Advanced Mathematics Course for the Data Engineering Track

SAR 508
SAR 254

اشترك الآن

Duration
01:46:39 hours

Access Time
Lifetime

Language
Arabic

Resources
(1)

1121

SAR 508
SAR 254

About the instructor

بطاقة تفاصيل الخدمة

اسم الخدمة: Advanced Mathematics Course for the Data Engineering Track
التصنيف: Engineering Specialties
المدة: 01:46:39 hours
عدد المحاضرات: 18
لغة المحتوى: Arabic
الرسوم: ~~SAR 508~~
SAR 254
الشهادة: شهادة إتمام معتمدة
قناة تقديم الخدمة: إلكترونياً عبر المنصة
المستفيدون: الأفراد والجهات

الخطوات

إنشاء حساب أو تسجيل الدخولسجّل بياناتك الأساسية (الاسم، البريد الإلكتروني، رقم الجوال) وفعّل الحساب.
الاشتراك في المنصةاختر خطة الاشتراك الشهرية أو السنوية وأكمل الدفع الإلكتروني.
متابعة المحتوى التدريبيشاهد المحاضرات وأنجز الاختبارات حتى اكتمال نسبة الإنجاز.
الحصول على الشهادةتُصدر شهادة الإتمام إلكترونياً ويمكن التحقق منها عبر خدمة التحقق من الشهادة.

المستندات المطلوبة

لا تتطلب الخدمة أي مستندات ورقية.
بريد إلكتروني فعّال ورقم جوال لتفعيل الحساب.
الاسم الكامل كما في الهوية ليُطبع على الشهادة.

Objectives of Advanced Mathematics Course for the Data Engineering Track

This program aims to provide a comprehensive understanding of the fundamental concepts in probability and statistics, which form the backbone of machine learning and data science. It helps participants build a solid framework that enables them to clearly interpret the results of algorithms and understand the reasons behind using certain methods. It also empowers them to adjust techniques when desired results are not achieved, thus improving prediction accuracy and making informed decisions. The program covers key topics such as joint probability, conditional probability, Bayes' Theorem, random variables, normal distribution, variance, and linear regression. By the end of the program, participants will be able to practically apply these concepts to analyze data and build machine learning models effectively.

You Will Learn

In this program, you will learn the fundamentals of probability and statistics and how to apply them in machine learning and data science. You will explore how to calculate conditional probabilities and use Bayes' Theorem to analyze data more accurately. You will gain a deep understanding of random variables, normal distribution, and linear regression, which will help you interpret results and make data-driven decisions. Additionally, you will learn how to use p-values to test hypotheses and perform statistical data analysis. By the end of the program, you will be able to apply these concepts to build machine learning models and improve algorithm performance using solid mathematical and statistical foundations.

Targeted Students

This program is aimed at students and professionals who seek to enhance their skills in machine learning and data science. This includes university students in fields such as computer science, mathematics, statistics, and engineering, as well as researchers in the fields of artificial intelligence and data analysis. It also targets professionals working in data analysis, machine learning algorithm developers, and technical project managers who want to make data-driven decisions. The program is also suitable for programmers and data scientists who wish to improve the accuracy of their models and understand the mathematical and statistical foundations underlying machine learning algorithms.