Generative AI for Business Leaders
This condensed course is designed to equip business leaders with an essential understanding of generative artificial intelligence.
Advertising with Meta
This Pathway will throw light upon how it is imperative for individuals and businesses to employ Cybersecurity in the usage of IoT.
How Google does Machine Learning
This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning.
دوراتنا
Statistics 2 Part 2: Statistical Inference
The final part in a series of four courses which help you to master statistics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further study at undergraduate level.
- مقدم بواسطة
الإنجليزية
الاشتراك الشهري
متضمن في- الباقة الاحترافية @ AED 149 + VAT
- الباقة الإبتدائية @ AED 99 + VAT
Inferenzstatistik
This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project.
- مقدم بواسطة
التعلم الذاتي 
17 ساعات - ألماني
الاشتراك الشهري
متضمن في- الباقة الإبتدائية @ AED 99 + VAT
- الباقة الاحترافية @ AED 149 + VAT
Statistical Inference for Estimation in Data Science
This course introduces statistical inference, sampling distributions, and confidence intervals. Students will learn how to define and construct good estimators, method of moments estimation, maximum likelihood estimation, and methods of constructing confidence intervals that will extend to more general settings. This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform.
- مقدم بواسطة
- التعلم الذاتي
- 28 ساعات
- الإنجليزية
الاشتراك الشهري
متضمن في- الباقة الإبتدائية @ AED 99 + VAT
- الباقة الاحترافية @ AED 149 + VAT
Using probability distributions for real world problems in R
By the end of this project, you will learn how to apply probability distributions to solve real world problems in R, a free, open-source program that you can download. You will learn how to answer real world problems using the following probability distributions – Binomial, Poisson, Normal, Exponential and Chi-square. You will also learn the various ways of visualizing these distributions of real world problems.
- مقدم بواسطة
- التعلم الذاتي
- 2 ساعات
- الإنجليزية
مجاني
اعرف المزيد
Population Health: Responsible Data Analysis
In most areas of health, data is being used to make important decisions. As a health population manager, you will have the opportunity to use data to answer interesting questions. In this course, we will discuss data analysis from a responsible perspective, which will help you to extract useful information from data and enlarge your knowledge about specific aspects of interest of the population. First, you will learn how to obtain, safely gather, clean and explore data.
- مقدم بواسطة
- التعلم الذاتي
- 20 ساعات
- الإنجليزية
الاشتراك الشهري
متضمن في- الباقة الإبتدائية @ AED 99 + VAT
- الباقة الاحترافية @ AED 149 + VAT
Mathematical Biostatistics Boot Camp 2
Learn fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples.
- مقدم بواسطة
- التعلم الذاتي
- 12 ساعات
- الإنجليزية
الاشتراك الشهري
متضمن في- الباقة الإبتدائية @ AED 99 + VAT
- الباقة الاحترافية @ AED 149 + VAT
Data Science Foundations: Statistical Inference
This program is designed to provide the learner with a solid foundation in probability theory to prepare for the broader study of statistics. It will also introduce the learner to the fundamentals of statistics and statistical theory and will equip the learner with the skills required to perform fundamental statistical analysis of a data set in the R programming language. This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform.
- مقدم بواسطة
- التعلم الذاتي
- الإنجليزية
الاشتراك الشهري
متضمن في- الباقة الإبتدائية @ AED 99 + VAT
- الباقة الاحترافية @ AED 149 + VAT
Data Science: Statistics and Machine Learning
Build models, make inferences, and deliver interactive data products. This specialization continues and develops on the material from the Data Science: Foundations using R specialization. It covers statistical inference, regression models, machine learning, and the development of data products. In the Capstone Project, you’ll apply the skills learned by building a data product using real-world data.
- مقدم بواسطة
- التعلم الذاتي
- الإنجليزية
الاشتراك الشهري
متضمن في- الباقة الإبتدائية @ AED 99 + VAT
- الباقة الاحترافية @ AED 149 + VAT
Improving Your Statistical Questions
This course aims to help you to ask better statistical questions when performing empirical research. We will discuss how to design informative studies, both when your predictions are correct, as when your predictions are wrong. We will question norms, and reflect on how we can improve research practices to ask more interesting questions.
- مقدم بواسطة
- التعلم الذاتي
- 18 ساعات
- الإنجليزية
الاشتراك الشهري
متضمن في- الباقة الإبتدائية @ AED 99 + VAT
- الباقة الاحترافية @ AED 149 + VAT
Advanced Statistical Inference and Modelling Using R
Extend your knowledge of linear regression to the situations where the response variable is binary, a count, or categorical as well as to hierarchical experimental set-up.
- مقدم بواسطة
- التعلم الذاتي
- الإنجليزية
الاشتراك الشهري
متضمن في- الباقة الإبتدائية @ AED 99 + VAT
- الباقة الاحترافية @ AED 149 + VAT
Basics of Statistical Inference and Modelling Using R
Learn why a statistical method works, how to implement it using R and when to apply it and where to look if the particular statistical method is not applicable in the specific situation.
- مقدم بواسطة
- التعلم الذاتي
- الإنجليزية
الاشتراك الشهري
متضمن في- الباقة الاحترافية @ AED 149 + VAT
- الباقة الإبتدائية @ AED 99 + VAT
MathTrackX: Statistics
Understand fundamental concepts relating to statistical inference and how they can be applied to solve real world problems.
- مقدم بواسطة
- التعلم الذاتي
- 30
- الإنجليزية
الاشتراك الشهري
متضمن في- الباقة الاحترافية @ AED 149 + VAT
- الباقة الإبتدائية @ AED 99 + VAT
Statistical Inference and Modeling for High-throughput Experiments
A focus on the techniques commonly used to perform statistical inference on high throughput data.
- مقدم بواسطة
- التعلم الذاتي
- 12
- الإنجليزية
الاشتراك الشهري
متضمن في- الباقة الاحترافية @ AED 149 + VAT
- الباقة الإبتدائية @ AED 99 + VAT
Improving your statistical inferences
This course aims to help you to draw better statistical inferences from empirical research. First, we will discuss how to correctly interpret p-values, effect sizes, confidence intervals, Bayes Factors, and likelihood ratios, and how these statistics answer different questions you might be interested in. Then, you will learn how to design experiments where the false positive rate is controlled, and how to decide upon the sample size for your study, for example in order to achieve high statistical power.
- مقدم بواسطة
- التعلم الذاتي
- 28 ساعات
- الإنجليزية
AED 170.99 + VAT
اعرف المزيد
Data Science in Real Life
Have you ever had the perfect data science experience? The data pull went perfectly. There were no merging errors or missing data. Hypotheses were clearly defined prior to analyses. Randomization was performed for the treatment of interest. The analytic plan was outlined prior to analysis and followed exactly. The conclusions were clear and actionable decisions were obvious. Has that every happened to you? Of course not. Data analysis in real life is messy. How does one manage a team facing real data analyses? In this one-week course, we contrast the ideal with what happens in real life.
- مقدم بواسطة
- التعلم الذاتي
- 7 ساعات
- الإنجليزية
AED 170.99 + VAT
اعرف المزيد
Statistical Inference
Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance.
- مقدم بواسطة
- 54 ساعات
- الإنجليزية
AED 170.99 + VAT
اعرف المزيد
Fitting Statistical Models to Data with Python
In this course, we will expand our exploration of statistical inference techniques by focusing on the science and art of fitting statistical models to data. We will build on the concepts presented in the Statistical Inference course (Course 2) to emphasize the importance of connecting research questions to our data analysis methods.
- مقدم بواسطة
- التعلم الذاتي
- 15 ساعات
- الإنجليزية
AED 274.99 + VAT
اعرف المزيد