2023 Master class on Data Science using Python A-Z™ : for ML

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Surendra Varma Pericherla

5:50:28

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1 - BONUS Python Crash Course

1 - Variables in Python.mp4

04:35

2 - Conditionals If statement.mp4

04:48

3 - Example for If statement.mp4

03:36

4 - If else statement.mp4

02:02

5 - Example of If else statement.mp4

01:51

6 - Nested If statement.mp4

03:31

7 - Example for Nested If statement.mp4

03:51

8 - Elif statement.mp4

03:40

9 - Example for Elif statement.mp4

02:24

10 - While loop.mp4

06:52

11 - Example of while loop.mp4

03:16

12 - For Loop.mp4

07:36

13 - Example of For Loop.mp4

01:55

14 - Break Continue Statement.mp4

02:37

15 - Introduction to containers.mp4

17:31

16 - Creating and accessing lists in Python.mp4

07:06

17 - List indexing and slicing.mp4

09:05

18 - Working with List methods.mp4

31:05

19 - Working with operators on lists.mp4

03:37

20 - List Comprehension.mp4

03:57

21 - Tuple definition.mp4

03:35

22 - Tuples.mp4

03:08

23 - Tuple Indexing Slicing.mp4

18:15

24 - Manipulating Tuples.mp4

04:55

25 - Unpacking Tuples.mp4

01:09

26 - Sets.mp4

03:48

27 - Dictionaries.mp4

05:32

28 - Basics of dictionary.mp4

20:13

29 - Accessing dictionary.mp4

07:16

30 - len str type functions in dictionary.mp4

04:15

31 - Functions in python.mp4

04:28

32 - Example program1 on Functions.mp4

06:20

33 - Example program2 on functions.mp4

03:21

2 - Data Handling using Numpy

34 - Introduction to modules in python.mp4

02:28

35 - Creating Displaying 1D array.mp4

01:12

36 - Understanding 1D array Index.mp4

04:17

37 - Creating Array of 0s and Array of 1s.mp4

01:48

38 - Sorting elements in 1D array.mp4

01:17

39 - Slicing a 1D array.mp4

10:29

40 - Mathematical Operations on Array.mp4

04:22

41 - Searching an element in a Array.mp4

06:34

42 - Filtering an array.mp4

04:20

43 - Checking whether given array is empty or not.mp4

02:54

44 - Creating Displaying 2D array.mp4

01:03

45 - ndim Attribute.mp4

02:19

46 - Size Attribute.mp4

02:30

47 - Shape and reshape of array.mp4

03:17

48 - Creating an Identity Matrix.mp4

02:19

49 - arange.mp4

02:43

50 - linspace.mp4

01:29

51 - Random array.mp4

01:22

52 - Random matrix.mp4

01:17

53 - Creating a diagonal matrix.mp4

01:04

54 - Flatten a Matrix.mp4

02:10

55 - Computing Trace of a Matrix.mp4

03:12

56 - Finding Transpose of a Matrix.mp4

04:19

57 - Negative indexing to access elements in a 2D array.mp4

03:27

3 - Data Handling using Pandas

58 - Introduction to Pandas.mp4

04:46

59 - Working with series in Pandas.mp4

08:07

60 - Combining series with Numpy.mp4

05:35

61 - Finding number of elements in a series.mp4

01:30

62 - Computing mean max and min in a series.mp4

03:38

63 - Sorting a Series.mp4

02:49

64 - Displaying Unique values in a Series.mp4

02:29

65 - Summary of series statistics.mp4

02:12

4 - Data Visualization using Matplotlib in Python

66 - Introduction to Matplotlib.mp4

02:57

67 - Creating Line Graph.mp4

05:30

68 - Creating Bar Graph.mp4

02:20

69 - Creating Scatter Graph.mp4

01:07

70 - Creating Histogram Graph.mp4

02:01

71 - Creating Pie Chart.mp4

02:24

72 - Creating 3D Plot.mp4

01:23

73 - Creating 3D Line graph.mp4

00:34

5 - Data Visualization using Seaborn in Python

74 - Understanding a sample Dataset Downloadable.mp4

02:32

74 - tips.csv

75 - Introduction to Seaborn.mp4

02:58

76 - Swarm Plot.mp4

04:07

77 - Violin Plot.mp4

01:48

78 - Facet Grids.mp4

04:31

79 - Heatmap.mp4

01:48

6 - Problem Solving Assignments

7 - Projects

Description

Python NumPy, Pandas, Matplotlib and Seaborn for Data Analysis, Data Science and ML. Pre-machine learning Analysis.

What You'll Learn?

Students will learn how to create and manipulate arrays, perform mathematical operations on arrays, and use functions such as sorting, searching, and statistics
Students will learn how to create and manipulate Series and Data Frames.
Students will learn how to create plots and charts, customize the appearance of visualizations, and add annotations and labels.
NumPy, Pandas, and Matplotlib will typically teach students how to use these tools to analyze and visualize data.

Who is this for?

Students who want to learn data science using Python.

Anyone with an interest in data science and machine learning

More details

Description
Welcome to 2023 Master class on Data Science using Python.
NumPy is a leading scientific computing library in Python while Pandas is for data manipulation and analysis. Also, learn to use Matplotlib for data visualization. Whether you are trying to go into Data Science, dive into machine learning, or deep learning, NumPy and Pandas are the top Modules in Python you should understand to make the journey smooth for you. In this course, we are going to start from the basics of Python NumPy and Pandas to the advanced NumPy and Pandas. This course will give you a solid understanding of NumPy, Pandas, and their functions.
At the end of the course, you should be able to write complex arrays for real-life projects, manipulate and analyze real-world data using Pandas.

WHO IS THIS COURSE FOR?
âˆš This course is for you if you want to master the in-and-out of NumPy, Pandas, and data visualization.
âˆš This course is for you if you want to build real-world applications using NumPy or Panda and visualize them with Matplotlib and Seaborn.
âˆš This course is for you if you want to learn NumPy, Pandas, Matplotlib and Seaborn for the first time or get a deeper knowledge of NumPy and Pandas to increase your productivity with deep and Machine learning.
âˆš This course is for you if you are coming from other programming languages and want to learn Python NumPy and Pandas fast and know it really well.
âˆš This course is for you if you are tired of NumPy, Pandas, Matplotlib and Seaborn courses that are too brief, too simple, or too complicated.
âˆš This course is for you if you have to get the prerequisite knowledge to understanding Data Science and Machine Learning using NumPy and Pandas.
âˆš This course is for you if you want to learn NumPy and Pandas by doing exciting real-life challenges that will distinguish you from the crowd.
âˆš This course is for you if plan to pass an interview soon.
Who this course is for:
Students who want to learn data science using Python.
Anyone with an interest in data science and machine learning

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The name of the instructor is Surendra varma.He is a winner of BEST TEACHER award.He is a winner of Young Achiever award.He holds Bachelors degree in Computer Science & Masters degree in Computer science. He cracked toughest exams in computer science such as GATE & UGC-NET with flying colors. Also, he is a university topper during masters.He is currently Pursuing PhD from world's most reputed university Indian Institute of Sciences(IISC), Bangalore.He worked with various EdTech companies in India including Great Learning. He always received best feedback from his students. He has 14+ Years of experience in Teaching/research/Industry. He worked in various roles like Software Engineer, Associate professor, Researcher, Technical Trainer, Senior Technical Trainer, Technical head & Academic head. He has trained over 1,00,000 students in his career. His former students are currently working in MNC's such as Amazon, Infosys, Wipro, TCS, CTS, Accenture etc.He has given Guest lectures in top Universities/ colleges in India like IIIT’s, SRM University, VIT etc.He has given online training to students of various countries such as India, USA, Canada, UAE, Australia, UK, Germany etc.He ranked in Top 5% in Cracking the Amazon Coding Assessment.In Udemy, his students are scattered in 161 different countries."He loves education and educating others. His goal is to Provide quality of education to the students across the world."

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