Discover how to apply business analytics and machine learning techniques to decipher complex business data, derive actionable insights, and drive strategic decisions. Develop understanding about the key-terminology around descriptive and predictive analytics and get familiar with no-code tools for you own analyses.

Day 1: Basics of Data Analytics and Machine Learning

Understand the foundations of data-driven decision-making.
Explore descriptive analytics, data visualization, and diagnostic analytics.
Familiarize yourself with essential terminology and no-code tools for analysis.

Day 2: Introduction to Machine Learning (Predictive Analytics) – Part I

Gain insights into artificial intelligence, machine learning, and deep learning.
Differentiate between supervised and unsupervised learning.
Dive into practical examples, including logistic regression and decision trees.

Day 3: Introduction to Machine Learning (Predictive Analytics) – Part II

Explore advanced techniques like random forests and lasso regression.
Discover the power of boosting algorithms.
Learn how to assess and fine-tune algorithm performance with real-world examples.