• Class and Course

    No-Code AI: Hands-On Training

    "No-Code AI: Hands-On Training" is a practical workshop designed to empower participants with the skills and knowledge to build AI models and applications without the need for programming. Leveraging user-friendly no-code tools, attendees will be guided through the process of creating, training, and deploying AI solutions.

    Dataiku Core Concepts 

    • Introduction to Dataiku
    • Create the Project
    • Create the Dataset
    • Explore your Data
    • Prepare your data
    • Interactive Visual Statistics
    • Group the data
    • Explore the Flow
    • Data enrichment with Join Recipe
    • Welcome to the Lab
    • Reporting Tools

    A No Code example of Machine Learning applied to Subsurface Data (a geological facies prediction)

    • Data preprocessing for facies classification
    • Data visualization, statistics and dashboards
    • Model training and prediction
      • Let’s setup a first baseline
      • Hyper parameters tuning
      • Model interpretation

    Dataiku for Excel Users (automating manual tasks with Dataiku flows and AI) 

    Dataiku for Excel Users

    • Data cleaning and preparation with visual recipes
    • Working with dates and formulas
    • Dataset connection, aggregation, and pivot tables 

    Automating manual tasks

    • Introduction to MLOps
    • Create a scenario to automate your workflow
    • Add a visual interface for non-data scientists users
    • Push your workflow to production to get consumed by other applications

    Currently there are no scheduled classes for this course.

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    Set a training goal, and easily track your progress

    Customize your own learning journey and track your progress when you start using a defined learning path.

    In just few simple steps, you can customize your own learning journey in the discipline of your interest based on your immediate, intermediate and transitional goals. Once done, you can save it in NExTpert, the digital learning ecosystem, and track your progress.
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