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Π‘ΡΡΠ°Π½ΠΈΡΠ°:
Introduction to Python for Data Science (3 hour)
Π‘ΡΡΠ°Π½ΠΈΡΡ
Adding AI to your Applications
Automate Your Development with GitHub Actions
Azure Cognitive Services with ML
Beginners Data Science for Python Developers (3 hour)
Beginners Data Science for Python Developers
Blockchain Fundamentals
Build a mobile app with Xamarin
Build a web app with ASP.NET Core
Build and Deploy applications to Azure by using GitHub Actions
Build continuous integration (CI) workflows by using GitHub Actions
Building and deploying a Django App
Building smart contracts for Blockcopoly
Building smart contracts with blockchain
Computer Vision API and Text Analytics
Connecting and deploying to Ethereum networks
Contribute to an Open Source Project on GitHub
Contributing guide
Create dynamic pages in Vue.js
Creating Chat Bots with TypeScript
Creating decentralized apps
DevOps Tools of the Trade
Discover Something new in Genomics Data
Embrace data nuances with K means
Embrace data nuances with Naive Bayes
End to End App Development Using Visual Studio Code
Explore Linear Regression and Classification with a bioscience project
Explore Logistic Regression with a loan application project
Explore Logistic Regression
Explore data types in Go
Explore the art world by using RESTFUL APIs
Exploring Genomics Data in VS Code
Exploring with Linear Regression
Get familiar with Solidity advanced data structures
Get started with Go
Get started with TypeScript
Get started with Vue CLI and single file components in Vue.js
Get started with Vue
Get started with the Windows Subsystem for Linux
Getting Started with JavaScript β Making Pages Dynamic
Getting started with DevOps
Getting started with HTML & CSS β Page layout and design
Getting started with HTML & CSS
Getting started with TypeScript No Learn Module
Getting started with TypeScript
Getting your data ready for analysis
HTML fundamentals
Home
How to Manipulate and Clean your data in Jupyter Notebooks
How to build a bot with QnA Maker
How to use Azure's Computer Vision Service
How to use NumPy and Pandas to write Python for Data Science
I 3 OSS
Implement interfaces in TypeScript
Intro to JQuery & APIs
Intro to Machine Learning Models
Intro to Python
Intro to Solidity
Introducing CSS selectors
Introduction to Python for Data Science (3 hour)
Introduction to Python for Data Science
Introduction to Python for space exploration
Introduction to blockchain on Azure
JavaScript fundamentals
Joining Datasets with Pandas
Learn about error handling in Rust
Learn how to work with offchain data using Oracles
Learn how to work with tokens in smart contracts
Learn the basics of PowerShell
Learn the foundations of programming in Go
Leverage GitHub Actions to Publish to GitHub Packages
Linear Regression with Azure Machine Learning
Making Your Data Useful for Analysis
Overview of Artificial Intelligence
Overview of Django
Pandas are more than bears: How to import, clean, and store data
Predict values with Linear Regression
Predict values with regression
Publish a Blazor WebAssembly app with Azure Static Web Apps
Quantum computing fundamentals
Rust 101
Rust: understand common concepts
Take Your First Steps with C#
Take Your First Steps with Python
TypeScript101
Use Machine Learning to Predict Rocket Launch Delays
Use the UNIX shell to wrangle log data
Using Advanced Machine Learning Models
Using the Azure Blockchain Development Kit
Using the Cloud for Machine Learning with ML Studio
0
Introduction to Python for Data Science (3 hour)
mebaumb ΡΠ΅Π΄Π°ΠΊΡΠΈΡΠΎΠ²Π°Π»(Π°) ΡΡΡ ΡΡΡΠ°Π½ΠΈΡΡ 2021-05-07 11:35:10 -07:00
Π‘ΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΠ΅
Event Information
Category | Details |
---|---|
Workshop Active? | No, too long for virtual events |
Reactor Topic | Data Science and Machine Learning |
Location | In person |
Workshop Level | Beginner |
Workshop Duration | 3 hours |
Title | Introduction to Python for Data Science |
Description | Data enables us to understand the world around us. Whether we're gathering data about our natural world to understand how it is changing, or analyzing patterns in how societies grow and change to ensure we're supporting all people, data is what drives the conversation. In this one-day workshop, we invite you to take the first step to learning how to understand data. With the power of Python, you will be able to explore data more quickly and develop more complex learnings from that data with just a few lines of code. Step 1: Learn the basics of Python coding and understand how it can be used to digest large data sets. You do not need any prior experience with data science to attend this workshop. You are likely someone who is interested in data science, maybe have coded a bit before in any programming language, and are looking to understand the basics of the Python programming language and the libraries that help with getting data prepped for analysis. You should bring your own laptop (Windows or Mac) with an Internet browser. You will be using Azure Notebooks, a cloud-based Jupyter Notebooks instance. All you will need is a Microsoft Account, which only requires an email address and for which you can sign up for at the event. |
Content Link | Unknown |
Event Dates Run:
Here's an overview of what this workshop will cover and suggested agenda to follow with links and resources.
Workshop Agenda
15 minutes Introduction to Data Science
45 minutes Introduction to Python
45 minutes NumPy: Your Local Data Friend
45 minutes Pandas are more than bears: How to import, clean, and store data
45 minutes Data Science 1:1 Getting your Data Ready
15 minutes Wrap Up and Next Steps
Resources
- TBD