Description
Mathematics for Data Science 101. This course teaches the basic mathematical concepts needed to enter the fields of data science and machine learning in a clear and visual way. This course is specifically designed to address the common challenge of understanding complex formulas and keeping learners motivated. In this course, critical mathematical concepts are presented not through heavy theoretical texts, but with the help of clear infographics and simplified steps. This image-based approach makes the material easy and stress-free for all levels—from complete beginners to retraining experts. The main difference of this course is its emphasis on practical aspects, so that the application of each mathematical concept to real-world data science tasks, such as modeling and analysis, is clearly demonstrated. The course structure does not require any advanced mathematical background, and its ultimate goal is to develop a deep understanding of the fundamentals as well as to build confidence to apply this knowledge to practical projects and complex data analysis. This method significantly increases the speed of learning and retention of concepts.
What you will learn
- Understanding the basic and fundamental mathematical concepts that are essential to entering the world of Data Science.
- Learning the principles of statistics, including the concepts of mean, median, mode, variance, and standard deviation.
- Mastering the basics of probability and how to apply these concepts in various machine learning models.
- Learn the essentials of linear algebra, including working with vectors, matrices, and understanding linear transformations.
- Teaching the basics of differential and integral calculus to optimize artificial intelligence (AI) algorithms.
- Understanding how these mathematical concepts directly relate to application models in real data-driven projects.
This course is suitable for people who:
- Beginners who are interested in the field of data science but find mathematics a challenging and difficult subject.
- Students preparing to start a career in machine learning, artificial intelligence, or data analytics.
- Professionals who are changing careers into data science and need a quick, practical refresher course in math.
- Self-taught learners who prefer to understand concepts visually and pictorially rather than simply memorizing formulas.
Mathematics for Data Science 101 Course Details
- Publisher: Udemy
- Instructor: Haris Jafri
- Training level: Beginner to advanced
- Training duration: 7 hours and 17 minutes
- Number of lessons: 44 lessons
Course syllabus
Prerequisites for Mathematics for Data Science 101
- No Prerequisites
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: None
Quality: 1080p
Changes:
Version 2025/12 compared to 2025/9 has increased by 4 hours and 56 minutes in duration.
Download link
Downloadly
Rapidgator
File(s) password: www.downloadly.ir
File size
1.35 GB
