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Course Description

This course provides a comprehensive introduction to DataRobot, a leading AI and automated machine learning (AutoML) platform. Participants will learn how to build, deploy, and monitor machine learning models using DataRobot’s automated tools. The training emphasizes data preparation, model selection, evaluation, and deployment strategies, enabling participants to leverage AI for data-driven decision-making without extensive coding expertise.

Course Objectives

Upon completion of this course, participants will be able to:

  • Understand the fundamentals of AutoML and the DataRobot platform.
  • Prepare and upload datasets for automated modeling.
  • Build, evaluate, and compare machine learning models.
  •  Deploy and monitor models in production environments.
  • Interpret AI model outputs and insights to support business decisions.

Who Should Attend?

This course is designed for data analysts, data scientists, business analysts, and IT professionals interested in AI-driven predictive analytics.

Course Agenda

Registration

Welcome & Introduction

Pre-Test

Day 1: Introduction to DataRobot & AutoML Concepts

  • Overview of AI, machine learning, and AutoML
  • Introduction to the DataRobot platform and interface
  • Key concepts: models, projects, predictors, and outcomes
  • Understanding data types and features
  • Case studies: business applications of AutoML

Day 2: Data Preparation & Feature Engineering

  • Data exploration and cleaning
  • Handling missing values and outliers
  • Feature selection and transformation
  • Feature impact and understanding predictors
  • Best practices for preparing high-quality datasets
Day 3: Building and Evaluating Models

  • Automated model building process
  • Model types: regression, classification, time series
  • Model comparison and leaderboard interpretation
  • Model evaluation metrics (RMSE, AUC, accuracy, etc.)
  • Understanding model explanations and insights
Day 4: Model Deployment & Monitoring

  • Deploying models for predictions
  • Model monitoring and performance tracking
  • Managing retraining and model lifecycle
  • Integrating models into business processes
  • Governance and compliance considerations
Day 5: Advanced Features & Applications

  • Time series modeling in DataRobot
  • AI-driven insights and decision-making
  • Using APIs for automated workflows
  • Case studies and scenario analysis
  • Review, Q&A, and knowledge assessment

Post Test

End of the Course

Assessment Methodology

All courses conducted by EdTech will begin with a Pre-evaluation and end with a Post-evaluation. The instructor will evaluate the knowledge and skills of the participants according to the feedback given by participants. This will help to recognize the benefits and the level of knowledge gained by participants through the course.

Training Methodology

Facilitated by a highly qualified specialist, who has extensive knowledge and experience; this program will be conducted using extensively interactive methods, encouraging participants to share their own experiences and apply the program material to real-life work situations in order to stimulate group discussions and improve the efficiency of the subject coverage.

Percentages of the total course hour classification are:

  • ​40% Theoretical lectures, Concepts and approach
  • 20% Motivation to develop individual skill and Techniques
  • 20% Case Studies and Practical Exercises
  • 20% Topic General Discussions and interaction

Course Manual

Participants will be provided with comprehensive presentation material as reference manual. This presentation material is a compilation of core valuable information, references, presentation methods and inspiring reading which will be used as a part of the material guide.

Course Certificate

At the completion of the course, all participants who successfully accomplished the required contact hours will receive an EdTech Training Participation Certificate as a testimony to their commitment to professional development and further education.

Why Edtech ?

  • Industry Experienced; Internationally Qualified Trainers
  • Hands-on Practical Sessions & Assignments
  • Intensive Study materials
  • Flexible Schedules
  • Realistic training methodology
  • High-Quality Training in Affordable Course Fees
  • Achievement Certificate, as approved by the Ministry of Education (Abu Dhabi Center for Technical and Vocational Education Training - ACTVET), HABC, AWS, IAOSHE, SHRM, etc.