Udemy – Chatgpt For Data Engineers

What you'll learn
Learn how to use ChatGPT to write, debug, and optimize code for data pipelines, SQL queries, and automation scripts across tools like Spark, Airflow, and Bash.
Master Prompt Engineering for Data Use Cases
Discover how to apply ChatGPT in real-life use cases including pipeline creation, performance tuning, schema design, and cloud-based deployment.
Create custom workflows and tools using ChatGPT and APIs to automate repetitive tasks, enhance productivity, and boost team collaboration.
Requirements
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
Description
In today's fast-paced data-driven world, efficiency, automation, and innovation are key to staying ahead. This course, "ChatGPT for Data Engineers," is designed to empower data professionals with the practical skills and strategies to leverage Generative AI tools like ChatGPT in real-world data engineering workflows.Whether you're writing complex SQL queries, designing scalable ETL pipelines, automating documentation, or debugging code, ChatGPT can act as your virtual co-pilot. This course blends hands-on demos, best practices, and real-world use cases to help you integrate ChatGPT into every stage of your data engineering lifecycle — from ideation to implementation.You'll learn how to use ChatGPT to:Generate, optimize, and explain SQL queries for different databasesAutomate data pipeline tasks and script generation in Python, Bash, and SparkTranslate requirements into technical specifications using prompt engineeringBuild AI-powered tools to streamline documentation, data profiling, and quality checksBy 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.Perfect for aspiring and experienced data engineers, data analysts, and technical leads looking to future-proof their skill set with cutting-edge AI tools.
Overview
Section 1: Introduction to ChatGPT for Data Engineers
Lecture 1 What is ChatGPT? Overview of Generative AI
Lecture 2 Why Data Engineers Should Care About LLMs
Lecture 3 Capabilities & Limitations of ChatGPT
Lecture 4 ChatGPT Sneak Peek
Lecture 5 Hands On Practice Part 1
Lecture 6 Use Cases of ChatGPT in Data Engineering
Lecture 7 Hands On Practice Part 2
Section 2: Mastering Prompt Engineering
Lecture 8 What is Prompt Engineering?
Lecture 9 Crafting Effective Prompts for Data Tasks
Lecture 10 Hands On Practice Part 3
Lecture 11 Prompt Patterns: Templates, Chains, and Variables
Lecture 12 Debugging and Refining Prompts for Better Results
Section 3: ChatGPT for Data Exploration and SQL
Lecture 13 Writing and Optimizing SQL Queries with ChatGPT
Lecture 14 Data Profiling and Summarization
Lecture 15 Explaining Complex Queries and Database Schemas
Lecture 16 Data Cleaning Suggestions Using AI
Section 4: ChatGPT for Python & Data Pipelines
Lecture 17 Auto-generating Python Scripts and Functions
Lecture 18 Converting Pseudo-code to Production-ready Code
Lecture 19 Writing ETL Scripts with ChatGPT
Lecture 20 Using ChatGPT for Code Reviews and Refactoring
Section 5: Integrating ChatGPT with Data Engineering Tools
Lecture 21 Connecting ChatGPT to Apache Spark Jobs
Lecture 22 Automating Airflow DAG Generation
Lecture 23 Assisting with Kafka Topic Management
Lecture 24 ChatGPT for Dockerfile and Kubernetes YAML Creation
Section 6: Automation & Documentation with ChatGPT
Lecture 25 Auto-generating Project Documentation
Lecture 26 Writing README Files and Code Comments
Lecture 27 Explaining Data Workflows to Non-Technical Stakeholders
Lecture 28 Creating Architecture Diagrams from Text Prompts
Section 7: ChatGPT for DevOps & Monitoring
Lecture 29 Writing Bash Scripts and Monitoring Scripts
Lecture 30 Assisting with CI/CD YAML Configuration
Lecture 31 Analyzing Log Files with ChatGPT
Lecture 32 Suggestions for Performance Tuning
Section 8: Ethical Use, Risks, and Limitations
Lecture 33 Avoiding Over-Reliance on AI
Lecture 34 Validating AI-Generated Code and Outputs
Lecture 35 Data Privacy & Security Considerations
Lecture 36 Responsible Use of Generative AI in Data Teams
Aspiring & Junior Data Engineers,Mid-Level & Senior Data Engineers,Data Analysts & Scientists,ETL Developers & Pipeline Architects,DevOps & MLOps Practitioners,Tech-Curious Professionals

Homepage

https://www.udemy.com/course/chatgpt-for-data-engineers/

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