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Rust for Data Engineering

سرفصل های دوره

In this course, learn how to use Rust to build high-performance data pipelines that you can use in data engineering, ML Ops, and traditional software engineering. Rust provides safety, speed, and low-level control for systems programming, and instructor Noah Gift illustrates these aspects in the four sections of this course. Noah starts off looking at the key features of Rust, including HashMaps and vectors. He then takes a look at safety, security, and concurrency with Rust. In the third section, Noah covers popular Rust data engineering libraries and tools, and finishes the course with a look at designing data processing systems in Rust.


01 - 1. Getting Started with the Modern Rust Development Ecosystem
  • 01 - Meet the instructor and course overview
  • 02 - Introduction to the AI coding paradigm shift
  • 03 - Introduction to cloud-based development environments
  • 04 - Introduction to GitHub Copilot ecosystem for Rust
  • 05 - Prompt engineering with GCP BigQuery SQL
  • 06 - Introduction to AWS CodeWhisperer for Rust
  • 07 - Using Google Bard to enhance productivity
  • 08 - Continuous integration with Rust and GitHub actions

  • 02 - 2. Rust Sequences and Maps
  • 01 - Introducing Rust sequences and maps
  • 02 - Demo Print Rust data structures
  • 03 - Demo Vector fruit salad
  • 04 - Demo VecDeque fruit salad
  • 05 - Demo LinkedIn list fruit salad
  • 06 - Demo Fruit salad CLI
  • 07 - Demo HashMap frequency counter
  • 08 - HashMap language comparison

  • 03 - 3. Rust Sets, Graphs, and Miscellaneous Data Structures
  • 01 - Analyzing UFC fighter network using graph centrality in Rust
  • 02 - Storing unique fruits using HashSet in Rust
  • 03 - Maintaining sorted and unique fruits using BTreeSet in Rust
  • 04 - Creating a fig-priority fruit salad using BinaryHeap in Rust
  • 05 - PageRank algorithm for sports data
  • 06 - Showing shortest path with Dijkstra
  • 07 - Detecting strongly connected components A deep dive into Kosarajus algorithm
  • 08 - Simple charting of data structures in Rust

  • 04 - 4. Rust Safety and Security Features
  • 01 - Multifactor authentication
  • 02 - Network segmentation
  • 03 - Least privilege access
  • 04 - Encryption
  • 05 - Mutable fruit salad
  • 06 - Customize fruit salad with a CLI
  • 07 - Data race example

  • 05 - 5. Security Programming with Rust
  • 01 - High availability
  • 02 - Understanding the Homophonic cipher A cryptographic technique
  • 03 - Decoding the secrets of the Caesar cipher
  • 04 - Building a Caesar cipher command-line interface
  • 05 - Creating a decoder ring A practical guide
  • 06 - Detecting duplicates with SHA-3 A data integrity tool
  • 07 - Incident response
  • 08 - Compliance

  • 06 - 6. Concurrency with Rust
  • 01 - Core concepts in concurrency
  • 02 - Dining philosophers
  • 03 - Web crawl Wikipedia with Rayon
  • 04 - Intelligent chatbot with Tokio
  • 05 - Multi-threaded deduplication with Rust
  • 06 - Energy efficiency Python vs. Rust
  • 07 - Concurrency stress test with a GPU
  • 08 - Host efficiency serverless optimization problem

  • 07 - 7. Using Rust to Manage Data, Files, and Network Storage
  • 01 - Process CSV files in Rust
  • 02 - Using Cargo Lambda with Rust
  • 03 - List files on AWS EFS with Rust
  • 04 - Use AWS S3 storage
  • 05 - Use AWS S3 storage from Rust
  • 06 - Write encrypted data to tables or Parquet files

  • 08 - 8. DataFrames with Rust, Python, and Notebooks
  • 01 - What is Colab
  • 02 - Using Bard to enhance notebook development
  • 03 - Exploring life expectancy in a notebook
  • 04 - Load a DataFrame with sensitive data
  • 05 - Using MLFlow with Databricks Notebooks
  • 06 - End to End ML with MLFlow and Databricks
  • 07 - Exploring global life expectancy with Polars

  • 09 - 9. Using Rust with Cloud SDKs and CLIs for Data Engineering
  • 01 - Cloud developer workspace advantage
  • 02 - Onboarding to GCP with Python and Rust
  • 03 - Using GCP Cloud Shell with Rust
  • 04 - Learn AWS CloudShell
  • 05 - Prototyping AI APIs with AWS CloudShell
  • 06 - Cloud9 with CodeWhisperer
  • 07 - Demo GCP App Engine Rust Deploy
  • 08 - Containerized Rust Actix Microservice on AWS

  • 10 - 10. Getting Started with Rust Data Pipelines (Including ETL)
  • 01 - Jack and the Beanstalk data pipelines
  • 02 - Open source data engineering Pros and cons
  • 03 - Core components of data engineering pipelines
  • 04 - Rust AWS step functions pipeline
  • 05 - Rust AWS Lambda Async S3 size calculator
  • 06 - What is Distroless
  • 07 - Demo Deploying Rust microservices on GCP

  • 11 - 11. Using Rust and Python for LLMs, ONNX, Hugging Face, and PyTorch Pipelines
  • 01 - Introduction to Hugging Face Hub
  • 02 - Rust PyTorch pre-trained model ecosystem
  • 03 - Rust GPU Hugging Face translator
  • 04 - Rust PyTorch high-performance options
  • 05 - EFS ONNX Rust inference with AWS Lambda
  • 06 - Theory behind model fine-tuning
  • 07 - Doing fine-tuning

  • 12 - 12. Building SQL Solutions with Rust, Generative AI, and Cloud
  • 01 - Selecting the correct database on GCP
  • 02 - Rust SQLite Hugging Face zero-shot classification
  • 03 - Prompt engineering for BigQuery
  • 04 - BigQuery to Colab pipeline
  • 05 - Exploring data with BigQuery
  • 06 - Using public data sets for data science
  • 07 - Querying log files with BigQuery
  • 08 - There is no one-size database
  • 09 - Course conclusion
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    تاریخ انتشار: 19 دی 1402
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