Top 10 Data Science YouTube Channels to Follow in 2024

In the ever-evolving field of data science, staying updated with the latest trends, tools, and techniques is crucial. YouTube has become a valuable resource for learning, offering a wealth of tutorials, lectures, and insights from industry experts. Here are the top 10 data science YouTube channels to follow in 2024, providing high-quality content for both beginners and seasoned professionals.

In the world of data science where this brilliantly demanding profession is developing it is essential to know what is happening in the industry at the moment. This mega video-sharing site has evolved into more than just a source of entertainment but also as an educational platform where one can find numerous tutorial videos, lectures, and insights from professionals. So, below are the lists of the 10 best Data Science YouTube Channels that would be best for the year 2024: For beginners to advanced learners.

The Kaggle channel on YouTube is a haven to data scientists; where the platform hosts tutorials, competitions, and even focused discussions on data science projects.

– Rich & comprehensive resources on machine learning and data analysis.

– Effects of key factors regarding strategies from success in Kaggle competition.

– We wanted to capture top data scientists’ insights through interviews.

– This report is based on the subject “Intro to Machine Learning” and the topic focuses on the basic concepts of machine learning

Popular Videos:

– “Pandas DataFrame Basics”

– “Deep Learning Explained”

Much of StatQuest’s content is presented in a simple and animated manner, which makes it easy for viewers to understand the presented material, which is based on the mathematics of statistics and various machine learning algorithms.

– Translations of originally short articles into lengthy articles, which are easier to comprehend and apply statistical methods.

– They have also used diagrams and samples to help the students understand different points better.

– They have designed the exercises for a range of students from novices to the highly advanced learners.

– “Neural Networks StatQuest”

– “PCA in Python”

– “Random Forests”

Data School is founded by Kevin Markham that present tutorials and practical guidance regarding to data science and machine learning.

– Detailed guides and lessons on pandas, scikit-learn, and other pieces of Python software.

– Consequently, easy tips and tricks on data manipulation and modeling are described below:

– In general, one can see that there are no unnecessary words in the text and the meaning is stated quite clearly.

– Python Data Science: Pandas are one of the most popular and powerful tools for data analysis in Python today and in this lesson, you’ll learn to use it.

– In chapter 2: Basics of sci-kit learn, let’s learn the fundamentals of machine learning.

– An internet post: “Tips for Pandas DataFrame Users”.

As an influencer with a specialization in data science, Krish Naik’s channel features topics such as machine learning deep learning, AI, and more.

– Step-by-step recipes on data science and artificial intelligence tips.

– Real-life surveys, research and developmental undertakings Real-time project and current issue scenarios.

– Reciprocal accurate and detailed information regarding current activities and new inventions within the sector.

– “Deep Learning Projects”

– “Machine Learning Algorithms”

– There are a lot of questions in the Data Science Interview Questions list that can be found online or in books.

His channel, Siraj Raval, is also quite popular due to the exciting, funny, and informative videos that are shared regarding data science, machine learning as well as Artificial Intelligence.

– Good work: offers fresh and entertaining solutions to mastering difficult lessons.

– Examples and exercises involving real-life practices and coding tasks.

– Presenting the latest developments in the application of Artificial Intelligence.

As such, various strategies can be used to apply the knowledge of data science in the year 2024:

– “Neural Networks Demystified”

– “AI for Beginners”

Simplilearn offers detailed courses and guidance on the most essential of data science, AI, and big data.

– High-quality educational content.

– This leaves detailed comprehensive tutorials and certification courses as the most appropriate method of training the RailRoad employees and technicians.

– This is perhaps the reason why the current source covers the fundaments and also other advanced topics of the relevant area.

– This is a full course in data science where learners explore the basic statistics and programming tools, use algorithms to make predictions and classifications, work with data sets, and much more.

– “Artificial Intelligence Tutorial”

– “Big Data Hadoop Tutorial ”

Few guys have created YouTube channels that have a lot of material on programming, Python, data science and software development, and one of them is Corey Schafer.

– For concise Python tutorials.

– Further, actual examples and real implementation scenarios

– This is because data science libraries and tools are required to apply the principles of data science.

– “Python Pandas Tutorial”

– “Matplotlib Tutorial”

– “Freshers can learn ‘Python for Data Science’ program easily. ”

The book under discussion by Brandon Foltz is devoted to statistics and data analysis and includes rather comprehensive explanations and examples that allow the reader to grasp the topic.

– Exploring statistics in detail, focusing on both its concepts and methods.

– Practicality and problem-solving: Observe how the aspects of the narrative discussed are useful and functional in solving problems in life.

– This paper is useful for classwork and reference for any person who has embarked on a project that requires the use of a statistical test.

– “Statistics for Beginners”

– “Linear Regression Analysis”

– “Hypothesis Testing”

Tech with Tim discusses various topics mainly programming with Python, data science, and machine learning.

– Beginner-friendly tutorials.

– Rubber tough bumpers and whisker coloring changes Coding challenges.

– You will often find articles on the most popular data science tools and frameworks.

– Below, we can start to look at the release of one of the most famous Python packages, namely the Machine Learning Library:

– These tools can be used for a “data science project from scratch” where the idea both as a concept and a digital vision happens to be viable for a data scientist to work on.

– “Intro to TensorFlow”

Originally, a lecture series by Jeremy Howard, the Data Professor provides lessons, guest lectures, and conversations about data science, machine learning, and biostatistics.

– Courses related to Programming such as Python programming, R programming along with the Data visualization course.

– Shifting the attention to the trends and using empirical studies.

– “Data Science 101”

– “Bioinformatics with Python”

– To the best of the popular genres of using R, is arranging a set of data in a certain way or else visualizing data.