Generative AI for Data Engineering and Data Professionals

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Henry Habib,The Intelligent Worker

5:37:03

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1 - Introduction

1 - About the course.mp4

06:20

2 - Course Tips.html

3 - How Generative AI impacts Data Engineer Tasks.mp4

09:44

4 - Course Roadmap.mp4

04:09

5 - Caveats about Using Generative AI.mp4

05:46

6 - About the Instructor.mp4

01:08

7 - Keys to Success.mp4

02:22

8 - Ways to Contact.mp4

00:51

9 - Leave a Rating.mp4

00:56

2 - Environment Setup

10 - Environment Setup.mp4

02:10

11 - Option 1 Download Python VSCode and Jupyter Lab.mp4

09:01

12 - Option 2 Google Colab.mp4

03:52

13 - Set up OpenAI API.mp4

11:07

14 - Resources.html

14 - resources.zip

3 - Data Generation and Augmentation

15 - Introduction to using Generative AI for Data Generation and Augmentation.mp4

06:37

16 - Generating Synthetic Data with Generative AI.mp4

09:55

17 - Augmenting Existing Data with Generative AI.mp4

07:43

18 - Creating Time Series Data.mp4

04:41

19 - Generating Edge Cases in Data Engineering.mp4

08:13

20 - Handling PII Data with Generative AI.mp4

07:48

21 - Balancing Imbalanced Datasets in Data Engineering.mp4

04:11

22 - Activity Data Augmentation App Walkthrough.mp4

02:35

23 - Activity Creating Functions for Data Engineering.mp4

08:06

24 - Activity Running the Backend.mp4

04:18

25 - Activity Adding FrontEnd Components.mp4

05:48

26 - Activity Running the Web App GenAI for Data Engineering.mp4

05:57

4 - Writing Data Engineering Code with Gen AI

27 - Introduction to using Generative AI for Writing Data Engineering Code with Gen A.mp4

04:13

28 - Data Cleaning and Modeling with Generative AI.mp4

11:20

29 - Documenting Code for Data Projects.mp4

04:03

30 - Creating Data Schemas Systems and Pipelines.mp4

10:58

31 - Transferring Data with Generative AI.mp4

02:46

5 - Gen AI Data Engineering Tools

32 - Introduction to using Generative AI for Gen AI Data Engineering Tools.mp4

03:01

33 - Use ChatGPT for Data Engineering.mp4

14:49

34 - Build a Data Engineering App with Claude.mp4

09:00

35 - Custom GPTs for Data Engineering.mp4

03:29

36 - Custom LLM or Generative AI tools for Data Engineering.mp4

02:18

37 - Copilot for Azure Data Factory and Gemini for BigQuery.mp4

05:26

6 - Data Parsing and Extraction

38 - Introduction to using Generative AI for Data Parsing and Extraction.mp4

04:46

39 - Parsing Data Data Engineering.mp4

07:44

40 - Extracting Data from Web Scrapes and Images.mp4

10:10

41 - Performing Named Entity Recognition.mp4

05:39

42 - Activity Extracting Data from Contracts.mp4

15:41

7 - Data Querying and Analysis

43 - Introduction to using Generative AI for Data Querying and Analysis.mp4

03:20

44 - Querying Data with Generative AI.mp4

12:20

45 - Optimizing Data Queries.mp4

04:02

46 - Activity Developing Data Engineering Query Apps.mp4

15:59

47 - Activity Running Data Engineering Query Apps.mp4

07:43

48 - Activity Converting to a Web App with FrontEnd.mp4

07:40

8 - Data Enrichment Data Normalization and Standardization

49 - Introduction to using Generative AI for Data Enrichment Data Normalization and.mp4

05:37

50 - Enriching Features for Data Models.mp4

01:21

51 - Data Imputation and Normalization with Generative AI.mp4

11:06

52 - Imputation for Time Series Data Engineering.mp4

04:20

53 - Standardizing and Normalizing Textual Data with Generative AI.mp4

10:47

9 - Conclusion

54 - Conclusion and Certificate.mp4

02:07

55 - Ways to contact.mp4

00:53

10 - Bonus

56 - Bonus.mp4

01:07

Description

Work Faster with Practical Gen AI for Data Engineering | For all Data Professionals (Engineers, Analysts, Scientists)

What You'll Learn?

Integrate Generative AI into existing data flows and data engineering lifecycle
Learn how Gen AI is revolutionizing each step of the data engineering lifecycle, with hands-on practice and activities
Understand the role of Generative AI in Data Engineering, especially on when to use it and when not to use it
Generate and augment data using Generative AI
Write data engineering code with Generative AI
Explore Generative AI tools for data engineering
Parse and extract insights and data from unstructured text using Generative AI
Query and analyze data in data engineering with Generative AI
Enrich, normalize, and standardize data using Generative AI features

Who is this for?

Data engineers who want to incorporate Generative AI into their workflows

All data professionals (data engineers, data analysts, data scientists, data managers)

Data professionals or engineers who want to use Generative AI for data tasks

Anyone wanting to enhance their skills in data engineering and Gen AI integration

Developers aiming to build data engineering applications

Individuals curious about leveraging AI to streamline data workflows

What You Need to Know?

Familiarity with basic data engineering concepts (data cleaning, SQL queries)

Basic understanding of programming, especially Python

Familiarity with coding tools like Jupyter notebooks and VS Code

More details

Description
Note: this is as practical hands-on-keyboard course on how to use Generative AI in Data Engineering (and as a Data Professional). We will be using Python, OpenAI API, and Jupyter Notebooks to write and execute code.

Generative AI is changing the game in data and data engineering for two reasons:
Do tasks faster - Data professionals who use Generative AI complete tasks 16% faster. This increases to more then 45% if you code / analyze data on a day-to-day basis
Do new tasks - Generative AI enables data engineers and analysts to do so much more. In fact, some tasks like extracting features / insights from unstructured data or augmenting textual data is now only possible with Gen AI.

This is why GenAI is revolutionizing each step of the data engineering lifecycle. It doesn't matter if you're a data analyst, data scientist, data engineer, data professional, or data manager - you need to learn how to embed Generative AI in your day-to-day workflows.

That's what this course is all about - to make you more powerful and productive as a data professional with Generative AI.

Learn from more than 5.5 hours of relevant instructional video content, with the only course that will practically teach you the different ways that Generative AI is impacting the data engineering and data professional lifecycle, and then apply that to real-life end-to-end examples.

What is this course all about?
This course is all about how you can practically embed Gen AI into your day-to-day workflows as a Data Engineer or Data Professional. It's a deep practical guide on how Generative AI is revolutionizing each step of the data engineering lifecycle, making you more productive and powerful. This is a technical and practical course (it's not theoretical or hand-wavy).

Why learn Generative AI as a Data Professional or Data Engineer?
There are two reasons: productivity and power. Generative AI can do certain things faster - like writing SQL queries, documentation, creating schemas, and analyzing simple data. Generative AI can do things that were not possible before, like extracting insights from unstructured text, imputing textual data, or augmenting data while maintaining context. You must know how to use Gen AI to avoid being left behind.

How can Generative AI impact Data Engineering?
Gen AI impacts Data Engineering in many different ways. Specifically, we'll look at 7 different archetypes:
Data Generation and Augmentation
Writing Generative AI Code with Gen AI
Data Parsing and Extraction
Gen AI Data Engineering Tools
Data Querying and Analysis
Data Enrichment, Normalization, and Standardization
Anomaly Detection and Compression

What will you learn?
Integrate Generative AI - Learn how to fully embed Generative AI as a Data Professional in your workflows (including data generation, analysis, storage, visualization, pipelines, and more)
Be more productive - Generative AI is a productivity game changer - it can help you complete data tasks up to 20% faster (McKinsey), and even more if you write or use code
Be more powerful - Learn how to do more data tasks that weren't possible without Generative AI, like extracting insights from unstructured text or augmenting textual data

Why choose this course?
Complete guide - this is the 100% start to finish, zero to hero, basic to advanced guide on using Generative AI as a Data Engineer or Data Professional. There is no other course like it that teaches you everything from start to finish. It contains over 5.5 hours of instructional content!
Structured to succeed - this course is structured to help you succeed. We first go through the fundamentals on how Generative AI can be used for Data Engineering. Then, we go through the 7 different archetypes of how Gen AI can be embedded into your workflows. We go through each, one-by-one, in full detail.
Fully instructional - we not only go through important concepts, but also apply them. This is a practical hands-on-keyboard type course. This is not only a walkthrough of the all the features and theoretical concepts, but a course that actually uses real-life examples and integrates workflows with you.
Step by step - we go through every single method of how Generative AI can impact Data Engineering step-by-step. We start with examples, then complete full end-to-end activities to apply what we've learned.
Teacher response - if there's anything else you would like to learn, or if there's something you cannot figure out, I'm here for you! Look at the ways to reach out video.

Course overview
Introduction to Generative AI for Data Engineering - Get an overview of the course, learn how Generative AI impacts Data Engineering tasks, and become familiar with the course roadmap.
Environment Setup - Set up your workspace with two options: download Python, VSCode, and Jupyter Lab, or use Google Colab. We'll also guide you through setting up the OpenAI API.
Data Generation and Augmentation - Generate and augment data with Generative AI. Learn to create synthetic data, handle PII, balance datasets, and more. We'll also build a data augmentation app, from backend to frontend.
Writing Data Engineering Code with Generative AI - Discover how to use Generative AI for writing data engineering code. This section includes data cleaning, modeling, documenting code, creating data schemas, and transferring data.
Gen AI Data Engineering Tools - Explore tools like ChatGPT, Claude, custom GPTs, and other Gen AI tools for data engineering.
Data Parsing and Extraction - Parse and extract data from unstructured text using Generative AI, including data from web scrapes, images, contracts, invoices, receipts, and perform named entity recognition.
Data Querying and Analysis - Master querying and analyzing data with Generative AI. Optimize your queries, develop and run query apps, and convert them to web apps with front-end components.
Data Enrichment, Normalization, and Standardization - use Generative AI to enrich, normalize, and standardize your data, covering feature enrichment, data imputation, and standardizing textual data for better models.
Conclusion - this covers the certificate, next steps, and ways to get in touch.

If you want to learn how to improve your productivity and be more powerful as a data engineer (in practice, not in theory) using Generative, then this is the course for you. We're looking forward to having you in the course and hope you earn the certificate.
Who this course is for:
Data engineers who want to incorporate Generative AI into their workflows
All data professionals (data engineers, data analysts, data scientists, data managers)
Data professionals or engineers who want to use Generative AI for data tasks
Anyone wanting to enhance their skills in data engineering and Gen AI integration
Developers aiming to build data engineering applications
Individuals curious about leveraging AI to streamline data workflows

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Big Data

Henry Habib

Instructor's Courses

As a manager at one of the world's top management consulting firms, he advises F500 companies on growth strategy, operation, and analytics. He has a vast background in applying data-driven solutions to create impact, in both large and small organizations. Henry is also a big proponent of no-code application development in business. He deploys business application to his clients using No-Code solutions, which are much easier to understand and faster. He believes in the No-Code revolution. As a professor, Henry is passionate about teaching students on how to succeed, on any topic (case interviews, no-code application development, automation). He does this by creating courses with engaging and helpful content, and always being around to answer any questions.

The Intelligent Worker

Instructor's Courses

Hello, this is The Intelligent Worker! We are pioneering enthusiasts of technology and innovation. Having spent the better part of the last decade exploring the realms of AI, automation, and no-code solutions, our passion lies in harnessing these powerful tools to optimize productivity and enhance personal efficiency.We firmly believe that everyone should have the ability to use these tools, regardless of their background or skill level. That's why I've dedicated myself to simplifying and democratizing these technologies, ensuring that they're accessible to all.Through our courses on Udemy, we aim to share my knowledge and experience with learners around the world. we focus on practical applications of AI, automation, and no-code tools that can immediately impact your day-to-day life and work. Our mission is to equip you with the skills needed to be a more effective and efficient worker in this modern digital age.Join me in exploring these exciting technologies and start your journey towards becoming an Intelligent Worker!

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