60 hours / 20 classes
Mon Wed Fri 18:00 - 21:00
Math and Statistics for Data Science
Machine learning is a technical science and, like any technical subject, uses a mathematical language to formulate ideas. A growing number of solutions are trying to automate the whole process of machine learning, but if a person does not understand the mathematical formalism underlying the algorithms, it is impossible to test and debug models that can lead to false conclusions.
In this course, students learn the concepts of linear algebra, probability theory, and statistics that are key to exploratory data analysis, as well as understanding and developing machine learning algorithms.
- Linear algebra;
- Differential calculus;
- Probability theory;
- Bayes theorem;
- Distributions of random variables;
- Null hypothesis significance testing;
- Exploratory data analysis.
- Foundations of linear algebra, calculus, probability theory, and statistics;
- How to read complex mathematical equations that underlie all machine learning algorithms;
- How to understand the mathematics behind machine learning algorithms;
- How to think abstractly.
- a person looking for a career change
- a graduate from universities looking for a job in Data Science
- a developer with a mathematical mindset who would like to get career growth
- a business owner who would like to utilize data analysis and implement data-driven and AI projects
- a Data Scientist practitioner who wants to systematize the knowledge and to master Deep Learning