Search result for Applied statistics Online Courses & Certifications
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Statistical Inference and Modeling for High-throughput Experiments
by Rafael Irizarry , Michael Love- 0.0
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4 Weeks
In this course you’ll learn various statistics topics including multiple testing problem, error rates, error rate controlling procedures, false discovery rates, q-values and exploratory data analysis. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. 1x: Statistics and R for the Life Sciences...
$149
Statistics & Applied Data Science - Business Data Analysis
by Mahmoud Ali- 3.8
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9 hours on-demand video
Data Science Statistics : Data Science from Scratch for Beginners : Data Analysis Techniques, Method Course : Analytics 270+ video lectures include real life practical projects and examples for people need to learn statistics for Machine learning and Data Analysis . In no time with simple and easy way you will learn and love statistics ....
$12.99
Introduction to Applied Biostatistics: Statistics for Medical Research
by Ayumi Shintani- 0.0
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6 Weeks
This Applied Biostatistics course provides an introduction to important topics in medical statistical concepts and reasoning....
$49
Optimizing Machine Learning Performance
by Anna Koop- 4.6
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Approx. 12 hours to complete
This course synthesizes everything your have learned in the applied machine learning specialization. You will understand and define procedures to operationalize and maintain your applied machine learning model. This is the final course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute (Amii)....
Statistics Made Easy by Example for Analytics/ data science
by Gopal Prasad Malakar- 4.4
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10.5 hours on-demand video
Learn the statistics in a simple and interesting way Know the business scenarios, where it is applied See the demonstration of important concepts (simulations) in MS Excel Practice it in MS Excel to cement the learning Get confidence to answer questions on statistics Be ready to do more advance course like logistic regression etc....
$12.99
Machine Learning Algorithms: Supervised Learning Tip to Tail
by Anna Koop- 4.7
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Approx. 9 hours to complete
Learners will also gain skills to contrast the practical consequences of different data preparation steps and describe common production issues in applied ML. You should have a basic understanding of linear algebra (vector notation) and statistics (probability distributions and mean/median/mode)....
Six Sigma Tools for Analyze
by Christina Scherrer, PhD , David Cook, PhD , Gregory Wiles, PhD , Bill Bailey, PhD- 4.7
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Approx. 8 hours to complete
This course will outline useful measure and analysis phase tools and will give you an overview of statistics as they are related to the Six Sigma process. The statistics module will provide you with an overview of the concepts and you will be given multiple example problems to see how to apply these concepts....
Managing, Describing, and Analyzing Data
by Wendy Martin- 4.4
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Approx. 17 hours to complete
You will describe data both graphically and numerically using descriptive statistics and R software. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. Calculate descriptive statistics and create graphical representations using R software...
Data for Machine Learning
by Anna Koop- 4.4
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Approx. 12 hours to complete
This course is all about data and how it is critical to the success of your applied machine learning model. You should have a basic understanding of linear algebra (vector notation) and statistics (probability distributions and mean/median/mode). This is the third course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute....
Linear regression in R for Data Scientists
by Francisco Juretig- 3
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7 hours on-demand video
Linear regression is the primary workhorse in statistics and data science. The goal is to provide the student the computational knowledge necessary to work in the industry, and do applied research, using lineal modelling techniques. Some basic knowledge in statistics and R is recommended, but not necessary....
$9.99
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