Data Science Full Course 2026 | Data Science Tutorial | Learn Data Science In 24 Hours | Simplilearn

Simplilearn ยท Beginner ยท๐Ÿ“Š Data Analytics & Business Intelligence ยท1w ago
๐Ÿ”ฅData Scientist Masters Program (Discount Code - YTBE15) - https://www.simplilearn.com/data-science-course?utm_campaign=qlzRMwC883o&utm_medium=Description&utm_source=Youtube ๐Ÿ”ฅMicrosoft Azure - Data Analyst Course - https://www.simplilearn.com/in/data-analyst-course?utm_campaign=qlzRMwC883o&utm_medium=Description&utm_source=Youtube ๐Ÿ”ฅMicrosoft Azure - Data Analyst Course - https://www.simplilearn.com/in/data-analyst-course?utm_campaign=qlzRMwC883o&utm_medium=Description&utm_source=Youtube Following are the topics covered in Data Science Full Course 2026: 00:00:00 - Introduction to Data Science Excel Full Course 2026 00:02:18 - Introduction to Data Science 00:13:29 - Probability and Statistics 00:57:10 - Data Preprocessing and EDA 01:26:10 - Machine Learning Fundamentals 01:50:00 - Data Visualization, Deployment, and Ethics 02:14:30 - Model Deployment and Operationalization 02:49:21 - Data Science With Python 04:12:18 - Applied Data Science With Python 04:15:25 - What is Data science 04:26:20 - Data science process and applications 04:39:20 - Python libraries and plotting overview 04:43:19 - Environment setup: Anaconda and Colab 04:48:22 - NumPy intro: arrays and purpose 04:57:34 - Why NumPy is fast: timing demo 05:15:45 - Arrays vs lists; nd-array basics 05:28:27 - 0D/1D/2D/3D arrays and attributes 06:13:19 - Reshape arrays: change dimensions 06:28:40 - Transpose arrays and use cases 06:48:43 - NumPy arithmetic operations 07:39:20 - String arrays with numpy.char 07:51:31 - arange and linspace explained 08:13:34 - Random numbers and distributions 08:51:07 - Indexing and slicing arrays 09:19:20 - Pandas intro and Series basics 10:13:42 - Series analysis and missing data 10:28:18 - Sorting, alignment, and map 11:37:30 - DataFrames: create and display 12:11:11 - SQL For Data Science Tutorial 2026 13:12:51 - Numpy Tutorial for Data Science 16:18:26 - Pandas For Data Science 16:57:25 - Statistics For Data Science 17:20:12 - Seaborn Library In Python 17:38:47 - Types
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Chapters (34)

Introduction to Data Science Excel Full Course 2026
2:18 Introduction to Data Science
13:29 Probability and Statistics
57:10 Data Preprocessing and EDA
1:26:10 Machine Learning Fundamentals
1:50:00 Data Visualization, Deployment, and Ethics
2:14:30 Model Deployment and Operationalization
2:49:21 Data Science With Python
4:12:18 Applied Data Science With Python
4:15:25 What is Data science
4:26:20 Data science process and applications
4:39:20 Python libraries and plotting overview
4:43:19 Environment setup: Anaconda and Colab
4:48:22 NumPy intro: arrays and purpose
4:57:34 Why NumPy is fast: timing demo
5:15:45 Arrays vs lists; nd-array basics
5:28:27 0D/1D/2D/3D arrays and attributes
6:13:19 Reshape arrays: change dimensions
6:28:40 Transpose arrays and use cases
6:48:43 NumPy arithmetic operations
7:39:20 String arrays with numpy.char
7:51:31 arange and linspace explained
8:13:34 Random numbers and distributions
8:51:07 Indexing and slicing arrays
9:19:20 Pandas intro and Series basics
10:13:42 Series analysis and missing data
10:28:18 Sorting, alignment, and map
11:37:30 DataFrames: create and display
12:11:11 SQL For Data Science Tutorial 2026
13:12:51 Numpy Tutorial for Data Science
16:18:26 Pandas For Data Science
16:57:25 Statistics For Data Science
17:20:12 Seaborn Library In Python
17:38:47 Types
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