Top YouTube playlist for Data Science and AI that you must check

Being into the machine learning and data science field for about two years now, I have realized that a lot of students fall victim to the belief that buying-in to expensive certifications is necessary for bagging a good job in the data science sector. Nothing could be farther from the truth. The reality is that certifications have very little value in today's day and age. An individual can become a machine learning engineer or a data scientist by learning from a ton of resources that are freely available, up on the internet. 

What could be a better resource than YouTube? In this article, I am presenting the reader with a list of the top resources on YouTube, I came across to learn programming, machine learning, and data science. These resources have been divided into appropriate sections. I hope you all like it and find it useful.

Data Scientist is the one who is best programmer among all the statistician and best statistician among all the programmers

Programming Languages:

 

Having knowledge of various programming tools is mandatory for a data scientist, to name a few Python, R, SQL are considered as essential tools that a data scientist should have knowledge of. I have mentioned, some good resources that I have personally went through to learn these skills from a beginner's perspective. In the end, I have also mentioned one playlist for GitHub which is considered as the most important tool for a Data Science Professional.

1.      Python Tutorial for Absolute Beginners by ProgrammingKnowledge {link}

2.      Python for beginners by MICROSOFT OFFICIAL {link}

3.      Python Programming Tutorials by Socratica {link}

4.      Learning Python for Data Science by Giles McMullen-Klein {link}

5.      Statistics with R by MarinStatsLectures-R Programming & Statistics {link}

6.      Data analysis in Python with pandas by Kevin Markham(Data School) {link}

7.      SQL for Data Science by Venkat, Pragim Technologies {link}

8.      Git Tutorials by Corey Schafer {link} 

Statistics:

Stats is considered as one of the primary fields in Data Science, some experts even say that Data Science has emerged from Statistics. Most of the time, you need to prove a hypothesis for statistical analysis, and for that, you just need a good knowledge of Stats. Check the following links for some of the best playlists on YourTube that I have come across.

9.      Statistics Fundamentals by StatQuest with Josh Stammer {link}

10.  Statistics by Khan Academy {link}

11.  Statistics Course for Data Science by MarinStatsLectures {link}

Machine Learning:

Let us come to one of the favorite topics Machine Learning, I have seen most of the times that people are able to explain or understand the ML Algorithm but they fail to apply them for a real problem, well I have found these playlists from some of the best Industry experts what not only explains about an ML algorithm but also explains how it can be applied to a problem, check out these playlists mentioned below.

12.  Applied Machine Learning Framework by Abhishek Thakur {link}

13.  Introduction to Machine Learning by Sudeshna Sarkar {link}

14.  Machine Learning with Python by sentdex {link}

15.  Applied Machine Learning by Andreas Mueller {link}

16.  Machine Learning by 5 Minutes Engineering {link}

17.  Machine Learning by Andrew NG, Stanford University {link}

18.  Practical Machine Learning with TensorFlow by Dr. Ashish Tendulkar {link}

Deep Learning and Neural Network:

The word "deep" in "deep learning" refers to the number of layers through which the data is transformed. Deep models are able to extract better features than shallow models and hence, extra layers help in learning the features effectively.

19.  Neural Network from scratch in Python {link}

20.  Deep Learning Lecture by Lex Fridman(MIT) {link}

21.  Deep Learning by 5 Minutes Engineering {link}

22.  Complete Deep Learning by Krish Naik {link}

Natural Language Processing & Reinforcement Learning:

Alexa, Siri, Cortana, Google Assistant these personalized virtual assistants are outcomes of extremely powerful NLP models, how feasibly they acquire our natural language as input and reply to us in a similar manner. This would surely be the most researching filed in the coming years.

23.  Fast.ai Code-First Intro to Natural Language Processing by Rachel Thomas {link}

24.  Natural Language Processing by Krish Naik {link}

25.  Reinforcement Learning by sentdex {link}

26.  Artificial Intelligence & Robotics by 5 Minutes Engineering {link}

Talks, Resources, Recommendations:

We all need inspiration on what we are working for, below are some awesome talks by some data science professionals in the Industry, also I have collated this section with some Interview questions and recommendations for the material for Data Science.

27.  Data Science & Machine Learning Real Talks by Springboard {link}

28.  Data Science Interview Questions by Krish Naik {link}

29.  Python & Data Science Book Recommendations by Bhavesh Bhatt {link}

30.  Daily News by Analytics India Magazine {link}