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    • Class and Course
    1. NExT
    2. Artificial Intelligence
    3. Applied Data Preparation and Visualization

    Applied Data Preparation and Visualization

    • Foundation
    • 5 Days
    • classroom1Classroom
      • Average client rating (based on 8 attendee reviews)

    • Gain an updated understanding of AI trends and refresh your Python skills, enabling you to utilize key libraries for AI development.  

    • Acquire expertise in data handling with Pandas and Numpy, and apply machine learning techniques for data preparation. 

    • Develop the ability to clean data, engineer features, and construct machine learning models using sklearn effectively. 

    • Learn comprehensive data annotation tools and methodologies, ensuring high-quality data for AI models. 

    • Design engaging visuals with Plotly and develop interactive web applications using Streamlit. 

    • Understand how to initiate and manage AI projects, orchestrate data, and deploy machine learning models using Dataiku’s visual interface and MLOps practices.  

    Module1: Understanding Your Data

    Machine Learning Refresh

    Why Data is Important

    Data Types

    Build the Dataset

    Feature Engineering

    Data Preparation and Management

    Systematic approach to data preparation

    Cleaning and Organizing Data

    Methods for consistent machine learning inputs

    Advancing skills in data augmentation

    Integrating diverse data sources


    Module3: Data Annotation​

    Fundamentals of Data Annotation

    Annotation Tools Exploration

    Best Practices in Data Annotation

    Quality Assurance in Annotation

    Module 4: Introduction to Interactive Visualization

    Introduction to Webapps

    Engaging Visuals with Plotly

    Dash Framework Overview

    Component Deep Dive

    Elevating Your Dashboards

    Module 5: Build End-to-End Workflow

    Hands-on Lab with No Code tools

    Connect Data

    Enrich Data

    Transform Data

    Visualize Data


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