (Windows OS Only) PT2
Module 2: Batch ETL Pipeline and Task Scheduler Orchestration
Data Engineering Process flow Overview
Project Overview
Data Extraction
Data Architecture
Data Modelling
Data Cleaning and Transformation
Data Loading
Data Pipeline Orchestrating with Task Scheduler
Module 3: PySpark ETL Pipeline and Task Scheduler Orchestration
Pyspark Introduction and Case Study Overview
Data Extraction (and Spark Setup)
Data cleaning
Data architecture and data modelling
Data Transformation
Data Loading to a Postgres Database
Week 19
Apache Airflow
The Apache Airflow is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Airflow
Week 20
Cloud Engineering (AZURE)
The Cloud Engineering (AZURE) is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Cloud Engineering PRT 1
Module 2: Azure Cloud Engineering
Module 3: Azure Cloud Project
Module 4: Databrick and PySpark
Module 5: Cloud Engineering
Week 22
Cloud Engineering (AWS & GCP)
The Cloud Engineering (AWS & GCP) is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: AWS Cloud Engineering
Module 2: End-to-End Data Engineering
Module 3: GCP Cloud Engineering
Meet Your Instructor
Iyanujesu Taiwo Akinyefa
Team Lead Data Engineering
"Taiwo is a highly skilled Data Professional with over five years of robust industry experience in Data Engineering and Data Analysis. She demonstrates advanced proficiency in Python, SQL, ETL/ELT processes, data warehousing, and cloud platforms such as Azure, AWS, and GCP, with a focus on Big Data solutions. Taiwo has successfully trained and mentored students, equipping them with the skills to excel in data-driven roles. Her experience spans industries including Technology, Fintech, Fast-Moving Consumer Goods (FMCG), Telecommunications, and Entertainment, where she has consistently leveraged data to drive strategic decision-making and foster innovation. Taiwo is passionate about building scalable data solutions that optimize business operations and deliver actionable insights for growth."
Sadique Timileyin
Senior Data Associate
Senior Data Associate
Job Opportunities
With our Data Analytics Cerificate, you get to work as any of the following:
Data Engineer
Analytics Engineer
BI Engineer / Developer
AWS Cloud Engineer
Azure Cloud Engineer
GCP Cloud Engineer
ETL Developer
Big Data Engineer
Data Migration Specialist
Data Platform Engineer
Course Reviews
Select your preferred pricing plan
As an edu-tech brand, we specialize in providing the essential skills and knowledge you need to unlock high-paying opportunities in the dynamic world of technology. Our mission is simple: to empower individuals to pursue their dreams and excel in high-demand tech roles through intensive, hands-on training.
8-Month Plan
Learners looking for extended industry exposure and advanced skill-building.
6 months of classroom learning + 2 months of internship.
Payment Plan: $150 per month for 5 months.
What You Get:
- Extended internship for in-depth practical experience.
- Access to all advanced course materials and certifications.
- Mentorship and career guidance throughout your journey.
