Data Engineering Bootcamp - Learn tech skills from the top 10% tutors

Become a certified
Data Engineer in 3 months

Launch your product design career with our intensive, live online bootcamp. Gain the skills to design user-centred products from scratch.

Live Bootcamp

All Levels

3 months

20+ topics

400+ Students

Our world-class curriculum empowers you to unleash your full potential as a Data Engineer!

This curriculum is tailored for individuals aspiring to embark on careers in data engineering. The program spans three months and is structured around three core tools: SQL, Power BI, and Python, with each tool receiving dedicated focus.

Integral to the course is a capstone project, offering students an opportunity to apply acquired skills in practical scenarios and showcase their proficiency upon completion of all modules. The capstone project will occur prior to the conclusion of each cohort, providing participants with a culminating experience to demonstrate their learning outcomes.

Module 1: Data Engineering Basics

Introduction to Data

What is data, types of data and forms, Data formats (CSV, Avro, Parquet, e.t.c), Concept of Storage systems (databases)

Introduction to Data Engineering

The need for a Data engineer, The Data lifecycle (Data collection process, storage, transformation and consumption)

Data Storage and Management

Types of databases, examples of each types

Modern Data Storage systems

Data warehouses, Datalakes, Lakehouses and differences

Common data Engineering concepts

ETLs and ELTs, Data Modelling; Meaning, Normalisation and Denormalisation

Module 2: SQL

SQL Server Basics

Connecting to SQL Server using SSMS
Creating and altering a database
Creating and working with tables
Basic Select Operations
DDL and DML operations
Table constraints
Differences between Where and Having

Joins and Advanced Operations

Understanding the concept of Joins
Types of Joins and their use cases
Working with NULLs and Coalesce function
Using Unions and Union All
Exploring Stored Procedures
Triggers and their use cases

Functions and Optimization

Understanding SQL Functions
Types of Functions: Built-in and Custom Functions
Examples: LEFT, Right, Len, Upper, Lower, Date Functions
Exploring Indexes and Partitioning for Performance
Performance Testing Techniques

Advanced SQL Concepts

Working with Views, CTEs, and Subqueries
Understanding Database Normalization and Relational Databases
Types of Database Normalization
Exploring Rollup and Cube in SQL Server

Module 3: Python

Python Basics - Introduction to Python and its importance in data engineering

a. Setting up Python environment (Anaconda, Jupyter Notebook)
b. Basic syntax, variables, and data types
c. Control structures: if statements, loops

Data Structures

a. Lists, tuples, dictionaries, sets
b. List comprehensions
c. Working with data structures

Functions and Modules

a. Functions: defining, calling, arguments, return values
b. Scope and namespaces
c. Introduction to modules and libraries (e.g. pandas, NumPy)

Data Manipulation with pandas

a. Introduction to pandas library
b. Reading and writing data: CSV, Excel, SQL
c. Data exploration and manipulation: filtering, sorting, grouping

Data Cleaning and Preprocessing- Data transformation and standardization

Data Visualization - Creating basic plots: line plots, bar charts, histograms

Database Integration

a. Connecting Python with databases (e.g., SQLite, PostgreSQL)
b. Performing CRUD operations (Create, Read, Update, Delete) using Python
c. Executing SQL queries from Python

Web Scraping and API Integration

a. Introduction to web scraping using libraries like BeautifulSoup
b. Accessing APIs using Python

Introduction to Data Pipelines

a. Understanding data pipelines and ETL (Extract, Transform, Load) processes
b. Designing data engineering pipelines using Python
c. Workflow Management Tools (Azure Data Factory, Apache Airflow, Databricks,)

Module 4: PowerBI

Get Started with Microsoft Data Analytics

a. Describe the Power BI Landscape of Products and Services
b. Tour the Power BI Service

Get Data in Power BI

a. Identify and retrieve data from different data sources
b. Understand the different connection methods and their performance
c. Optimise query performance

Clean, Transform, and Load Data in Power BI

a. Apply Data Shape Transformations
b. Enhance the Data Structure
c. Profile and Examine the Data

Design a Data Model in Power BI

a. Apply Data Shape Transformations
b. Understand the basics of Data Modelling
c. Defining Tables and Granularity
d. Define Relationships and their Cardinality
e. Implement Dimensions and Hierarchies

Creating Measures using DAX in Power BI

a. Understand DAX
b. Use DAX for Simple Formulas and Expressions
c. DAX Date and Time functions
d. Create Calculated tables and columns
e. Build simple Measures

Creating Reports

a. Design a Page layout
b. Select and add Appropriate Visualization type
c. Work with charts and tables on the report.

Module 5: Projects and Demo Prep

We hold 100% virtual live classes enabling you to learn from wherever alongside other budding techies, After your program, you’ll get the chance to showcase your work to industry experts and potential employers on our demo day.

This program is not for you if:

You are looking to bag jobs quickly without putting in the work

You can’t commit 6-8 hours a week for sessions and assignments

You don’t want to grow alongside a community of hustlers

You’re seeking theoretical learning and do not want to build a portfolio

You're searching for shortcuts rather than mastering core skills

You don't want to invest in your personal development

This program is tailor made for:

Individuals who love asking questions and uncovering insights from data.

People who understand that learning require putting in the work

Beginner data engineers who want to accelerate their growth

You love to put your lerning into practice and get hands-on

People from other career path trying to transition to Data engineering.

Newbies trying to get into the data field.

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