Best YouTube Channels to Learn Data Science

Are you looking for the best YouTube channels to learn data science? Data science has surged in importance, growing 15 to 20 times in recent years, with an expected 28% growth by 2026.

YouTube offers free, high-quality educational content for beginners, making complex concepts in data science, machine learning, and AI accessible to a wide audience. It’s a great platform for learning the skills that help companies analyze user behavior and improve products.

With countless YouTube channels available, how do you find the best ones for data science? Look no further! Here’s a curated list of top channels to boost your data science journey, whether you’re a beginner or aiming to advance your skills. Computer science also plays a foundational role, which is essential for understanding data science and its applications.

Before we dive in, remember that while YouTube is an excellent starting point, it’s just the tip of the iceberg. A tutor, on the other hand, can accelerate your learning beyond what self-study alone can achieve. Wiingy offers expert Data Science tutors for better conceptual understanding, homework help, assignments, and project guidance.

Now, let’s explore the best Data Science education on YouTube!

12 Best YouTube Channels for Learning Data Science

Channel Name	Subscribers	Total Views	Number of Videos	Avg. Video Length
StatQuest with Josh Starmer	1.21M	96M	282	10-15 minutes
Krish Naik	723K	66M	1,100+	15-30 minutes
Ken Jee	196K	14M	400+	10-20 minutes
Data School	202K	15M	250+	15-25 minutes
Corey Schafer	1.03M	97M	230+	20-30 minutes
Sentdex	1.09M	124M	1,300+	15-25 minutes
DataCamp	279K	14M	500+	5-10 minutes
Keith Galli	188K	12M	70+	30-60 minutes
Tina Huang	132K	8.5M	100+	10-15 minutes
Alex The Analyst	381K	20M	150+	10-20 minutes
freeCodeCamp.org	7.03M	525M	1,400+	1-4 hours
Data Professor	235K	11M	300+	10-20 minutes

Let’s dive deeper into each of these channels to understand what makes them stand out in the vast sea of Data Science content.

1. StatQuest with Josh Starmer

StatQuest is your go-to channel for breaking down complex statistical and machine-learning concepts into bite-sized, easily digestible videos.

• Started: 2012
• Subscribers: 1.21 million
• No. of videos: 282
• Views: 96 million
• Frequency of videos: Weekly
• Average duration: 10-15 minutes
• Country: United States
• Teaching Style: Clear, concise explanations with hand-drawn illustrations
• Interactive Elements: Quizzes and challenges in some videos

Josh Starmer, a Ph.D. in Genetics and Molecular Biology, has a knack for making even the most daunting statistical concepts feel approachable. His videos cover a wide range of topics, from basic statistics to advanced machine learning algorithms. What sets StatQuest apart is Josh’s ability to break down complex ideas using simple analogies and hand-drawn illustrations.

Key Points:

• Simplifies complex statistical concepts
• Uses engaging animations and illustrations
• Covers both basic and advanced topics

2. Krish Naik

Krish Naik’s channel is a treasure trove for data enthusiasts and aspiring Data Scientists, offering a mix of theoretical concepts and practical implementation.

• Started: 2017
• Subscribers: 723K
• No. of videos: 1,100+
• Views: 66 million
• Frequency of videos: Almost daily
• Average duration: 15-30 minutes
• Country: India
• Teaching Style: Practical, project-based learning
• Interactive Elements: Live coding sessions, Q&A videos

Krish covers a wide array of topics, from Python programming basics to advanced machine learning techniques. His project-based approach helps learners understand how to apply Data Science concepts in real-world scenarios. Krish also frequently discusses industry trends and career advice, making his channel invaluable for those looking to break into the field.

Key Points:

• Focuses on practical, real-world applications
• Includes a vast array of tools and techniques used in Data Science
• Provides career advice and industry insights

3. Ken Jee

Ken Jee’s channel offers a unique blend of Data Science education and career insights.

• Started: 2018
• Subscribers: 196K
• No. of videos: 400+
• Views: 14 million
• Frequency of videos: 2-3 times per week
• Average duration: 10-20 minutes
• Country: United States
• Teaching Style: Personal experiences, tutorials, and career advice
• Interactive Elements: Live streams, coding challenges

Ken‘s content ranges from technical tutorials on tools like Python and SQL to soft skills necessary for a successful Data Science career. His “Day in the Life” series gives viewers a realistic glimpse into the work of a Data Scientist. Ken’s approachable style and focus on practical skills make his channel particularly useful for those transitioning into Data Science from other fields.

Key Points:

• Blends technical tutorials with career advice
• Shares personal experiences in the Data Science field
• Covers both hard and soft skills

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4. Data School

Data School, run by Kevin Markham, is an excellent resource for those looking to build a solid foundation in Data Science.

• Started: 2014
• Subscribers: 202K
• No. of videos: 250+
• Views: 15 million
• Frequency of videos: Monthly
• Average duration: 15-25 minutes
• Country: United States
• Teaching Style: Step-by-step tutorials, focus on pandas library
• Interactive Elements: Code-along sessions, dataset exploration

Kevin‘s teaching style is methodical and beginner-friendly. He’s particularly known for his in-depth tutorials on the pandas library, an essential tool for data manipulation in Python. Data School’s content is perfect for those who prefer a structured, classroom-like approach to learning Data Science.

Key Points:

• Strong focus on pandas library
• Structured, classroom-style approach
• Emphasis on data manipulation and analysis

5. Corey Schafer

While not exclusively focused on Data Science, Corey Schafer’s Python tutorials are invaluable for aspiring Data Scientists.

• Started: 2013
• Subscribers: 1.03 million
• No. of videos: 230+
• Views: 97 million
• Frequency of videos: Monthly
• Average duration: 20-30 minutes
• Country: United States
• Teaching Style: In-depth, step-by-step coding tutorials
• Interactive Elements: Code-along sessions, real-world examples

Corey‘s Python tutorials are known for their clarity and depth. He covers everything from Python basics to advanced topics like decorators and generators. For Data Science learners, his series on pandas, matplotlib, and NumPy are particularly useful. Corey’s attention to detail and focus on best practices make his channel an excellent resource for building a strong programming foundation.

Key Points:

• In-depth Python programming tutorials
• Covers Python libraries essential for Data Science
• Emphasis on best practices and clean code

6. Sentdex

Sentdex, run by Harrison Kinsley, offers a wide range of Python programming and machine learning tutorials.

• Started: 2010
• Subscribers: 1.09 million
• No. of videos: 1,300+
• Views: 124 million
• Frequency of videos: Weekly
• Average duration: 15-25 minutes
• Country: United States
• Teaching Style: Project-based learning, focus on practical applications
• Interactive Elements: Coding challenges, community projects

Harrison‘s content covers a broad spectrum of Data Science topics, from basic Python programming to advanced machine learning and artificial intelligence. What sets sentdex apart is the focus on practical, real-world applications. Whether it’s creating a stock prediction algorithm or building a self-driving car in Grand Theft Auto V, Harrison shows how to apply Data Science concepts to interesting and engaging projects.

Key Points:

• Wide range of Python and machine learning topics
• Focuses on practical, interesting projects
• Covers cutting-edge AI and Data Science applications

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7. DataCamp

DataCamp’s YouTube channel serves as an extension of its popular online learning platform.

• Started: 2014
• Subscribers: 279K
• No. of videos: 500+
• Views: 14 million
• Frequency of videos: Weekly
• Average duration: 5-10 minutes
• Country: Belgium/USA
• Teaching Style: Short, focused tutorials and career insights
• Interactive Elements: Webinars, live Q&A sessions

While their main platform offers in-depth courses, their YouTube channel provides quick tutorials, career advice, and insights into the Data Science industry. The channel features a mix of technical content and soft skills development, making it a well-rounded resource for aspiring Data Scientists.

Key Points:

• Short, focused tutorials on various Data Science topics
• Career insights and industry trends
• Complements DataCamp’s online learning platform

8. Keith Galli

Keith Galli’s channel focuses on Python programming with an emphasis on Data Science applications.

• Started: 2018
• Subscribers: 188K
• No. of videos: 70+
• Views: 12 million
• Frequency of videos: Monthly
• Average duration: 30-60 minutes
• Country: United States
• Teaching Style: Long-form tutorials, project-based learning
• Interactive Elements: Code-along sessions, real-world data analysis

Keith‘s videos are known for their depth and thoroughness. His longer video format allows for comprehensive coverage of topics, from data cleaning and visualization to machine learning. Keith’s project-based approach, often using real-world datasets, helps learners understand how to apply Data Science techniques to solve actual problems.

Key Points:

• Long-form, in-depth tutorials
• Focus on practical Data Science applications
• Covers data cleaning, visualization, and machine learning

9. Tina Huang

Tina Huang offers a unique perspective as a self-taught Data Scientist working in Silicon Valley.

• Started: 2019
• Subscribers: 132K
• No. of videos: 100+
• Views: 8.5 million
• Frequency of videos: Weekly
• Average duration: 10-15 minutes
• Country: United States
• Teaching Style: Personal experiences, career advice, and technical tutorials
• Interactive Elements: Live coding sessions, Q&A videos

Tina‘s content is a mix of technical tutorials and career insights. She often shares her journey of becoming a Data Scientist, providing valuable advice for those looking to break into the field. Her videos on resume building, job interviews, and day-in-the-life of a Data Scientist are particularly popular among aspiring professionals.

Key Points:

• Shares personal experiences as a self-taught Data Scientist
• Blends technical tutorials with career advice
• Focuses on practical skills for breaking into the field

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10. Alex The Analyst

Alex Freberg’s channel, Alex The Analyst, focuses on data analytics and visualization, with content tailored for beginners.

• Started: 2020
• Subscribers: 381K
• No. of videos: 150+
• Views: 20 million
• Frequency of videos: Weekly
• Average duration: 10-20 minutes
• Country: United States
• Teaching Style: Step-by-step tutorials, focus on SQL and data visualization
• Interactive Elements: Project walkthroughs, tool comparisons

Alex’s content is particularly useful for those starting their Data Science journey. He covers essential skills like SQL, Excel, and Tableau, often through project-based tutorials. His “Data Analyst Bootcamp” playlist provides a structured path for beginners to learn key Data Science skills.

Key Points:

• Focuses on data analytics and visualization
• Tailored for beginners and career transitioners
• Covers essential tools like SQL, Excel, and Tableau

11. freeCodeCamp.org

While not exclusively focused on Data Science, freeCodeCamp.org offers a wealth of programming, computer science, and Data Science content.

• Started: 2014
• Subscribers: 7.03 million
• No. of videos: 1,400+
• Views: 525 million
• Frequency of videos: Weekly
• Average duration: 1-4 hours (full courses)
• Country: United States
• Teaching Style: Comprehensive courses, hands-on coding
• Interactive Elements: Coding exercises, projects

freeCodeCamp.org is known for its in-depth, course-style videos covering various programming languages and technologies. Their Data Science content includes full courses on Python, machine learning, and data analysis. The long-form video format allows for comprehensive coverage of topics, making it ideal for dedicated learners who prefer a structured approach.

Key Points:

• Offers full-length courses on various programming topics
• Covers a wide range of Data Science and coding skills
• Provides structured learning paths

12. Data Professor

Run by Chanin Nantasenamat, Data Professor offers a mix of Data Science tutorials and career advice.

• Started: 2019
• Subscribers: 235K
• No. of videos: 300+
• Views: 11 million
• Frequency of videos: Weekly
• Average duration: 10-20 minutes
• Country: Thailand
• Teaching Style: Hands-on tutorials, focus on practical applications
• Interactive Elements: Live coding sessions, tool demonstrations

Chanin‘s videos cover a wide range of Data Science topics, from machine learning algorithms to data visualization techniques. He often showcases various Data Science tools and platforms, helping viewers understand the practical aspects of working in the field. His content is particularly useful for those looking to apply Data Science in research or academic settings.

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Key Points:

• Covers a wide range of Data Science topics and tools
• Focuses on practical applications in research and industry
• Blends technical tutorials with career advice

Learning Insights

While these YouTube channels offer a wealth of knowledge, it’s essential to approach your learning strategically.

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Here are some tips to make the most of your YouTube Data Science education:

1. Create a Learning Plan: Don’t just watch videos randomly. Create a structured plan that covers the fundamentals before moving to advanced topics.
2. Practice Regularly: Data Science is a hands-on field. Make sure to code along with the tutorials and work on projects to reinforce your learning.
3. Explore Multiple Channels: Each creator has their unique teaching style and areas of expertise. Exploring multiple channels can give you a well-rounded understanding of concepts.
4. Engage with the Community: Many of these channels have active comment sections or associated forums. Engage with fellow learners to discuss concepts and share resources.
5. Supplement with Other Resources: While YouTube is excellent for visual learning, complement your studies with textbooks, online courses, and coding practice platforms.
6. Stay Updated: The field of Data Science evolves rapidly. Follow multiple channels to stay informed about the latest trends and technologies.
7. Apply Your Learning: Try to apply the concepts you learn to real-world datasets or problems. This hands-on experience will strengthen your comprehension and enhance your collection of work.

Stay Updated: Data Science is constantly evolving, with new tools and techniques emerging regularly. Keeping pace is even more critical if you’re preparing for exams.

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The Role of Data Science Tutors in Your Learning Journey

While YouTube channels provide an excellent starting point for learning Data Science, they have limitations. This is where Wiingy’s Data Science tutors can play a crucial role in your educational journey.

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Here’s an informative table summarizing the advantages of having a tutor compared to YouTube videos for learning:

Aspect	Tutors	YouTube Videos
Personalized Learning	Tutors tailor lessons to individual needs, learning styles, and pace, offering a more customized experience.	Standard content, created for a broad audience without personalization.
Immediate Feedback	Provides instant, personalized feedback on errors or questions, helping you correct mistakes in real-time.	No direct interaction or feedback, requiring you to troubleshoot issues independently.
In-depth Guidance	Tutors can dive deeper into topics and give context and real-world applications specific to your goals.	Videos may lack depth on certain topics and might not cover advanced applications.
Structured Learning Path	Tutors can design a structured learning path, ensuring you cover all relevant topics logically.	Content is often unorganized, requiring you to build your own learning plan.
Project Support	Offers hands-on support and feedback on projects, helping you improve skills and deliver high-quality work.	No direct assistance for project-related work; you need to find resources on your own.
Career Advice	Tutors with industry experience provide valuable insights into job markets and career growth.	Typically, videos do not cover personalized career advice or job market trends.
Motivation & Accountability	Regular sessions with a tutor help maintain motivation and hold you accountable for consistent progress.	Self-paced learning with no accountability makes it easier to lose focus over time.

While YouTube channels are excellent for introducing concepts and providing a broad overview, Data Science tutors can offer the depth, personalization, and interaction needed to truly master the field.

Tutors not only tailor lessons to your unique needs but also help you stay focused, accountable, and prepared for exams and real-world applications.

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Conclusion

Looking to start or advance your Data Science journey? Here are the top 12 YouTube channels that provide a wealth of knowledge and practical learning. StatQuest with Josh Starmer simplifies complex statistical concepts with engaging visuals, while Krish Naik offers real-world, project-based tutorials and career insights. Ken Jee blends technical tutorials with valuable career advice, and Data School excels at step-by-step guides, particularly with the pandas library. If you’re looking for in-depth Python tutorials, Corey Schafer is a must-watch.

For hands-on projects and practical applications, Sentdex and Keith Galli provide project-based learning in Python and data visualization. Tina Huang shares personal experiences and career tips for breaking into the field, while Alex The Analyst focuses on beginner-friendly content for tools like SQL and Excel. freeCodeCamp.org offers full-length Data Science courses, and DataCamp provides short, focused tutorials with career insights. Finally, Data Professor covers a broad range of Data Science topics with a practical, hands-on approach.

These channels offer a mix of tutorials, projects, and career advice, making them essential resources for anyone looking to learn or deepen their understanding of Data Science.

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