[UdemyCourseDownloader] The Data Science Course 2019 Complete Data Science Bootcamp

11. Statistics - Practical Example Descriptive Statistics/1. Practical Example Descriptive Statistics.mp4

33. Part 5 Mathematics/16. Why is Linear Algebra Useful.mp4

05. The Field of Data Science - Popular Data Science Techniques/1. Techniques for Working with Traditional Data.mp4

03. The Field of Data Science - Connecting the Data Science Disciplines/1. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.mp4

05. The Field of Data Science - Popular Data Science Techniques/15. Types of Machine Learning.mp4

05. The Field of Data Science - Popular Data Science Techniques/10. Techniques for Working with Traditional Methods.mp4

46. Software Integration/5. Taking a Closer Look at APIs.mp4

15. Statistics - Hypothesis Testing/4. Rejection Region and Significance Level.mp4

02. The Field of Data Science - The Various Data Science Disciplines/7. Continuing with BI, ML, and AI.mp4

46. Software Integration/3. What are Data Connectivity, APIs, and Endpoints.mp4

06. The Field of Data Science - Popular Data Science Tools/1. Necessary Programming Languages and Software Used in Data Science.mp4

44. Deep Learning - Business Case Example/4. Business Case Preprocessing.mp4

14. Statistics - Practical Example Inferential Statistics/1. Practical Example Inferential Statistics.mp4

05. The Field of Data Science - Popular Data Science Techniques/13. Machine Learning (ML) Techniques.mp4

15. Statistics - Hypothesis Testing/1. Null vs Alternative Hypothesis.mp4

05. The Field of Data Science - Popular Data Science Techniques/7. Business Intelligence (BI) Techniques.mp4

44. Deep Learning - Business Case Example/1. Business Case Getting acquainted with the dataset.mp4

29. Advanced Statistical Methods - Logistic Regression/3. Logistic vs Logit Function.mp4

02. The Field of Data Science - The Various Data Science Disciplines/1. Data Science and Business Buzzwords Why are there so many.mp4

04. The Field of Data Science - The Benefits of Each Discipline/1. The Reason behind these Disciplines.mp4

48. Case Study - Preprocessing the 'Absenteeism_data'/11. Obtaining Dummies from a Single Feature.mp4

13. Statistics - Inferential Statistics Confidence Intervals/3. Confidence Intervals; Population Variance Known; z-score.mp4

44. Deep Learning - Business Case Example/6. Creating a Data Provider.mp4

05. The Field of Data Science - Popular Data Science Techniques/4. Techniques for Working with Big Data.mp4

17. Part 3 Introduction to Python/3. Why Python.mp4

48. Case Study - Preprocessing the 'Absenteeism_data'/16. Classifying the Various Reasons for Absence.mp4

31. Advanced Statistical Methods - K-Means Clustering/13. How is Clustering Useful.mp4

08. The Field of Data Science - Debunking Common Misconceptions/1. Debunking Common Misconceptions.mp4

46. Software Integration/9. Software Integration - Explained.mp4

10. Statistics - Descriptive Statistics/1. Types of Data.mp4

30. Advanced Statistical Methods - Cluster Analysis/2. Some Examples of Clusters.mp4

13. Statistics - Inferential Statistics Confidence Intervals/12. Confidence intervals. Two means. Dependent samples.mp4

16. Statistics - Practical Example Hypothesis Testing/1. Practical Example Hypothesis Testing.mp4

46. Software Integration/1. What are Data, Servers, Clients, Requests, and Responses.mp4

02. The Field of Data Science - The Various Data Science Disciplines/9. A Breakdown of our Data Science Infographic.mp4

02. The Field of Data Science - The Various Data Science Disciplines/5. Business Analytics, Data Analytics, and Data Science An Introduction.mp4

12. Statistics - Inferential Statistics Fundamentals/9. Central Limit Theorem.mp4

43. Deep Learning - Classifying on the MNIST Dataset/9. MNIST Results and Testing.mp4

01. Part 1 Introduction/2. What Does the Course Cover.mp4

48. Case Study - Preprocessing the 'Absenteeism_data'/3. Checking the Content of the Data Set.mp4

48. Case Study - Preprocessing the 'Absenteeism_data'/7. Dropping a Column from a DataFrame in Python.mp4

12. Statistics - Inferential Statistics Fundamentals/2. What is a Distribution.mp4

36. Deep Learning - How to Build a Neural Network from Scratch with NumPy/4. Basic NN Example (Part 4).mp4

46. Software Integration/7. Communication between Software Products through Text Files.mp4

38. Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks/3. Digging into a Deep Net.mp4

51. Case Study - Analyzing the Predicted Outputs in Tableau/4. Analyzing Reasons vs Probability in Tableau.mp4

13. Statistics - Inferential Statistics Confidence Intervals/10. Margin of Error.mp4

45. Deep Learning - Conclusion/3. An overview of CNNs.mp4

17. Part 3 Introduction to Python/1. Introduction to Programming.mp4

09. Part 2 Statistics/1. Population and Sample.mp4