PadhAI-Foundations of Data Science Course

This article serves as the index page for the articles corresponding to different modules of the Foundations of Data Science course.

1. Foundations of Data Science
2. Statistical and Algorithmic Modeling
3. Why is Data Science so popular today?
4. Are AI and Data Science related?
5. Engineering data science systems
6. CRISP-DM
7. Statistics
8. Statistics continued
9. Descriptive Statistics — Different types of data
10. How to describe Qualitative Data?
11. How to describe Quantitative Data?
12. Histogram
13. Typical trends in Histogram
14. Uses of Histograms in ML
15. Stem and leaf plot
16. How to describe the relationship between variables?
17. Measures of centrality and spread
18. Characteristics of measures of centrality and sensitivity of measures of centrality to outliers
19. Measures of Centrality for different types of distributions
20. Computing measures of centrality from a histogram
21. Measures of Spread — Percentiles
22. Alternative ways of computing percentiles
23. Frequently used percentiles and effect of transformations on percentiles
24. Measures of spread
25. NumPy
26. High dimensional array and Creating NumPy array
27. Indexing NumPy arrays
28. Operations on NumPy array
29. Pandas
30. Data Visualisation
31. Styling Tabulation
32. Distribution of Data — Histogram
33. Box Plot
34. Distribution of a categorical variable — bar plot
35. Joint distribution of two variables
36. Swarm Plot
37. The need for counting and probability theory
38. Multiplication principle
39. Subtraction Principle
40. Collections
41. Collections with repetitions
42. The element of chance
43. Set Theory
44. Experiment and Sample Space
45. Axioms, Properties of the Probability function
46. Designing probability function as a relative frequency
47. Designing probability functions for experiments for which all outcomes are equally likely
48. Conditional Probability
49. Chain rule of probability
50. Total probability theorem
51. Baye’s theorem
52. Independent Events
53. Random variable
54. Probability mass function
55. Discrete distributions
56. Bernoulli distribution
57. Binomial distribution
58. Geometric Distribution
59. Uniform distribution
60. Expectation
61. The function of a random variable
62. The variance of a random variable
63. Continuous Random variable
64. Experimental studies
65. Statistics: Basic Terminology

References: PadhAI