About Course

Data Science Course: Statistics and Machine Learning Specialization – FREE!

Boost your data science career with the **Statistics and Machine Learning Specialization** from **Johns Hopkins University**, now available **completely free** on Theetay. This specialization builds on the “Data Science: Foundations using R Specialization” course, diving deeper into **statistical inference, regression models, machine learning, and data product development**.

Through five engaging courses, you’ll learn how to analyze data, build predictive models, and develop data products. This specialization is perfect for **data scientists, aspiring data scientists, and anyone interested in data analysis**. By the end, you’ll be equipped to tackle real-world data challenges and demonstrate your mastery with a certificate upon completion.

Get **free access** to this Data Science Specialization from **Johns Hopkins University** and thousands of other **top-rated online courses** from platforms like **Udemy, Udacity, Coursera, MasterClass, NearPeer,** and more, all on Theetay. Start your data science journey today! This course is a great option for anyone looking to learn **machine learning, data analysis, R programming, statistical modeling, and data product development**.

Course Content

01. statistical-inference
new topic

0005 002_welcome-to-statistical-inference_instructions.html

00:00
A Message from the Professor
0006 003_some-introductory-comments_courses.git

00:00
0008 004_pre-course-survey_instructions.html

00:00
0010 005_syllabus_JHSPH-StudentReferencing_handbook.pdf

00:00
0013 006_course-book-statistical-inference-for-data-science_instructions.html

00:00
0015 007_data-science-specialization-community-site_instructions.html

00:00
0016 008_homework-problems_hw1.html

00:00
0021 001_probability_instructions.html

00:00
0025 002_02-01-introduction-to-probability.mp4

00:00
0029 003_02-02-probability-mass-functions.mp4

00:00
0033 004_02-03-probability-density-functions.mp4

00:00
0034 001_conditional-probability_instructions.html

00:00
0038 002_03-01-conditional-probability.mp4

00:00
0042 003_03-02-bayes-rule.mp4

00:00
0046 004_03-03-independence.mp4

00:00
0047 001_expected-values_instructions.html

00:00
0051 002_04-01-expected-values.mp4

00:00
0055 003_04-02-expected-values-simple-examples.mp4

00:00
0059 004_04-03-expected-values-for-pdfs.mp4

00:00
0060 001_practical-r-exercises-in-swirl-1_instructions.html

00:00
0065 002_05-01-introduction-to-variability.mp4

00:00
0069 003_05-02-variance-simulation-examples.mp4

00:00
0073 004_05-03-standard-error-of-the-mean.mp4

00:00
0077 005_05-04-variance-data-example.mp4

00:00
0078 001_distributions_instructions.html

00:00
0082 002_06-01-binomial-distrubtion.mp4

00:00
0086 003_06-02-normal-distribution.mp4

00:00
0090 004_06-03-poisson.mp4

00:00
0091 001_asymptotics_instructions.html

00:00
0095 002_07-01-asymptotics-and-lln.mp4

00:00
0099 003_07-02-asymptotics-and-the-clt.mp4

00:00
0103 004_07-03-asymptotics-and-confidence-intervals.mp4

00:00
0104 001_practical-r-exercises-in-swirl-part-2_instructions.html

00:00
0109 002_08-01-t-confidence-intervals.mp4

00:00
0113 003_08-02-t-confidence-intervals-example.mp4

00:00
0117 004_08-03-independent-group-t-intervals.mp4

00:00
0121 005_08-04-a-note-on-unequal-variance.mp4

00:00
0122 001_hypothesis-testing_instructions.html

00:00
0126 002_09-01-hypothesis-testing.mp4

00:00
0130 003_09-02-example-of-choosing-a-rejection-region.mp4

00:00
0134 004_09-03-t-tests.mp4

00:00
0138 005_09-04-two-group-testing.mp4

00:00
0139 001_p-values_instructions.html

00:00
0143 002_10-01-pvalues.mp4

00:00
0147 003_10-02-pvalue-further-examples.mp4

00:00
0148 001_knitr_instructions.html

00:00
0151 002_just-enough-knitr-to-do-the-project.mp4

00:00
0152 001_practical-r-exercises-in-swirl-part-3_instructions.html

00:00
0157 002_11-01-power.mp4

00:00
0161 003_11-02-calculating-power.mp4

00:00
0165 004_11-03-notes-on-power.mp4

00:00
0169 005_11-04-t-test-power.mp4

00:00
0173 001_12-01-multiple-comparisons.mp4

00:00
0178 002_13-01-bootstrapping.mp4

00:00
0182 003_13-02-bootstrapping-example.mp4

00:00
0186 004_13-03-notes-on-the-bootstrap.mp4

00:00
0190 005_13-04-permutation-tests.mp4

00:00
0191 001_practical-r-exercises-in-swirl-part-4_instructions.html

00:00
Section Quiz

02. regression-models
new topic

0004 002_book-regression-models-for-data-science-in-r_instructions.html

00:00
0006 003_syllabus_JHSPH-ReferencingHandbook.pdf

00:00
0007 004_pre-course-survey_instructions.html

00:00
0009 005_data-science-specialization-community-site_instructions.html

00:00
0010 006_where-to-get-more-advanced-material_instructions.html

00:00
0011 001_regression_instructions.html

00:00
0015 002_introduction-to-regression.mp4

00:00
0019 003_introduction-basic-least-squares.mp4

00:00
0020 004_technical-details_instructions.html

00:00
0024 005_technical-details-skip-if-you-d-like.mp4

00:00
0028 006_introductory-data-example.mp4

00:00
0029 001_least-squares_instructions.html

00:00
0033 002_notation-and-background.mp4

00:00
0037 003_linear-least-squares.mp4

00:00
0041 004_linear-least-squares-coding-example.mp4

00:00
0045 005_technical-details-skip-if-you-d-like.mp4

00:00
0046 001_regression-to-the-mean_instructions.html

00:00
0049 002_regression-to-the-mean.mp4

00:00
0050 001_practical-r-exercises-in-swirl-part-1_instructions.html

00:00
0055 002_statistical-linear-regression-models.mp4

00:00
0059 003_interpreting-coefficients.mp4

00:00
0063 004_linear-regression-for-prediction.mp4

00:00
0064 001_residuals_instructions.html

00:00
0068 002_residuals.mp4

00:00
0072 003_residuals-coding-example.mp4

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0076 004_residual-variance.mp4

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0077 001_inference-in-regression_instructions.html

00:00
0081 002_inference-in-regression.mp4

00:00
0085 003_coding-example.mp4

00:00
0089 004_prediction.mp4

00:00
0090 001_looking-ahead-to-the-project_instructions.html

00:00
0093 002_really-really-quick-intro-to-knitr.mp4

00:00
0094 001_practical-r-exercises-in-swirl-part-2_instructions.html

00:00
0099 002_multivariable-regression-part-i.mp4

00:00
0103 003_multivariable-regression-part-ii.mp4

00:00
0107 004_multivariable-regression-continued.mp4

00:00
0111 001_multivariable-regression-examples-part-i.mp4

00:00
0115 002_multivariable-regression-examples-part-ii.mp4

00:00
0119 003_multivariable-regression-examples-part-iii.mp4

00:00
0123 004_multivariable-regression-examples-part-iv.mp4

00:00
0124 001_adjustment_instructions.html

00:00
0128 002_adjustment-examples.mp4

00:00
0129 001_residuals_instructions.html

00:00
0133 002_residuals-and-diagnostics-part-i.mp4

00:00
0136 003_residuals-and-diagnostics-part-ii.mp4

00:00
0139 004_residuals-and-diagnostics-part-iii.mp4

00:00
0140 001_model-selection_instructions.html

00:00
0144 002_model-selection-part-i.mp4

00:00
0148 003_model-selection-part-ii.mp4

00:00
0152 004_model-selection-part-iii.mp4

00:00
0153 001_practical-r-exercises-in-swirl-part-3_instructions.html

00:00
0158 002_glms.mp4

00:00
0159 001_logistic-regression_instructions.html

00:00
0163 002_logistic-regression-part-i.mp4

00:00
0167 003_logistic-regression-part-ii.mp4

00:00
0171 004_logistic-regression-part-iii.mp4

00:00
0172 001_count-data_instructions.html

00:00
0175 002_poisson-regression-part-i.mp4

00:00
0178 003_poisson-regression-part-ii.mp4

00:00
0179 001_mishmash_instructions.html

00:00
0183 002_hodgepodge.mp4

00:00
0184 001_practical-r-exercises-in-swirl-part-4_instructions.html

00:00
Section Quiz

03. practical-machine-learning
new topic

0002 002_a-note-of-explanation_instructions.html

00:00
0003 003_syllabus_instructions.html

00:00
0004 004_pre-course-survey_instructions.html

00:00
0008 005_prediction-motivation.mp4

00:00
0012 006_what-is-prediction.mp4

00:00
0016 007_relative-importance-of-steps.mp4

00:00
0020 008_in-and-out-of-sample-errors.mp4

00:00
0024 009_prediction-study-design.mp4

00:00
0028 010_types-of-errors.mp4

00:00
0031 011_receiver-operating-characteristic.mp4

00:00
0035 012_cross-validation.mp4

00:00
0039 013_what-data-should-you-use.mp4

00:00
0043 001_caret-package.mp4

00:00
0047 002_data-slicing.mp4

00:00
0051 003_training-options.mp4

00:00
0055 004_plotting-predictors.mp4

00:00
0059 005_basic-preprocessing.mp4

00:00
0063 006_covariate-creation.mp4

00:00
0067 007_preprocessing-with-principal-components-analysis.mp4

00:00
0071 008_predicting-with-regression.mp4

00:00
0075 009_predicting-with-regression-multiple-covariates.mp4

00:00
0079 001_predicting-with-trees.mp4

00:00
0083 002_bagging.mp4

00:00
0087 003_random-forests.mp4

00:00
0091 004_boosting.mp4

00:00
0095 005_model-based-prediction.mp4

00:00
0099 001_regularized-regression.mp4

00:00
0103 002_combining-predictors.mp4

00:00
0107 003_forecasting.mp4

00:00
0111 004_unsupervised-prediction.mp4

00:00
0113 001_course-project-instructions-read-first_pml-testing.csv

00:00
Section Quiz

04. data-products
new topic

0047 004_shiny-2-4.mp4

00:00
0050 005_shiny-2-5.mp4

00:00
0053 006_shiny-2-6.mp4

00:00
0056 001_shiny-gadgets-1-1.mp4

00:00
0059 002_shiny-gadgets-1-2.mp4

00:00
0062 003_shiny-gadgets-1-3.mp4

00:00
0065 001_googlevis-1-1.mp4

00:00
0068 002_googlevis-1-2.mp4

00:00
0071 001_plotly-1-1.mp4

00:00
0074 002_plotly-1-2.mp4

00:00
0077 003_plotly-1-3.mp4

00:00
0080 004_plotly-1-4.mp4

00:00
0083 005_plotly-1-5.mp4

00:00
0086 006_plotly-1-6.mp4

00:00
0089 007_plotly-1-7.mp4

00:00
0092 008_plotly-1-8.mp4

00:00
0095 001_r-markdown-1-1.mp4

00:00
0098 002_r-markdown-1-2.mp4

00:00
0101 003_r-markdown-1-3.mp4

00:00
0104 004_r-markdown-1-4.mp4

00:00
0107 005_r-markdown-1-5.mp4

00:00
0110 006_r-markdown-1-6.mp4

00:00
0115 001_leaflet-1-1.mp4

00:00
0118 002_leaflet-1-2.mp4

00:00
0121 003_leaflet-1-3.mp4

00:00
0124 004_leaflet-1-4.mp4

00:00
0127 005_leaflet-1-5.mp4

00:00
0130 006_leaflet-1-6.mp4

00:00
0131 001_r-packages_instructions.html

00:00
0134 002_r-packages-part-1.mp4

00:00
0137 003_r-packages-part-2.mp4

00:00
0140 004_building-r-packages-demo.mp4

00:00
0143 005_r-classes-and-methods-part-1.mp4

00:00
0146 006_r-classes-and-methods-part-2.mp4

00:00
0149 001_swirl-1-1.mp4

00:00
0152 002_swirl-1-2.mp4

00:00
0155 003_swirl-1-3.mp4

00:00
0156 001_post-course-survey_instructions.html

00:00
0004 002_a-note-of-explanation_instructions.html

00:00
0005 003_syllabus_instructions.html

00:00
0007 004_welcome_Developing_Data_Products.git

00:00
0010 005_book-developing-data-products-in-r_book.pdf

00:00
0013 006_community-site_community.pdf

00:00
0016 007_r-and-rstudio-links-tutorials_instructions.html

00:00
0017 001_shiny_instructions.html

00:00
0019 002_shinyapps-io-project_instructions.html

00:00
0023 003_shiny-1-1.mp4

00:00
0026 004_shiny-1-2.mp4

00:00
0029 005_shiny-1-3.mp4

00:00
0032 006_shiny-1-4.mp4

00:00
0035 007_shiny-1-5.mp4

00:00
0038 001_shiny-2-1.mp4

00:00
0041 002_shiny-2-2.mp4

00:00
0044 003_shiny-2-3.mp4

00:00
Section Quiz

05. data-science-project
new topic

0004 002_a-note-of-explanation_instructions.html

00:00
0005 003_project-overview_instructions.html

00:00
0010 004_welcome-from-swiftkey.mp4

00:00
0013 005_you-are-a-data-scientist-now.mp4

00:00
0016 006_syllabus_Referencing_handbook.pdf

00:00
0019 001_introduction-to-task-0-understanding-the-problem.mp4

00:00
0020 002_task-0-understanding-the-problem_Coursera-SwiftKey.zip

00:00
0023 003_about-the-corpora_instructions.html

00:00
0026 001_introduction-to-task-1-getting-and-cleaning-the-data.mp4

00:00
0027 002_task-1-getting-and-cleaning-the-data_instructions.html

00:00
0030 003_regular-expressions-part-1-optional.mp4

00:00
0033 004_regular-expressions-part-2-optional.mp4

00:00
0036 001_introduction-to-task-2-exploratory-data-analysis.mp4

00:00
0037 002_task-2-exploratory-data-analysis_instructions.html

00:00
0040 001_introduction-to-task-3-modeling.mp4

00:00
0041 002_task-3-modeling_instructions.html

00:00
0044 001_introduction-to-task-4-prediction-model.mp4

00:00
0045 002_task-4-prediction-model_instructions.html

00:00
0048 001_introduction-to-task-5-creative-exploration.mp4

00:00
0049 002_task-5-creative-exploration_instructions.html

00:00
0052 001_introduction-to-task-6-data-product.mp4

00:00
0053 002_task-6-data-product_instructions.html

00:00
0056 001_introduction-to-task-7-slide-deck.mp4

00:00
0057 002_task-7-slide-deck_instructions.html

00:00
0060 001_congratulations.mp4

00:00
Section Quiz

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About Course

Data Science Course: Statistics and Machine Learning Specialization – FREE!

What Will You Learn?

Course Content

01. statistical-inference new topic

0005 002_welcome-to-statistical-inference_instructions.html

A Message from the Professor

0006 003_some-introductory-comments_courses.git

0008 004_pre-course-survey_instructions.html

0010 005_syllabus_JHSPH-StudentReferencing_handbook.pdf

0013 006_course-book-statistical-inference-for-data-science_instructions.html

0015 007_data-science-specialization-community-site_instructions.html

0016 008_homework-problems_hw1.html

0021 001_probability_instructions.html

0025 002_02-01-introduction-to-probability.mp4

0029 003_02-02-probability-mass-functions.mp4

0033 004_02-03-probability-density-functions.mp4

0034 001_conditional-probability_instructions.html

0038 002_03-01-conditional-probability.mp4

0042 003_03-02-bayes-rule.mp4

0046 004_03-03-independence.mp4

0047 001_expected-values_instructions.html

0051 002_04-01-expected-values.mp4

0055 003_04-02-expected-values-simple-examples.mp4

0059 004_04-03-expected-values-for-pdfs.mp4

0060 001_practical-r-exercises-in-swirl-1_instructions.html

0065 002_05-01-introduction-to-variability.mp4

0069 003_05-02-variance-simulation-examples.mp4

0073 004_05-03-standard-error-of-the-mean.mp4

0077 005_05-04-variance-data-example.mp4

0078 001_distributions_instructions.html

0082 002_06-01-binomial-distrubtion.mp4

0086 003_06-02-normal-distribution.mp4

0090 004_06-03-poisson.mp4

0091 001_asymptotics_instructions.html

0095 002_07-01-asymptotics-and-lln.mp4

0099 003_07-02-asymptotics-and-the-clt.mp4

0103 004_07-03-asymptotics-and-confidence-intervals.mp4

0104 001_practical-r-exercises-in-swirl-part-2_instructions.html

0109 002_08-01-t-confidence-intervals.mp4

0113 003_08-02-t-confidence-intervals-example.mp4

0117 004_08-03-independent-group-t-intervals.mp4

0121 005_08-04-a-note-on-unequal-variance.mp4

0122 001_hypothesis-testing_instructions.html

0126 002_09-01-hypothesis-testing.mp4

0130 003_09-02-example-of-choosing-a-rejection-region.mp4

0134 004_09-03-t-tests.mp4

0138 005_09-04-two-group-testing.mp4

0139 001_p-values_instructions.html

0143 002_10-01-pvalues.mp4

0147 003_10-02-pvalue-further-examples.mp4

0148 001_knitr_instructions.html

0151 002_just-enough-knitr-to-do-the-project.mp4

0152 001_practical-r-exercises-in-swirl-part-3_instructions.html

0157 002_11-01-power.mp4

0161 003_11-02-calculating-power.mp4

0165 004_11-03-notes-on-power.mp4

0169 005_11-04-t-test-power.mp4

0173 001_12-01-multiple-comparisons.mp4

0178 002_13-01-bootstrapping.mp4

0182 003_13-02-bootstrapping-example.mp4

0186 004_13-03-notes-on-the-bootstrap.mp4

0190 005_13-04-permutation-tests.mp4

0191 001_practical-r-exercises-in-swirl-part-4_instructions.html

Section Quiz

02. regression-models new topic

0004 002_book-regression-models-for-data-science-in-r_instructions.html

0006 003_syllabus_JHSPH-ReferencingHandbook.pdf

0007 004_pre-course-survey_instructions.html

0009 005_data-science-specialization-community-site_instructions.html

0010 006_where-to-get-more-advanced-material_instructions.html

0011 001_regression_instructions.html

0015 002_introduction-to-regression.mp4

0019 003_introduction-basic-least-squares.mp4

0020 004_technical-details_instructions.html

0024 005_technical-details-skip-if-you-d-like.mp4

0028 006_introductory-data-example.mp4

0029 001_least-squares_instructions.html

0033 002_notation-and-background.mp4

0037 003_linear-least-squares.mp4

01. statistical-inference
new topic

02. regression-models
new topic

03. practical-machine-learning
new topic