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Generative AI for Data Engineering and Data Professionals

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


1 - Introduction
  • 1 - About the course
  • 2 - Course Tips.html
  • 3 - How Generative AI impacts Data Engineer Tasks
  • 4 - Course Roadmap
  • 5 - Caveats about Using Generative AI
  • 6 - About the Instructor
  • 7 - Keys to Success
  • 8 - Ways to Contact
  • 9 - Leave a Rating

  • 2 - Environment Setup
  • 10 - Environment Setup
  • 11 - Option 1 Download Python VSCode and Jupyter Lab
  • 12 - Option 2 Google Colab
  • 13 - Set up OpenAI API
  • 14 - Resources.html
  • 14 - resources.zip

  • 3 - Data Generation and Augmentation
  • 15 - Introduction to using Generative AI for Data Generation and Augmentation
  • 16 - Generating Synthetic Data with Generative AI
  • 17 - Augmenting Existing Data with Generative AI
  • 18 - Creating Time Series Data
  • 19 - Generating Edge Cases in Data Engineering
  • 20 - Handling PII Data with Generative AI
  • 21 - Balancing Imbalanced Datasets in Data Engineering
  • 22 - Activity Data Augmentation App Walkthrough
  • 23 - Activity Creating Functions for Data Engineering
  • 24 - Activity Running the Backend
  • 25 - Activity Adding FrontEnd Components
  • 26 - Activity Running the Web App GenAI for Data Engineering

  • 4 - Writing Data Engineering Code with Gen AI
  • 27 - Introduction to using Generative AI for Writing Data Engineering Code with Gen A
  • 28 - Data Cleaning and Modeling with Generative AI
  • 29 - Documenting Code for Data Projects
  • 30 - Creating Data Schemas Systems and Pipelines
  • 31 - Transferring Data with Generative AI

  • 5 - Gen AI Data Engineering Tools
  • 32 - Introduction to using Generative AI for Gen AI Data Engineering Tools
  • 33 - Use ChatGPT for Data Engineering
  • 34 - Build a Data Engineering App with Claude
  • 35 - Custom GPTs for Data Engineering
  • 36 - Custom LLM or Generative AI tools for Data Engineering
  • 37 - Copilot for Azure Data Factory and Gemini for BigQuery

  • 6 - Data Parsing and Extraction
  • 38 - Introduction to using Generative AI for Data Parsing and Extraction
  • 39 - Parsing Data Data Engineering
  • 40 - Extracting Data from Web Scrapes and Images
  • 41 - Performing Named Entity Recognition
  • 42 - Activity Extracting Data from Contracts

  • 7 - Data Querying and Analysis
  • 43 - Introduction to using Generative AI for Data Querying and Analysis
  • 44 - Querying Data with Generative AI
  • 45 - Optimizing Data Queries
  • 46 - Activity Developing Data Engineering Query Apps
  • 47 - Activity Running Data Engineering Query Apps
  • 48 - Activity Converting to a Web App with FrontEnd

  • 8 - Data Enrichment Data Normalization and Standardization
  • 49 - Introduction to using Generative AI for Data Enrichment Data Normalization and
  • 50 - Enriching Features for Data Models
  • 51 - Data Imputation and Normalization with Generative AI
  • 52 - Imputation for Time Series Data Engineering
  • 53 - Standardizing and Normalizing Textual Data with Generative AI

  • 9 - Conclusion
  • 54 - Conclusion and Certificate
  • 55 - Ways to contact

  • 10 - Bonus
  • 56 - Bonus
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    شناسه: 41118
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    مدت زمان: 338 دقیقه
    تاریخ انتشار: 15 آبان 1403
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