Course Description

The math and statistics behind machine learning

Learn Python and the fundamental concepts behind Machine Learning. In this course you will have the opportunity to obtain a thorough mathematical understanding of many of these concepts which will help you later during the bootcamp to grasp the inner workings of the algorithms and get good results.


Course Outcomes

  • Obtain an in-depth knowledge of the mathematical theory used for Machine Learning and any data-driven decision making methodology

  • Learn how to solve problems in mathematics and statistics with Python

  • Create beautiful graphs with matplotlib library

Training Content

A quick brush up of the most important topics:

  • Anaconda installation, getting started with Jupyter notebooks
  • Variables, numbers, strings and print formatting
  • Objects and Data Structures
  • Comparison operators & Statements
  • Methods & Functions
  • List comprehension
  • Error handling
  • String manipulations
  • Basic visualizations
  • Systems of linear equations
  • Matrices
  • Matrix transformations
  • Learn the NumPy library
  • Eigenvalues and eigenvectors
  • Matrix decomposition
  • Determinant and trace
  • Singular Value decomposition
  • Differentiation of Univariate Functions
  • Partial Differentiation and Gradients
  • Chain Rule
  • Constrained Optimization and Lagrange Multipliers
  • Discrete and Continuous Probabilities
  • Sum Rule, Product Rule, and Bayes’ Theorem
  • Means and Covariances
  • Descriptive Statistics
  • Inferential Statistics
  • Gaussian Distribution and Descriptive Stats
  • Correlation Between Variables

Use statistics and visualizations to explore a dataset of a business case

More Courses

Introduction to Python for Data Science


Launch your career in Data Science

Next Bootcamp: 13.09.2021 - 03.12.2021