DataRobot... for business analysts

DataRobot is for business analysts who want fast, accurate predictive models with or without programming. DataRobot complements your deep insight into business processes and data sources by automating model-building and optimization.

Two day course

DataRobot Essentials

Appropriate for business analysts and beginning data scientists

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Gain the skills you need to make the most of the automated capabilities of DataRobot to explore, model, and act on data. This course provides hands-on coverage of the DataRobot platform and its features, expert advice on best practices in machine learning, and guidance on how to integrate predictions into your production systems.

1. Data Exploration and Preparation

  • Data cleaning
  • Data loading
  • Exploratory data analysis
  • Target leakage

2. Modeling and Interpretation

  • Cross-validation
  • DataRobot Insights
  • Blended models
  • Model X-Ray
  • Learning curves
  • Model selection

3. DataRobot in Production

  • Accuracy vs latency
  • Batch prediction
  • Prediction API
  • Managing projects
one day course

Advanced DataRobot with R

Appropriate for graduates of DataRobot Essentials or DataRobot for Data Scientists who program in R

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The Advanced DataRobot with R course is a one-day, hands-on coverage of expert techniques to get the best machine learning results using the power of the DataRobot API. In addition, you’ll learn to build custom visualizations and autopilot processes as well as how to enhance results through sophisticated statistical methods.

1. DataRobot API

  • Creating and running projects
  • Extracting insights for visualizations
  • Pipeline automation

2. Advanced Techniques

  • Creating your own custom autopilot
  • Feature selection methods
  • Assessing variance in your results
two day course

Advanced DataRobot with Python

Appropriate for graduates of DataRobot Essentials or DataRobot for Data Scientists who program in Python

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Get the best machine learning results using advanced feature engineering and model tuning. Review the powerful pandas data preparation package, and learn to integrate advanced modeling and predictions into an automated workflow with the DataRobot API. DataRobot Essentials or DataRobot for Data Scientists and prior experience with Python required.

1. Data Preparation in Pandas

  • Exploratory analysis
  • Data cleaning
  • Data visualization
  • Table merges
  • Feature engineering

2. Advanced Techniques in DataRobot

  • Metric selection
  • Automated feature engineering
  • Creating feature lists
  • Advanced tuning

3. DataRobot API

  • Creating projects
  • Defining feature lists
  • Monitoring
  • Calling predictions
  • Pipeline automation
one day course

DataRobot Time Series Modeling

Appropriate for graduates of DataRobot Essentials or DataRobot for Data Scientists

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Gain the skills you need to make the most of the automated time series modeling capabilities of DataRobot to explore and make forecasts on your data. This course provides hands-on coverage of the DataRobot platform and its features, expert advice handling time series problems, and guidance on how to extract business value from your predictions.

1. Introduction to Time Series

  • Problem definition
  • Feature engineering
  • DataRobot’s approach

2. Modeling and Insights

  • Backtesting
  • Accuracy plots
  • Feature interpretation
  • Making forecasts

3. Best Practices

  • Enriching data
  • Feature Selection
  • Model Evaluation
Two to five day training

Custom Client Training

Appropriate for Groups of six or more DataRobot users in one location

Working together, we tailor curriculum and instruction to your team’s experience level, preferred tools, and industry. Training can be customized to your datasets or to public datasets appropriate to your predictive modeling challenges. This training includes and can expand on the coverage of DataRobot Essentials.

1. Data Exploration

  • Data preparation in Python
  • Data preparation in R
  • Data preparation in SAS
  • DataRobot and Hadoop
  • Feature Engineering

2. Modeling and Interpretation

  • Cross-validation
  • Model X-Ray
  • Learning curves
  • Blended models
  • DataRobot insights
  • Model selection

3. DataRobot in Production

  • Accuracy vs latency
  • Prediction API
  • DataRobot Prime
  • Managing and sharing projects

Have a question about learning data science with DataRobot?

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