The DataRobot for Automated Machine Learning course is designed to provide you with the skills and knowledge necessary to harness the power of DataRobot, an industry-leading platform for automated machine learning (AutoML).
DataRobot for Automated Machine Learning
The DataRobot for Automated Machine Learning course is designed to provide you with the skills and knowledge necessary to harness the power of DataRobot, an industry-leading platform for automated machine learning (AutoML). With DataRobot's AutoML tools, you can quickly and easily build, deploy, and monitor machine learning models without the need for extensive coding or data science expertise. This course will guide you through the end-to-end process of using DataRobot, from data preparation to model deployment, with hands-on experience in building models for various real-world applications.
Whether you're new to machine learning or looking to streamline your model development process, this course offers a practical approach to mastering DataRobot for Automated Machine Learning. By the end of this course, you'll be proficient in using the platform's features and tools to improve the efficiency and accuracy of machine learning tasks in a variety of business contexts.
This course is designed for business analysts, data scientists, and machine learning enthusiasts who want to leverage DataRobot for automated machine learning workflows. It’s ideal for professionals seeking to automate data science processes, streamline model development, and enhance decision-making capabilities using AI. Whether you have little experience with machine learning or you are looking to expand your knowledge of AutoML tools, this course will help you gain practical skills in building, evaluating, and deploying predictive models with DataRobot. This course is also beneficial for anyone involved in data-driven decision-making in industries like finance, healthcare, marketing, and technology.
Understand the fundamentals of automated machine learning (AutoML) and how DataRobot simplifies the model development process.
Get hands-on experience with DataRobot, from initial setup to data import and preparation.
Prepare and explore datasets to ensure they're ready for machine learning model development.
Build, evaluate, and interpret machine learning models using DataRobot’s advanced features.
Deploy and monitor machine learning models in production, ensuring they perform optimally over time.
Leverage DataRobot’s AutoML tools to automatically generate and compare multiple models for different use cases.
Customize and fine-tune models to meet specific business needs and improve prediction accuracy.
Apply your learning in a capstone project, where you'll implement an end-to-end AutoML workflow using DataRobot.
-
In this module, you will explore the concept of AutoML and understand its significance in modern data science. Learn how DataRobot automates the machine learning workflow and how it simplifies tasks such as data pre-processing, model building, and evaluation.
-
Get familiar with the DataRobot platform, learn how to navigate its interface, and set up your first machine learning project. This module will guide you through the process of creating a project, importing data, and preparing the environment for model development.
-
Data preparation is critical for building successful machine learning models. In this module, you will learn how to prepare and explore datasets within DataRobot, including techniques for handling missing data, normalizing features, and creating new features for model optimization.
-
Learn how to build predictive models using DataRobot’s automated machine learning features. This module will introduce you to the model-building process, from selecting the best algorithms to training models, and comparing their performance using DataRobot’s advanced tools.
-
After building models, it’s essential to evaluate and interpret their performance. This module focuses on the metrics and tools available in DataRobot for assessing model accuracy, identifying potential issues, and interpreting results to make informed decisions.
-
Once models are built and evaluated, deployment is the next step. Learn how to deploy models in real-world scenarios and monitor their performance in production using DataRobot’s deployment capabilities, ensuring they continue to deliver value over time.
-
Explore DataRobot's advanced features and customization options. Learn how to modify model parameters, fine-tune machine learning algorithms, and integrate external tools to extend DataRobot’s functionality and tailor it to specific business needs.
-
In the capstone project, you will apply all of the skills learned throughout the course to build an end-to-end machine learning workflow. This will include data preparation, model building, evaluation, deployment, and monitoring, providing a comprehensive hands-on experience with DataRobot.
Earn a Professional Certificate
Earn a certificate of completion issued by Learn Artificial Intelligence (LAI), recognised for demonstrating personal and professional development.
Martin Hu
DataRobot for Automa...I completed the DataRobot for Automated Machine Learning course, and it was a game-changer. The cour...
The course primarily uses DataRobot's graphical interface, which requires no coding to create machine learning models. However, if you wish to extend your knowledge, you may use Python or R for custom integrations and model tuning.
No prior machine learning experience is required. This course is suitable for both beginners and professionals who want to learn how to leverage automated machine learning tools like DataRobot.
Yes, this course is structured for self-paced learning, so you can work through the content at your own speed, revisiting any topics as needed.
DataRobot is an automated machine learning platform designed to simplify the process of building, deploying, and monitoring machine learning models. It allows users to create high-performing models without needing deep expertise in data science, by automating tasks like data preprocessing, algorithm selection, and model evaluation.
Automated machine learning (AutoML) works by automating the traditionally manual steps of the machine learning process, such as data cleaning, feature selection, model selection, training, and evaluation. Platforms like DataRobot allow users to input data and automatically generate a variety of machine learning models, which are then evaluated and compared to identify the best-performing solution.
DataRobot supports various data types, including numeric, categorical, and time-series data. The platform can handle structured data in formats such as CSV, Excel, and databases, as well as unstructured data like text, enabling it to work with a wide range of business data.
Key Aspects of Course
Premium quality course materials
Included for free with every course
