Description
Applied Math for Data Science course. As data becomes more available, there is a growing demand for talent who can analyze and make sense of it. This makes applied mathematics all the more important as it helps to derive insights from data. However, mathematics encompasses many subjects, and it can be difficult to discern which ones are applicable and relevant to a data science career. Knowing these essential mathematical topics is key to integrating knowledge in data science, statistics, and machine learning. In this course, learners carefully review a list of math topics to begin mastering areas of mathematics that they can immediately apply. They will understand the principles of probability, statistics, hypothesis testing, linear algebra, linear regression, classification models, and practical computing. Along the way, they will integrate this knowledge into applications for real-world problems.
What you will learn in Applied Math for Data Science course
- Gain a basic understanding of calculus, linear algebra, probability, statistics, and supervised machine learning.
- Apply the fundamentals of math in Python using standard math libraries such as NumPy and SymPy.
- Integrate multiple applied math disciplines such as linear algebra and calculus to perform tasks such as gradient descent.
This course is suitable for people who
- You are an emerging data scientist who wants to build a foundational knowledge of fundamental mathematical concepts and how they apply to probability, statistics, and machine learning.
- You are a programmer who uses data science and machine learning libraries and want to understand the mathematical principles and probability behind them.
- You manage a data science team and want a basic understanding of the techniques used in this field.
Specifications of Applied Math for Data Science course
- Publisher: Oreilly
- teacher: Thomas Nield
- Training level: beginner to advanced
- Training duration: 5 hours and 41 minutes
Course headings
Applied Math for Data Science course prerequisites
- Beginner knowledge of Python (if-then conditionals, for loops, lists and other collections)
Course images
Sample video of the course
Installation guide
After Extract, view with your favorite Player.
English subtitle
Quality: 1080p
download link
File(s) password: www.downloadly.ir
Size
1.3 GB
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