Essential Math for Data Science
- 33 Courses | 45h 36m 13s
Track 1: Introduction to Math
In this track of the Essential Math for Data Science Skillsoft Aspire journey, you will focus on the fundamentals of linear algebra and calculus. This includes discrete math concepts and their implementations, theoretical and practical guide to calculus, exploring linear algebra, and matrix operations.
- 10 Courses | 12h 44m 33s
Track 2: Statistics and Probability
In this track of the Essential Math for Data Science Skillsoft Aspire journey, you will acquire a deeper understanding of probability and statistical concepts including probability distributions, various types of statistical tests, and hypothesis testing. You will deep dive into understanding conditional probability concepts that forms the crux of naïve Bayes classification algorithms.
- 12 Courses | 17h 23m 14s
Track 3: Math Behind ML Algorithms
In this track of the Essential Math for Data Science Skillsoft Aspire journey, the focus will be on math applied in various machine learning algorithms. You will understand the intuition behind these algorithms along with math used in their optimization/loss/cost functions. You will understand the math behind regression algorithms, decision trees, distance-based models, kernel methods and SVM and neural networks.
- 9 Courses | 12h 49m 36s
Track 4: Advanced Math
In this track of the Essential Math for Data Science Skillsoft Aspire journey, the focus will be on math behind advanced concepts such as principal component analysis, recommendation systems, and gradient descent.
- 2 Courses | 2h 38m 50s
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