Learn Python for Data Science from Scratch -with 10 Projects

سرفصل های دوره

Unleash Data Potential: Master Python for Data Science, Visualization, and Machine Learning from Ground Zero to Pro!

1 - Introduction to Python and the Jupyter Notebook

1 - Introduction

2 - Python-for-data-science-course.docx

2 - What is Python

3 - Overview of the Jupyter Notebook

4 - The Print Function

5 - Basic Arithmetic Functions

6 - Variables

7 - Project 1

8 - Project 1 Solution

2 - Data Types and Structures in Python

9 - Strings

10 - Strings Numerical Data Types

11 - Lists

12 - Tuples

13 - Dictionaries

14 - Project 2

15 - Project 2 Solution

3 - Control Flow in Python

16 - Overview of Control Flow

17 - Conditional Statements

18 - For Loops

19 - While loops

20 - Project 3

21 - Project 3 Solution

4 - Functions and Modules in Python

22 - Functions

23 - Lambda Functions

24 - Modules

25 - Project 4

26 - Project 4 Solution

5 - Introduction to Numpy

27 - Introduction to Numpy

28 - Creating arrays in Numpy

29 - Indexing and Slicing Arrays

30 - Copy and View in Numpy

31 - Shape and reshaping arrays

32 - Basic Operations in Numpy Arrays

33 - Data Analytics operations in Numpy

34 - Project 5

35 - Project 5 Solution

6 - Introduction to Pandas

36 - Introduction to Pandas

37 - Reading in Files in Pandas

38 - Looking at data in the dataframe

39 - Accessing filtering and Sorting data

40 - Indexing loc and iloc in Pandas

41 - Groupby and aggregate functions

42 - Merge Join and Concatenate

43 - Data Cleaning in Pandas 1

44 - Data Cleaning in Pandas 2

45 - Data Visualization in Pandas

46 - Project 6

47 - Project 6 Solution

7 - Introduction to Matplotlib

48 - Introduction to Matplotli

48 - Python-for-data-science-course.docx

49 - Basic Plots in Matplotlib

50 - Project 7

51 - Project 7 Solution

8 - Basic Machine Learning with ScikitLearn

52 - Introduction to Machine Learning

52 - Python-for-data-science-course.docx

53 - Supervised Unsupervised Learning

54 - Machine Learning Techniques

55 - Introduction to ScikitLearn

9 - Regression Models with ScikitLearn

56 - Github repo of resources.txt

56 - Introduction to Regression Models

57 - Building your First Linear Regression Model 1

58 - Building your First Linear Regression Model 2

59 - Building your First Linear Regression Model 3

60 - Building your First Linear Regression Model 4

61 - Project 8

62 - Project 8 Solution

10 - Classification Models with ScikitLearn

63 - Github repo of resources.txt

63 - Introduction to Classification Models

64 - Building your First Classification Model 1

65 - Building your First Classification Model 2

66 - Building your First Classification Model 3

67 - Building your First Classification Model 4

68 - Project 9

69 - Project 9 Solution

11 - Clustering Models with ScikitLearn

70 - Github repo for resources.txt

70 - Introduction to Clustering Models

71 - Building your First Clustering Model 1

72 - Building your First Clustering Model 2

73 - Project 10

74 - Project 10 Solution

12 - Wrap up

75 - Wrap Up

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تولید کننده: Udemy