End to End Python Course: Start Your Python Programming Journey for Data Analysis

Starting a Python programming journey for Data Science as a beginner involves building a solid foundation in both Python and data science concepts.
Familiarize Yourself with Python Libraries for Data Science
NumPy: Learn NumPy for numerical operations and working with arrays. It’s the foundation for many other libraries.
Pandas: Master Pandas for data manipulation and analysis. Focus on DataFrames, Series, and operations like filtering, grouping, and merging data.
Matplotlib/Seaborn: Start with Matplotlib for basic data visualization, then move to Seaborn for more advanced and aesthetically pleasing plots.
Develop a Strong Understanding of Data Science Concepts
Statistics: Learn the basics of descriptive and inferential statistics, including concepts like mean, median, standard deviation, correlation, and hypothesis testing.
Probability: Understand probability theory, distributions, and Bayes' theorem, which are crucial for data science.
Table of content
0:01 - Inroduction
4:50 - Object oriented programming
10:28 - Understanding a statement
15:00 - Basic idea of a programming language
20:56 - The skills of a programmer
26:32 - Understanding some mathematical operation
31:32 - Use IDE and Website like anywhere python
36:50 - Python Syntax
42:23 - Difference between natural language and Python
47:58 - What is interpreter interpreter
53:12 - The prompt in the python
58:07 - The variable
1:02:47 - The function
1:07:31 - Indentation
1:12:08 - Debugging
1:16:31 - Extract some specific features from an image file
1:20:00 - What is neutal network
1:25:03 - Deploy machine learning model
1:29:16 - Visualization capability
1:33:23 - The network the activation function
1:37:39 - A jupyter notebook file
1:41:59 - An efficient training of Model
1:46:01 - An activation function
1:50:18 - Some prediction of the test data
1:54:12 - A neural network prefer for image classification
2:01:26 - Overfitting and underfitting situation
2:05:32 - Data preparation
2:09:31 - Irish flower dataset
2:14:00 - Supervised learning
2:20:19 - A descriptive statistic analysis
2:24:40 - Standard deviation
2:34:17 - Create a heat map
2:39:52 - Calculate the accuracy percentage of the model
2:43:29 - Type of machine learning
2:44:07 - What is deep learning
2:47:33 - What is directive generative model
2:51:16 - How to use deep neural network
2:54:47 - The super relationship between the input and output data
2:58:19 - The hidden layers deep neural networks
3:01:34 - The unsupervised learning tasks for feature learning
3:11:58 - Understanding of deep multile layers perceptions
3:19:32 - The abundance of data help the model generalize better
3:23:07 - Multi- device training
3:27:08 - What are the major deep learning Frameworks?
3:31:47 - AI vs Human Brains
3:34:45 - Two popular activation functions
3:37:51 - Adjust the weight and bias
3:41:49 - The training of deep neural networks
3:44:15 - Find the patterns and structure in the data
3:48:04 - Deep learning is common in all AI driven systems
3:50:52 - The learnable parameters of the networks
3:59:29 - What are the three popular approaches of object classification in deep learning
4:03:48 - what are the significance of deep learning
📺 Subscribe to "Getplus Mindset" to unlock a world of positive education and empower the future. 🌐✨
📺 Join Our Cources
Data Analysis: getplusmindset...
Programming: getplusmindset...
Join upcoming online Workshops: getplusmindset...
Books: getplusmindset...
👋 My Video Topics:
✨Data Analysis:
• Power BI
• MS Excel
• ChatGPT
✨Programming:
• Python
• Full Stack Development
• PHP
👋 Find my other homes on the internet -
Facebook: / getplusmindset
Linkedin: / npnath
Instagram: / npnath2024
KZbin: / @getplusmindset
🌐 The purpose of this video is to raise awareness and educate the viewers. The video presents information that is based on our knowledge and research and is intended to be accurate. However, any errors made are unintentional. If you notice any mistakes, please email us at [e-mail] with the subject "Getplus Mindset Video" so that we can take necessary action to resolve any errors or disputes amicably.

[@Radheya_80]

nice explaination sir ...better than our college lecturers

[@getplusmindset]

@@Radheya_80 Thank you for your input. Really appreciate, and keep learning .