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Investigate A Dataset Project Walkthrough Final-OtDZCYxbHB4.mp4 51.8 MBPart 15-Module 01-Lesson 05_Interview Practice/02. Describe your latest data project-cXluuqCVg18.mp4 44.2 MBPart 15-Module 01-Lesson 02_Practice Behavioral Questions/06. A Problem and How You Dealt With It-7IKqdW30GvQ.mp4 42.7 MBPart 16-Module 01-Lesson 06_Datasets and Questions/03. Accuracy vs. Training Set Size-9w1Yi5nMNgw.mp4 36.5 MBPart 07-Module 01-Lesson 01_What is EDA/09. Aude Explores Coordinated Migration-7ihp6ofAJG8.mp4 36.4 MBPart 15-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier-Uy89Ff49pRc.mp4 34.9 MBPart 13-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris-0ccflD9x5WU.mp4 34.1 MBPart 16-Module 01-Lesson 13_PCA/31. Eigenfaces Code-LgLYw-G4sLQ.mp4 34.0 MBPart 15-Module 02-Lesson 08_Technical Interview - Python/05. Brainstorming-LJFYhMDCCsU.mp4 33.2 MBPart 15-Module 02-Lesson 08_Technical Interview - Python/09. 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Tableau Dashboards Stories with Trina-i9xslfFp80g.mp4 19.7 MBPart 07-Module 01-Lesson 05_Explore Two Variables/25. Smoothing Conditional Means-hxk2cgdChUw.mp4 19.7 MBPart 18-Module 01-Lesson 03_Control Flow/10. For Loops-UtX0PXSUCdY.mp4 19.3 MBPart 15-Module 02-Lesson 01_Introduction and Efficiency/07. Efficiency-I-RASDPbDrI.mp4 19.3 MBPart 04-Module 01-Lesson 15_Multiple Linear Regression/05. How Does MLR Work-bvM6eUYyurA.mp4 19.3 MBPart 15-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure-Qb4o_4hCuyg.mp4 19.3 MBPart 15-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.mp4 19.3 MBPart 01-Module 01-Lesson 02_The Life of a Data Analyst/04. Lada's Money Bag Meme - Data Analysis with R-Isa_FGQrvgs.mp4 19.2 MBPart 07-Module 01-Lesson 03_Explore One Variable/21. Lada's Money Bag Meme-Isa_FGQrvgs.mp4 19.2 MBPart 18-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.mp4 19.2 MBPart 14-Module 03-Lesson 01_Craft Your Cover Letter/05. Writing the Body-aK9Qnv3a6Wg.mp4 19.1 MBPart 16-Module 01-Lesson 13_PCA/17. Composite Features-spVqFnSvlIU.mp4 19.0 MBPart 04-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.mp4 18.9 MBPart 16-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.mp4 18.5 MBPart 16-Module 01-Lesson 13_PCA/29. When to Use PCA-hJZHcmJBk1o.mp4 18.4 MBPart 04-Module 01-Lesson 15_Multiple Linear Regression/17. Multicollinearity VIFs-wbtrXMusDe8.mp4 18.4 MBPart 13-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.mp4 18.2 MBPart 18-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.mp4 18.2 MBPart 16-Module 01-Lesson 06_Datasets and Questions/04. Downloading Enron Data-TgkBAtaTqJk.mp4 18.2 MBPart 16-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-4GBJk6R0pb4.mp4 18.2 MBPart 04-Module 01-Lesson 15_Multiple Linear Regression/22. Interactions Higher Order Terms-gMHwogzqPOk.mp4 18.1 MBPart 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables/11. Subquery Solution Video-Y6S3S0LsMrw.mp4 18.1 MBPart 04-Module 01-Lesson 15_Multiple Linear Regression/06. Interpreting Multiplie Linear Regression Coefficients-qRD3OVX8UMM.mp4 18.1 MBPart 18-Module 01-Lesson 02_Data Types and Operators/13. Strings-ySZDrs-nNqg.mp4 18.1 MBPart 18-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.mp4 17.8 MBPart 16-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-krV6r7HxmZU.mp4 17.8 MBPart 04-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.mp4 17.7 MBPart 18-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.mp4 17.6 MBPart 16-Module 01-Lesson 12_Feature Selection/15. Regularization-l9V5tlIWTvs.mp4 17.6 MBPart 15-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.mp4 17.5 MBPart 14-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!-BH1KY63YfAM.mp4 17.5 MBPart 16-Module 01-Lesson 11_Text Learning/06. Bag of Words in Sklearn-aCdg-d_476Y.mp4 17.5 MBPart 13-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.mp4 17.4 MBPart 15-Module 02-Lesson 03_Searching and Sorting/11. Efficiency of Merge Sort-HKiK5Y-YSkk.mp4 17.3 MBPart 10-Module 01-Lesson 01_Congratulations & Next Steps/03. Creating Customer Segmentation Arvato Project-VCChvqoK6Go.mp4 17.2 MBPart 01-Module 01-Lesson 02_The Life of a Data Analyst/01. Sparta Science-MkjoaUmdOXc.mp4 17.1 MBPart 04-Module 01-Lesson 15_Multiple Linear Regression/08. Dummy Variables--QTgDd-fZuA.mp4 17.0 MBPart 15-Module 01-Lesson 05_Interview Practice/05. 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SVM Gamma Parameter-m2a2K4lprQw.mp4 16.3 MBPart 18-Module 01-Lesson 04_Functions/02. Defining Functions-IP_tJYhynbc.mp4 16.2 MBPart 16-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5DvUOwA7xhU.mp4 16.2 MBPart 18-Module 01-Lesson 02_Data Types and Operators/08. Números inteiros e floats-MiJ1vfWp-Ts.mp4 16.2 MBPart 18-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.mp4 16.1 MBPart 07-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.mp4 16.1 MBPart 07-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows-5ZbjUEg4a1g.mp4 16.1 MBPart 16-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-9JfaMZcSlQA.mp4 16.0 MBPart 15-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.mp4 16.0 MBPart 16-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.mp4 15.9 MBPart 08-Module 04-Lesson 01_Cleaning Data/17. Flashforward-rfMu3f9O9hQ.mp4 15.9 MBPart 18-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.mp4 15.8 MBPart 15-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.mp4 15.7 MBPart 04-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.mp4 15.7 MBPart 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/07. Finding the First Link-_bPdJBJtNqo.mp4 15.7 MBPart 16-Module 01-Lesson 10_Feature Scaling/11. MinMax Scaler in sklearn-lgoh5R05YM0.mp4 15.6 MBPart 15-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.mp4 15.4 MBPart 16-Module 01-Lesson 01_Welcome to Machine Learning/01. Introduction-ICKBWIkfeJ8.mp4 15.3 MBPart 15-Module 02-Lesson 03_Searching and Sorting/10. Merge Sort-K916wfSzKxE.mp4 15.3 MBPart 04-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.mp4 15.3 MBPart 16-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.mp4 15.3 MBPart 07-Module 01-Lesson 01_What is EDA/02. Data is Ubiquitous-YbVuN2KOlt4.mp4 15.3 MBPart 07-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-w6CLWh1dLCU.mp4 15.2 MBPart 07-Module 01-Lesson 02_R Basics/07. RStudio Layout-FDSmlIBy7ko.mp4 15.1 MBPart 04-Module 01-Lesson 15_Multiple Linear Regression/15. Potential Problems-lGwB6YRThbI.mp4 15.1 MBPart 15-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.mp4 15.1 MBPart 14-Module 03-Lesson 01_Craft Your Cover Letter/04. Writing Your Introduction-5S5PH73WLLY.mp4 15.1 MBPart 15-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.mp4 15.0 MBPart 07-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.mp4 14.9 MBPart 15-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.mp4 14.7 MBPart 16-Module 01-Lesson 07_Regressions/19. Extracting Information from sklearn-zDIRQE_oxfk.mp4 14.6 MBPart 08-Module 03-Lesson 01_Assessing Data/09. Quality Visual Assessment 1 -XfKc5PtJ7cc.mp4 14.6 MBPart 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study/02. Beautiful Soup Demonstration-dk7ESZXLnk4.mp4 14.5 MBPart 04-Module 01-Lesson 15_Multiple Linear Regression/02. Multiple Linear Regression-rvYZp99nj6c.mp4 14.5 MBPart 01-Module 01-Lesson 02_The Life of a Data Analyst/02. Interview with a Data Scientist-kNnFA5hxI2Q.mp4 14.4 MBPart 14-Module 01-Lesson 01_Conduct a Job Search/03. Target Your Application to An Employer-X9JBzbrkcvs.mp4 14.4 MBPart 08-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Clinical Trial Data-R-HT78SPxpE.mp4 14.3 MBPart 08-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Clinical Trial Data -R-HT78SPxpE.mp4 14.3 MBPart 07-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.mp4 14.1 MBPart 16-Module 01-Lesson 07_Regressions/27. Problem with Minimizing Absolute Errors-U46D7oEijlI.mp4 14.0 MBPart 16-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.mp4 14.0 MBPart 04-Module 01-Lesson 15_Multiple Linear Regression/11. Dummy Variable Interpretation-TxP_TD0kbOo.mp4 14.0 MBPart 16-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.mp4 14.0 MBPart 18-Module 01-Lesson 02_Data Types and Operators/25. L2 06 Lists Methods V1-tz2Ja1Eaeqo.mp4 14.0 MBPart 16-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.mp4 13.9 MBPart 18-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.mp4 13.9 MBPart 16-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.mp4 13.9 MBPart 14-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.mp4 13.9 MBPart 14-Module 02-Lesson 02_Refine Your Career Change Resume/02. 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