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Data Science with Python Course : Hands-on Data Science 2020
by Ankit Mistry- 4.3
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15.5 hours on-demand video
Welcome to Complete Ultimate course guide on Data Science and Machine learning with Python. "Good explanation, I have laready used two online tutorials on data -science and this one is more step by step, but it is good" The content of the course and the way he delivers is great. Data Science Prerequisite : Basics of Probability and statistics...
$12.99
Data Science 2021: Data Science & Machine Learning in Python
by Ankit Mistry- 4.4
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18.5 hours on-demand video
0, NLP, Statistics for Data Science, Data Analysis ! 2) Statistics Basic: Data, Levels of Measurement, Measures of Central Tendency, Population vs Sample, Probability based Sampling methods, Non Probability based Sampling method, Measures of Dispersion, Quartiles and IQR 11) Data Analysis with Numpy: NumPy Arrays, Indexing and Selection, NumPy Operations Refresh all basic statistics & Probability Concepts...
$11.99
Fitting Statistical Models to Data with Python
by Brenda Gunderson , Brady T. West , Kerby Shedden- 4.4
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Approx. 15 hours to complete
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. This course will introduce and explore various statistical modeling techniques, including linear regression, logistic regression, generalized linear models, hierarchical and mixed effects (or multilevel) models, and Bayesian inference techniques. Bayesian Approaches to Statistics and Modeling...
Probabilistic Deep Learning with TensorFlow 2
by Dr Kevin Webster- 4.7
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Approx. 53 hours to complete
Welcome to this course on Probabilistic Deep Learning with TensorFlow! This course builds on the foundational concepts and skills for TensorFlow taught in the first two courses in this specialisation, and focuses on the probabilistic approach to deep learning. The additional prerequisite knowledge required in order to be successful in this course is a solid foundation in probability and statistics....
Mindware: Critical Thinking for the Information Age
by Richard E. Nisbett- 4.8
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Approx. 13 hours to complete
They require in addition the ability to collect, analyze and think about data. This course presents basic concepts from statistics, probability, scientific methodology, cognitive psychology and cost-benefit theory and shows how they can be applied to everything from picking one product over another to critiquing media accounts of scientific research. Welcome Message and Course Principles from Professor Nisbett...
Probabilistic Graphical Models 1: Representation
by Daphne Koller- 4.6
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Approx. 67 hours to complete
Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more....
Introduction to Statistics
by Quantitative Specialists- 4.6
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2.5 hours on-demand video
Introductory Statistics as Covered in the Social, Behavioral, and Natural Sciences Probability, the Normal Curve and z-Scores - An introduction to probability is provided, along with properties of the normal distribution and how to calculate and interpret z-scores Goals/Learning Objectives: Understand beginning probability including important characteristics of the normal (Gaussian) distribution, as well as how to calculate and interpret z-scores....
$13.99
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Statistics for Data science
by Shivprasad Koirala- 4.3
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1 hour on-demand video
This course teaches Data Science with Maths statistics from basic to advanced level. I recommend start with statistics first using simple excel and the later apply the same using python and R. Chapter 4:- Spread and seeing the same visually. Lesson 4 :- The ZScore calculationChapter 16:- Probability of getting 50% above and 50% less....
$11.99
Probabilistic Graphical Models 3: Learning
by Daphne Koller- 4.6
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Approx. 66 hours to complete
These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. Following the first course, which focused on representation, and the second, which focused on inference, this course addresses the question of learning: how a PGM can be learned from a data set of examples....
Probability and Statistics IV: Confidence Intervals and Hypothesis Tests
by David Goldsman- 0.0
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4 Weeks
This course covers two important methodologies in statistics – confidence intervals and hypothesis testing. This course covers two important methodologies in statistics – confidence intervals and hypothesis testing. ” The second half the course begins by motivating hypothesis tests and how they are used. Finally, we formulate and interpret hypothesis tests for a variety of probability distributions and their parameters....
$199
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