Course Content
Udemy – The Data Science Course: Complete Data Science Bootcamp 2025
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01. Part 1 Introduction
08:41
02. The Field of Data Science – The Various Data Science Disciplines
39:01
03. The Field of Data Science – Connecting the Data Science Disciplines
07:20
04. The Field of Data Science – The Benefits of Each Discipline
04:45
05. The Field of Data Science – Popular Data Science Techniques
01:00:02
06. The Field of Data Science – Popular Data Science Tools
05:52
07. The Field of Data Science – Careers in Data Science
03:30
08. The Field of Data Science – Debunking Common Misconceptions
04:11
09. Part 2 Probability
23:05
10. Probability – Combinatorics
43:00
11. Probability – Bayesian Inference
54:42
12. Probability – Distributions
01:17:17
13. Probability – Probability in Other Fields
18:52
14. Part 3 Statistics
04:03
15. Statistics – Descriptive Statistics
47:33
16. Statistics – Practical Example Descriptive Statistics
16:16
17. Statistics – Inferential Statistics Fundamentals
21:54
18. Statistics – Inferential Statistics Confidence Intervals
44:15
19. Statistics – Practical Example Inferential Statistics
10:07
20. Statistics – Hypothesis Testing
46:55
21. Statistics – Practical Example Hypothesis Testing
07:17
22. Part 4 Introduction to Python
26:49
23. Python – Variables and Data Types
17:22
24. Python – Basic Python Syntax
11:33
25. Python – Other Python Operators
07:47
26. Python – Conditional Statements
13:35
27. Python – Python Functions
18:37
28. Python – Sequences
34:52
29. Python – Iterations
32:33
30. Python – Advanced Python Tools
12:58
31. Part 5 Advanced Statistical Methods in Python
01:28
32. Advanced Statistical Methods – Linear Regression with StatsModels
40:22
33. Advanced Statistical Methods – Multiple Linear Regression with StatsModels
42:18
34. Advanced Statistical Methods – Linear Regression with sklearn
53:56
35. Advanced Statistical Methods – Practical Example Linear Regression
37:13
36. Advanced Statistical Methods – Logistic Regression
40:37
37. Advanced Statistical Methods – Cluster Analysis
14:06
38. Advanced Statistical Methods – K-Means Clustering
48:50
39. Advanced Statistical Methods – Other Types of Clustering
13:36
40. ChatGPT for Data Science
01:03:35
41. Case Study Train a Naive Bayes Classifier with ChatGPT for Sentiment Analysis
46:45
42. Part 6 Mathematics
51:05
43. Part 7 Deep Learning
03:08
44. Deep Learning – Introduction to Neural Networks
42:44
45. Deep Learning – How to Build a Neural Network from Scratch with NumPy
19:47
46. Deep Learning – TensorFlow 2.0 Introduction
27:26
47. Deep Learning – Digging Deeper into NNs Introducing Deep Neural Networks
25:25
48. Deep Learning – Overfitting
19:39
49. Deep Learning – Initialization
08:06
50. Deep Learning – Digging into Gradient Descent and Learning Rate Schedules
20:43
51. Deep Learning – Preprocessing
14:35
52. Deep Learning – Classifying on the MNIST Dataset
35:09
53. Deep Learning – Business Case Example
38:42
54. Deep Learning – Conclusion
17:08
55. Appendix Deep Learning – TensorFlow 1 Introduction
26:17
56. Appendix Deep Learning – TensorFlow 1 Classifying on the MNIST Dataset
36:34
57. Appendix Deep Learning – TensorFlow 1 Business Case
50:31
58. Software Integration
29:41
59. Case Study – What’s Next in the Course
10:15
60. Case Study – Preprocessing the ‘Absenteeism_data’
01:22:48
61. Case Study – Applying Machine Learning to Create the ‘absenteeism_module’
01:05:45
62. Case Study – Loading the ‘absenteeism_module’
10:15
63. Case Study – Analyzing the Predicted Outputs in Tableau
22:41
64. Appendix – Additional Python Tools
46:04
65. Appendix – pandas Fundamentals
58:49
66. Bonus Lecture
Udemy – The Data Science Course: Complete Data Science Bootcamp 2025

    00:00 – 1. Object Oriented Programming

    05:00 – 3. Modules and Packages

    06:06 – 5. What is the Standard Library

    08:53 – 7. Importing Modules in Python

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