Name: Intro to Data Engineering
Price: 36 USD

What You Learn

Discover the data engineering field and the career opportunities it offers
Learn data engineering fundamentals
Determine if data engineering is the right career choice for you
Benefit from the knowledge of an experienced data engineer
Learn strategies to enhance data processes at your company
Acquire key technical data engineering skills and approach data engineering interview questions with confidence

Top Choice of Leading Companies Worldwide

Industry leaders and professionals globally rely on this top-rated course to enhance their skills.

Course Description

Do you want to get an intro to data engineering? Are you interested in becoming a data engineer? If that’s the case, then our Intro to Data Engineering course is the perfect fit for you. Learn data engineering from course instructor Shashank Kalanithi, who has rich experience in the data and tech field. He has held roles as a data analyst, data scientist, data engineer, and currently works as a software engineer at Meta. Shashank is passionate about teaching and is eager to pass on his experience to you. His engaging teaching style combined with his notable professional experience make him the perfect tutor for you. If you’re unfamiliar with the field, you might ask ‘what does a data engineer do’? A data engineer designs, builds, and maintains systems for collecting, storing, and analyzing data. Our data engineering course is perfect for people who are looking into a career in data engineering, as well as for those who have already landed a data engineering job but are still in the early days of their journey. Why is this the perfect course for data newcomers? - Determine if data engineering is a career path that interests you - Understand the difference between common roles: data analyst vs data scientist vs data engineer vs software engineer (note: data engineering skills allow you to transition to any of the other roles as you advance in your career) - Learn fundamental data engineering concepts, how to become a data engineer, and how to land your first job Why is this the perfect course for entry level data engineers? - Gain a big picture understanding of the data engineering field and its requirements - Benefit from Shashank's years of experience and gain valuable insights to excel in your job - Understand the different paths you can take in your career progression - Discover methods to enhance data engineering processes within your company What’s included in our data engineer training? Intro to Data Engineering begins with an overview of the data engineering career path. You will learn about the data engineering role, the technical skills needed on the job, and the different potential paths for career development. Then, you will learn about data architecture—a critical topic in data engineering. This field involves creating a structured framework for managing data. You'll also explore data orchestration, which is the automation of the flow and processing of data across different systems. Our data engineering course also covers relational databases, non-relational databases, and the software engineering skills required for data engineering. You will learn about crucial data engineering tools and frameworks like SQL, NoSQL, Python, APIs, Version Control, Docker and Containerization, Hadoop, Spark, Kafka, and more. Finally, Shashank will wrap up the Intro to Data Engineering course with insights on important aspects like data security and privacy. We hope you are very excited about this course! Start your data engineering journey today!

Learn for Free

1.1 What will this course teach you

3 min

2.1 What is a Data Engineer?

7 min

2.2 Data Engineering lifecycle

8 min

Interactive Exercises

Practice what you've learned with coding tasks, flashcards, fill in the blanks, multiple choice, and other fun exercises.

Curriculum

1. Introduction

1 Lesson 3 Min

Get an introduction to the course author and learn how the "Intro to Data Engineering" course will boost your career.

What will this course teach you
3 min
2. Data Engineering Career

6 Lessons 46 Min

In this section of the course, you will learn what a data engineer is, the different data engineering lifecycles, and the career paths related to data engineering. Shashank Kalanithi offers a comprehensive comparison to other data science and software engineering professions, allowing you to understand how data engineers contribute to an engineering team and what precisely their role is.

What is a Data Engineer?
7 min
Data Engineering lifecycle
8 min
Similar careers to Data Engineering
9 min
Data Engineering service models
7 min
Data Engineer leveling guide
10 min
Technical skills of a Data Engineer
5 min
3. Data Architecture

6 Lessons 55 Min

This part of the course introduces the concept of data architecture, its uses, and its implementation as a data engineer. Data architecture is the overarching structure and design principles guiding the collection, storage, management, and use of data within an organization.

What is Data Architecture
7 min
A sample Data Architecture
11 min
Data lakes, Swamps, Warehouses, and Marts
7 min
Modern data stack
5 min
Connecting to data
12 min
Good Data Architecture
13 min
4. Data Orchestration

2 Lessons 14 Min

Data orchestration helps us coordinate, schedule, and run data workflows. Get an introduction to how companies use tools like Apache Airflow for their data orchestration needs.

Data Pipelines and Data Orchestration
3 min
Apache Airflow
11 min
5. Relational Databases

4 Lessons 19 Min

Relational databases are the core aspect around which most data engineering work revolves. Every data engineering job will have you interacting with relational databases.

Relational Database Overview
4 min
Organizing Relational Databases
4 min
Relational Database Types
7 min
Interacting with Relational Databases SQL
4 min
6. Non-relational Databases

8 Lessons 21 Min

NoSQL databases are designed to handle large volumes of structured, semi-structured, and unstructured data, providing flexible schemas and scalability that traditional relational databases lack. Learning about NoSQL is essential because it equips you with the skills to manage and analyze diverse data types efficiently in modern big data environments.

ACID Properties
5 min
Document Databases
5 min
Key-Value Database
1 min
Object Storage
3 min
Further reading Read now
1 min
Columnar Database
2 min
Graph Database
2 min
No-SQL Database Questions
2 min
7. Software Engineering

9 Lessons 34 Min

This section of the course covers crucial software engineering aspects necessary for effective data engineering. You'll learn about scaling techniques (horizontal vs. vertical), use Python for scripting and automation, interface with APIs, manage tasks using shell scripting and cron, maintain versions with tools like Git and Mercurial, ensure code quality through testing, deploy applications using Docker, and manage infrastructure efficiently. These skills are foundational for building and maintaining scalable and robust data processing systems.

Horizontal Scaling vs Vertical Scaling
3 min
Python
5 min
APIs
4 min
Shell Scripting
6 min
Cron
4 min
Version Control - Git - Mercurial
3 min
Testing
4 min
Docker and Containerization
3 min
Infrastructure Management
2 min
8. Big Data Engineering

4 Lessons 11 Min

In this part of the course, we will go over some of the larger concepts you have heard of and will provide a foundational understanding of what big data is. However, we will not go into too much detail because very few companies need to use these technologies at the scale required by Big Tech companies.

What is Big Data?
5 min
Hadoop
2 min
Spark
2 min
Kafka
2 min
9. Data Modeling

4 Lessons 15 Min

This section delves into Data Modeling, a cornerstone of data engineering that ensures structured and efficient data storage and retrieval. You'll explore the transformation from logical to physical data models, entity-relationship diagrams, normalization principles for database optimization, and the Kimball and Inmon approaches to data warehousing.

Logical Physical Data Model
4 min
Entity Relationship Diagrams
2 min
Normalization
5 min
Kimball and Inmon Data Warehousing
4 min
10. Security and Privacy

3 Lessons 8 Min

The concluding lessons of the Intro to Data Engineering course underscore the critical importance of security and privacy in data engineering. You will learn core principles related to how to minimize access rights for users, accounts, and computing processes to only those resources absolutely necessary for their functions, in an effort to enhance overall system security.

The Non-optionality of Security and Privacy
2 min
PII
3 min
Principle of Least Privilege
3 min

Topics

Data EngineeringCareer development

Tools & Technologies

Course Requirements

Highly recommended to take the SQL course first

Who Should Take This Course?

Level of difficulty: Beginner

Aspiring data engineers
People who want to work in data science or a related field
Data engineers who want to improve their ‘big picture’ understanding

Exams and Certification

A 365 Data Science Course Certificate is an excellent addition to your LinkedIn profile—demonstrating your expertise and willingness to go the extra mile to accomplish your goals.

Meet Your Instructor

Shashank Kalanithi

Data Engineer at Meta

2 Courses

302 Reviews

3864 Students

Shashank Kalanithi is data engineer at Meta. His previous experience includes being a senior data analyst at the fashion retailer Nordstrom, where he worked on ML solutions to help augment the data team’s capabilities. He designed tools and dashboards that optimize the workflow and gather valuable data on the company’s numerous locations. Shashank also runs his own data analyst service where he helps companies organize, study, and extract insights to increase in-house efficiency and profitability. His YouTube channel, which he started in 2020, has accumulated over 149K subscribers.