Search result for Probability and Statistics Online Courses & Certifications
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Guided Tour of Machine Learning in Finance
by Igor Halperin- 3.8
Approx. 24 hours to complete
This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Experience with Python (including numpy, pandas, and IPython/Jupyter notebooks), linear algebra, basic probability theory and basic calculus is necessary to complete assignments in this course. Artificial Intelligence and Machine Learning, Part I...
Unsupervised Learning
by Mark J Grover , Miguel Maldonado- 4.9
Approx. 9 hours to complete
Explain the curse of dimensionality, and how it makes clustering difficult with many features To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics. Introduction to Unsupervised Learning and K Means...
Unsupervised Machine Learning
by Mark J Grover , Miguel Maldonado- 4.8
Approx. 9 hours to complete
Explain the curse of dimensionality, and how it makes clustering difficult with many features To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics. Introduction to Unsupervised Learning and K Means...
Data Analysis Bootcamp™ 21 Real World Case Studies
by Rajeev D. Ratan- 4.4
15 hours on-demand video
Data Analysts aim to discover how data can be used to answer questions and solve problems through the use of technology. You'll learn how to create awesome Dashboards, tell stories with Data and Visualizations, make Predictions, Analyze experiments and more! Data Manipulations and Wrangling with Pandas Probability and Statistics Python, Pandas & Data Analytics and Data Science Case Studies:...
$13.99
R Programming - Data Science using R
by Data Training Campus- 4.1
7 hours on-demand video
Through this course one will be learning about basic R functions, special numerical values, array and matrix, repository and packages, installing a package, how to calculate variance, co-variance, cumulative frequency, learn about statistics, probability and distribution, random examples, discrete example and many as such concept about R. People interested in statistics and data sciences...
$11.99
Mindware: Critical Thinking for the Information Age
by Richard E. Nisbett- 4.8
Approx. 13 hours to complete
They require in addition the ability to collect, analyze and think about data. Why you should never keep a stock that’s going down in hopes that it will go back up and prevent you from losing any of your initial investment. Welcome Message and Course Principles from Professor Nisbett Lesson 1: Statistics...
Data Analysis Excel for Beginners: Statistical Data Analysis
by Kawser Ahmed- 0.0
7 hours on-demand video
The explanations are clear and concise. I learned a lot from this course and shouldn't have any difficulty applying the concepts to future projects. But analyzing data requires that you know some basic statistics and probability theories. Most of the statistics and probability concepts that are necessary to analyze data effectively are covered in your undergraduate level courses....
$12.99
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Supervised Learning: Classification
by Mark J Grover , Miguel Maldonado- 4.9
Approx. 11 hours to complete
You will learn how to train predictive models to classify categorical outcomes and how to use error metrics to compare across different models. Confusion Matrix, Accuracy, Specificity, Precision, and Recall Boosting and Stacking Boosting and Stacking Demo Upsampling and Downsampling Modeling Approaches: Weighting and Stratified Sampling Modeling Approaches: Random and Synthetic Oversampling...
Supervised Machine Learning: Classification
by Mark J Grover , Miguel Maldonado- 4.9
Approx. 11 hours to complete
You will learn how to train predictive models to classify categorical outcomes and how to use error metrics to compare across different models. Confusion Matrix, Accuracy, Specificity, Precision, and Recall Boosting and Stacking Boosting and Stacking Demo Upsampling and Downsampling Modeling Approaches: Weighting and Stratified Sampling Modeling Approaches: Random and Synthetic Oversampling...
Data Analysis for Social Scientists
by Esther Duflo , Sara Fisher Ellison- 0.0
11 Weeks
Learn methods for harnessing and analyzing data to answer questions of cultural, social, economic, and policy interest. MicroMasters in Statistics and Data Science (SDS). This statistics and data analysis course will introduce you to the essential notions of probability and statistics. Intuition behind probability and statistical analysis How to summarize and describe data...