Free Download Applied Math for Data Science by Thomas NieldMP4 | Video: h264, yuv420p, 1920x1080 | Audio: aac, 44100 Hz | Duration: 5h 41m | 1.45 GB
Genre: eLearning | Language: English
With the availability of data, there is a growing demand for talent who can analyze and make sense of it. This makes practical math all the more important because it helps infer insights from data. However, mathematics comprises many topics, and it is hard to identify which ones are applicable and relevant for a data science career. Knowing these essential math topics is key to integrating knowledge across data science, statistics, and machine learning.
In this course, learners will delve into a carefully curated list of mathematical topics to jumpstart proficiency in areas of mathematics that they will be able to apply immediately. They will grasp the fundamentals of probability, statistics, hypothesis testing, linear algebra, linear regression, classification models, and practical calculus. Along the way they will integrate this knowledge into practical applications for real-world problems.
