This is a short introduction to Product Management. In this course, you’ll learn what Product…
This course introduces a variety of methods commonly used in predictive analytics, data mining, and managerial science. While most of us have heard how “hot” big data is nowadays, few of us understand what actually stands behind big data. In ten days, we’ll cover different data-driven and model-based approaches, such as K-Nearest Neighbors, Naïve Bayes, association rules, decision tree analysis, logistic regression, and others, which are widely used not only in business but also in many other fields, as the interest in artificial intelligence and machine learning increases. We’ll discuss the most popular applications of these approaches.
238 students completed this course
88% recommend it to other students
Teacher: Polina Durneva
“Great to get a first peak at the different analysis options. Clear and easy to understand.”
“Simple and good enough to know the basic. Good and clear examples given to illustrate the different techniques.”
Lesson 1. K-Nearest Neighbor
Lesson 2. Naïve Bayes
Lesson 3. Association Rules
Lesson 4. Cluster Analysis
Lesson 5. Decision Tree Analysis
Lesson 6. Linear Regression
Lesson 7. Logistic Regression
Lesson 8. Optimization
Lesson 9. Monte Carlo Simulation
Lesson 10. Final Thoughts on Business Analytics Methods
Starting tomorrow, you will receive a new lesson straight to your inbox every morning for 10 days. Lessons take just 5 minutes to read, and each course is followed by fun, knowledge-testing quiz.
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