
Data Science Lifecycle: Collect, Clean, Predict & Analyze your Data
Let's collect, clean, predict and deploy your data science pipeline. As we all know a data science pipeline consists of various steps, which certainly starts with collecting your data from different data sources, then we come to understand the data making sure that we are able to get meaning out of it and we clean it by managing missing values and normalizing it and then we train and deploy our machine learning model which is followed by getting feedback from the model's results and re-evaluating it.
In this workshop, we will be collecting data, after which we will be cleaning it and create a machine learning model. The idea of the exercise is to understand the implementation of the Data Science Methodology and the phases involved in a data science project to give you a more hands-on and practical approach towards your data science journey using AutoAI.
🎓 What will you learn?
Data Science methodology
Understanding data collection processes
Data Cleaning techniques
Data considerations for creating machine learning models
👩💻 Who should attend
Beginner level workshop with no programming skills required
Students who are interested in AI or Data Science
Data Science & AI enthusiasts who want to learn
Anyone who wants to perform Data Cleaning without writing code
👩🏫 Prerequisites
Log in or sign up for a free IBM Cloud Account: xxx
Register for the live stream or to watch the replay: xxx
🎙️ Speakers
Khalil Faraj, Developer Advocate, https://www.linkedin.com/in/khalilfaraj/
Fawaz Siddiqi, Developer Advocate, IBM
(https://www.linkedin.com/in/fawazsiddiqi/)
Resources:
Sign up/Log in to your IBM Cloud Account
https://ibm.biz/CleanAndPredict
Follow along for the hands-on
https://ibm.biz/CleanAndPredict-HandsOn
Slides: https://ibm.biz/CleanAndPredict-Slides
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