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ChatGPT for Data Engineers

person icon Bigdata Engineer

4.6

ChatGPT for Data Engineers

Practical Applications of ChatGPT for Modern Data Engineers

updated on icon Updated on Jul, 2025

language icon Language - English

person icon Bigdata Engineer

category icon Development ,Data Science,ChatGPT

Lectures -40

Resources -4

Duration -4.5 hours

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4.6

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Course Description

With the accelerated speed of life on information premises today, innovation, automation, and efficiency are the bridge to staying up to date. The "ChatGPT for Data Engineers" course is a step in the direction of equipping data professionals with hands-on experience and expertise to apply Generative AI software like ChatGPT in actual data engineering pipelines.

Whether you are crafting intricate SQL queries, architecting horizontally distributed ETL pipelines, writing auto-generated docs, or debugging code, ChatGPT is your virtual copilot. This course combines hands-on demos, best practices, and real-world examples to demonstrate how to make ChatGPT a part of every aspect of your data engineering workflow — from ideation to deployment.

You'll be at ease with using ChatGPT to:
Construct, refactor, and document SQL queries across several databases
Script data pipeline activities and generation in Bash, Python, and Spark
Translate requirements into technical specs through prompt engineering
Create AI-powered tools to auto-generate documentation, data profiling, and quality testing

By the end of this course, you’ll not only understand the capabilities and limitations of ChatGPT, but also have the skills to apply it confidently in your daily workflow to save time, improve accuracy, and drive innovation.
Intended for future and current data engineers, data analysts, and technical leaders looking to future-proof themselves using the most current AI technology.

Goals

  • Learn to use ChatGPT to write, debug, and optimize data pipeline code, SQL queries, and automation scripts on Spark, Airflow, and Bash platforms.
  • Master Prompt Engineering for Data Use Cases
  • Learn how to deploy ChatGPT into practical applications such as pipeline development, performance optimization, schema design, and cloud-based deployment.
  • Master Prompt Engineering for Data Use Cases
  • Learn how to use ChatGPT in actual use cases such as pipeline building, performance optimization, schema design, and deployment on clouds.
  • Build custom workflows and tools with ChatGPT and APIs to automate mundane tasks, increase productivity, and improve team collaboration.

Prerequisites

Basic Understanding of Data Engineering Concepts
Working Knowledge of SQL and Python
Comfort with the Command Line & Scripting
Curiosity About AI and Automation
Optional: Familiarity with Tools Like Spark, Airflow, or Docker
ChatGPT for Data Engineers

Curriculum

Check out the detailed breakdown of what’s inside the course

Introduction to ChatGPT for Data Engineers

7 Lectures
  • play icon What is ChatGPT? Overview of Generative AI 07:46 07:46
  • play icon Why Data Engineers Should Care About LLMs 04:21 04:21
  • play icon Capabilities & Limitations of ChatGPT 07:40 07:40
  • play icon ChatGPT Sneak Peek 05:16 05:16
  • play icon Hands On Practice Part 1 17:28 17:28
  • play icon Use Cases of ChatGPT in Data Engineering 09:28 09:28
  • play icon Hands On Practice Part 2 23:37 23:37

Mastering Prompt Engineering

5 Lectures
Tutorialspoint

ChatGPT for Data Exploration and SQL

4 Lectures
Tutorialspoint

ChatGPT for Python & Data Pipelines

4 Lectures
Tutorialspoint

Integrating ChatGPT with Data Engineering Tools

4 Lectures
Tutorialspoint

Automation & Documentation with ChatGPT

4 Lectures
Tutorialspoint

ChatGPT for DevOps & Monitoring

4 Lectures
Tutorialspoint

Ethical Use, Risks, and Limitations

4 Lectures
Tutorialspoint

Real-World Projects and Use Cases

4 Lectures
Tutorialspoint

Instructor Details

Bigdata Engineer

Bigdata Engineer

I am Solution Architect with 12+ year’s of experience in Banking, Telecommunication and Financial Services industry across a diverse range of roles in Credit Card, Payments, Data Warehouse and Data Center programmes

My role as Bigdata and Cloud Architect to work as part of Bigdata team to provide Software Solution.

Responsibilities includes,

- Support all Hadoop related issues
- Benchmark existing systems, Analyse existing system challenges/bottlenecks and Propose right solutions to eliminate them based on various Big Data technologies
- Analyse and Define pros and cons of various technologies and platforms
- Define use cases, solutions and recommendations
- Define Big Data strategy
- Perform detailed analysis of business problems and technical environments
- Define pragmatic Big Data solution based on customer requirements analysis
- Define pragmatic Big Data Cluster recommendations
- Educate customers on various Big Data technologies to help them understand pros and cons of Big Data
- Data Governance
- Build Tools to improve developer productivity and implement standard practices

I am sure the knowledge in these courses can give you extra power to win in life.

All the best!!

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