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The world of data science is fast and ever-changing. For a data scientist, this translates to continuous learning and exploration. YouTube exists as that treasure trove of high-quality educational content around any topic.
Therefore, the following guide represents a comprehensive view of the best data science YouTube channels and videos in 2024, targeted at data science learners of all levels: from absolute beginners to seasoned professionals.
Just getting started with your data science journey? Here are some of the best data science YouTube channels that will help you level up your data science skills in 2024:
3Blue1Brown: Grant Sanderson does an extraordinary job with his animations on his channel. He explains perfectly really tricky math, linear algebra, calculus, and neural networks. You will find learning through 3Blue1Brown's interactively done content quite enjoyable even if you have never touched these topics before.
StatQuest with Josh Starmer: Josh Starmer, through this channel, expounds on all concepts in statistics in a very engaging and enlightening manner. It gives clear explanations and fun visuals to drive home the basics of statistics into the mind of a data scientist, right from hypothesis testing to p-values.
freeCodeCamp.org: This is a non–profit online organization offering an end-to-end course on Python programming. The language is very important in data science. Structured videos with hands-on exercises will teach you the relevant programming skills to manipulate and analyze data effectively.
DataCamp: DataCamp offers introductory videos covering a range of concepts in data science, including data wrangling, visualization, and machine learning. Their beginner-friendly tutorials would pretty much serve as a good starting point to get an overview of the core functionalities of data science.
Data science Dojo: The channel is only concerned with what a beginner in data science would require. Their content includes data types, the pandas and NumPy libraries, and basic techniques of data analysis.
3Blue1Brown: Essence of Linear Algebra
StatQuest: Hypothesis Testing Explained
freeCodeCamp.org: Python for Everybody Specialization
DataCamp: Introduction to Data Science in Python
Data Science Dojo: Science
Now that you have the basics, it's time to dive into the various domains of data science. Listed here are some fantastic channels to help drive your skills further:
Ken Jee: This is a channel by Ken Jee focused on practical data science applications. He gives project-based tutorials in machine learning algorithms, including Natural Language Processing and Deep Learning, teaching several real-world insights.
Krish Naik: Krish Naik's channel is similar to that of Ken Jee, with a focus on project-oriented learning. He will walk you through the construction of data science projects from scratch and teach you some problem-solving skills with the best practices.
Andreas Kretz: For those who want to take a more theoretical route, Andreas Kretz's channel makes detailed explanations concerning machine learning algorithms and data engineering. He deepens into the mathematical roots of data science techniques, thereby giving them a tight theoretical base.
Simplilearn: This channel has structured courses on the different specializations of data science, such as data visualization and business analytics. Their comprehensive video lectures give learners a general understanding of specific areas in the field of data science.
Siraj Raval: He is an Artificial Intelligence and deep learning educator who covers a myriad of topics. He explains most of the difficult concepts related to AI in very lucid language and thus reaches a larger audience through examples.
Ken Jee: Machine Learning Crash Course
Krish Naik: Build a Stock Price Prediction Model
Andreas Kretz: The Fun Way of Building Data Pipelines
Simplilearn: Data Visualization with Python
Siraj Raval: Understanding Neural Networks
The further you get in your journey associated with data science, the more prominent the requirement is to keep yourself updated with recent trends and advancements. Here are brilliant channels that will help in keeping distinction at par:
Two-Minute Papers: The channel offers a 'light' overview of the very latest research papers in most areas of AI and machine learning. This is an excellent channel to keep up-to-date on cutting-edge research and focus on new topics in the field of data science.
Sentdex: This channel by Sebastian Trautsch covers in detail all the advanced Deep Learning techniques and frameworks like TensorFlow or PyTorch. The tutorials he gives or the explanations are at a higher level, too, for experienced learners who want to explore the depths of deep learning further.
Corey Schafer: If you are into data engineering and creating robust data pipelines, then the channel by Corey Schafer is very good. He covers topics such as Apache Spark, Apache Airflow, and cloud platforms like AWS, with hands-on guidance in building scalable data infrastructure.
Joma Tech: He provides detailed explanations of various algorithms of machine learning and its applications in computer vision and natural language processing. Hence, it will be very relevant to those advanced learners who want to focus more on these areas of data science.
CS Dojo: This is a channel by Michael Nielsen that goes deep into the theoretical parts of computer science and especially machine learning. It specializes in picking up complex subjects on information theory, reinforcement learning, or deep learning architectures and serving them to people with a strong mathematical background.
Two Minute Papers: Attention is All You Need
Sentdex: Generative Adversarial Networks (GANs) Explained
Corey Schafer: An in-depth look at the package management system
Joma Tech: What is Data science? Told by a Data Scientist
CS Dojo: A Gentle Intro to Deep Learning
While YouTube is such a rich repository for data science resources, keep in mind that it is only a part of the broad picture. Other suggestions to broaden your learning include the following:
Online Courses: Coursera, edX, and Udacity have been the flag bearers of online courses, with a comprehensive data science course inventory brought to you by the leading Ivy League schools and industry thought leaders. These courses provide structured learning pathways with graded assignments and projects.
Books and Articles: Many great books about data science provide insight into the theoretical aspect of things; some of these are books by Tom Mitchell, Andreas Müller, and Gareth James. Their books can help anyone learn most of the theoretical components of data science, together with practical advice. Stay up-to-date with new research by reading articles posted on blogs related to data science and reputable publications.
Kaggle Competitions: Kaggle is a perfect platform for different data science competitions, and this course will help you apply those skills in your case studies. Joining these competitions will enable a researcher to work with other top-notch data scientists, enhance one's problem-solving skills, and create a great portfolio.
Contribute to Open-Source Projects: Contributing to open-source projects on data science libraries and frameworks is a great way to get hands-on experience, interact with the community in data science, and deepen knowledge of the tools being used.
The life of a data scientist is that of learning and discovering. YouTube provides a platform to access quality educational videos on diverse topics related to data science If you follow through with these channels and videos, you will learn a great deal and grow up to be a good professional in data science.
Remember that watching videos is not the end of learning. It goes to utilizing the other resources mentioned so that you can know and keep up to date with the constantly changing field of data science. There are various data science courses which might guarantee job placements.
Not a problem at all! YouTube is filled with resources for people who have just started. Channels like 3Blue1Brown and StatQuest make complex mathematical concepts such as linear algebra and statistics entertaining and easy to follow, while freeCodeCamp.org and DataCamp provide introductory tutorials in Python programming and key data science functionalities.
A few channels focus on practical data science applications. Ken Jee and Krish Naik go deep with project-based tutorials, walking one through building machine learning models or a data science project from scratch. This will give you some of the valuable problem-solving skills and best practices for real-world scenarios
It has also a more theoretical foundation on YouTube: Andreas Kretz is a channel going deep into the math behind different techniques in data science and algorithms used in machine learning and data engineering. Simplilearn courses are well structured, and one can gain much deeper knowledge in certain subdomains of data science.
One needs to be abreast of each newer development in this fast-changing field. Channels like Two Minute Papers give you a summary of new research papers so you will never miss anything new and current in the field and will know all the hot topics in the area. Besides, spandex is oriented toward advanced deep learning techniques and frames that help to be at the edge.
It's just one of many tools, as great as YouTube can be. Mix and match with some online courses from Coursera, read books and related articles in data science, join Kaggle competitions, or better still, contribute to open-source projects. This holistic approach will not only help solidify your knowledge but also build up your portfolio and keep you sharp within the dynamic world of data science.
