Master Machine Learning with Qlik AutoML: No-Code Approach

This section lays the foundation for your machine learning journey. You'll discover the fundamentals of machine learning, understanding its core concepts and applications. Dive into the world of Automated Machine Learning (AutoML) and explore its key benefits, including streamlining model building and making machine learning accessible to a wider audience. You'll also gain a clear understanding of how AutoML works, including the steps involved in building and deploying machine learning models.

Get ready to delve into the world of Qlik AutoML, a powerful tool that empowers users to build machine learning models without coding. You'll explore the platform's features, including its intuitive interface, diverse algorithms, and extensive capabilities for data analysis and prediction. Discover the various use cases of Qlik AutoML across different industries, gaining insights into its applicability in real-world scenarios. This section also explores the algorithms employed by Qlik AutoML, equipping you with a foundational understanding of how these algorithms contribute to model building and prediction.

Gain a deeper understanding of key machine learning terminology and concepts that are crucial for building and evaluating models. You'll learn about metrics like F-score, permutation importance, and SHAP importance for assessing model performance and understanding feature contributions. Explore model fitting, correlation matrix, ROC curve, and confusion matrix for a comprehensive view of model accuracy and predictive power. Uncover the role of hyperparameters in model optimization and how to fine-tune these parameters to achieve desired results. Finally, learn about cross-validation and automatic holdout techniques for ensuring the robustness and generalizability of your models.

Get hands-on with Qlik AutoML! This section guides you through the signup process and initial setup, equipping you with the tools to start building your first project. You'll learn how to add data to Qlik AutoML and create a project for analyzing the breast cancer dataset. Dive into the process of managing data pipelines and explore the training data model output, gaining insights into the model's predictions and performance. You'll also delve into the intricacies of Qlik AutoML cards, learning to interpret their output and understand how to leverage them for data analysis. Finally, explore how to use the model for generating predictions on test data and compare those predictions with actual values to assess accuracy. You'll also learn how to use the scenario editor to perform what-if analysis, enabling you to explore different scenarios and gain valuable business insights.

Put your newfound skills to the test with a series of hands-on projects using Qlik AutoML. Learn to build machine learning models for different real-world applications, expanding your practical expertise and understanding of the platform's capabilities. Dive into stock value prediction, customer churn analysis, and weather forecasting, gaining insights into how Qlik AutoML can be applied to solve a wide range of business problems.

This section equips you with the knowledge and resources to further enhance your machine learning expertise. Learn practical strategies for improving model score and optimizing performance, ensuring that your models deliver the highest level of accuracy and insights. Discover valuable resources for accessing diverse datasets and expanding your hands-on practice with machine learning. As you complete the course, you'll receive a comprehensive understanding of Qlik AutoML and its capabilities, setting you on a path for continued growth and success in the field of machine learning.