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Mastering Dataiku: End-to-End AI & Data Science
Gain hands-on expertise in leveraging Dataiku for data preparation, analytics, and the deployment of machine learning solutions at scale.
What you'll learn
Develop comprehensive proficiency in using Dataiku to drive data science, analytics, and AI workflows from ideation to deployment.
- Navigate Dataiku’s user interface and understand its full feature set
- Perform data ingestion, preparation, and transformation for analytical use
- Build and evaluate predictive models using both code-free and code-assisted approaches
- Automate machine learning processes through integrated AutoML capabilities
- Deploy AI applications and orchestrate production-grade data pipelines
This course is designed for data analysts, data engineers, and AI professionals aiming to streamline end-to-end data science workflows with Dataiku.
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Course Content
- Introduction to the Dataiku platform and its core architecture
- Exploring the visual interface and primary functionalities
- Creating and managing end-to-end projects within Dataiku
- Importing datasets from diverse sources
- Cleaning, enriching, and transforming raw data for analysis
- Implementing feature engineering techniques to enhance model accuracy
- Designing and training machine learning models within Dataiku
- Utilizing AutoML for scalable predictive analytics
- Operationalizing and deploying models within real-world workflows
Requirements
- Fundamental understanding of data science principles and AI workflows
- No prior coding experience required (support available for code-driven users)
- Strong interest in automating and accelerating analytics through a unified platform
Description
- Gain practical experience in preparing and analyzing data with Dataiku
- Automate ML pipelines with built-in AutoML tools and scalable workflows
- Deploy robust AI solutions and optimize your analytics infrastructure for real-world applications
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