Top Data Science YouTube Channels in 2026 from Canada

Data Science is one of the most in-demand fields in technology, bridging the gap between raw data and actionable insights. Channels in this category cover the full spectrum of the discipline, from fundamental statistical analysis and data visualization to advanced machine learning and deep learning models. Whether you are aspiring to be a Data Scientist, Data Analyst, or Data Engineer, these creators provide the roadmap you need.

2 ChannelsPage 1 of 1

Content typically ranges from beginner-friendly tutorials on Python, R, and SQL to deep dives into libraries like pandas, NumPy, Scikit-learn, and TensorFlow. You'll also find extensive coverage of big data tools like Apache Spark and Hadoop, as well as business intelligence platforms like Tableau and PowerBI. Beyond syntax and tools, these channels often explore critical concepts such as data ethics, experimental design, and the mathematical foundations of algorithms.

Real-world applications are a major focus, with creators demonstrating how to clean messy datasets, build predictive models, and deploy AI solutions into production. Many channels also offer career advice, portfolio reviews, and mock interviews to help you navigate the competitive job market and land your first role in the data industry.

Channels

CS Dojo YouTube channel profile picture
1

CS Dojo

@CSDojo

Hello! My name is YK, and I usually make videos about programming and computer science here :)Business email: https://www.csdojo.io/contact/The logo was made...

Canada
Subscribers
1.95m
Total Views
84.5M
Videos
114
Coding on Windows (and Linux) in 2024?! | Introduction to C# and .NET | Scott Hanselman thumbnail
55:57

Coding on Windows (and Linux) in 2024?! | Introduction to C# and .NET | Scott Hanselman

13.8K views1 year ago

CS Dojo, hosted by YK, is a prominent YouTube channel dedicated to demystifying programming and computer science for a broad audience. The channel offers insightful tutorials, interviews with industry leaders, and practical advice for aspiring and established tech professionals. With a focus on data structures, algorithms, web development, and the evolving landscape of AI in tech, CS Dojo provides viewers with actionable knowledge to advance their careers. Whether you're a beginner looking to learn coding fundamentals or an experienced developer seeking to stay ahead, YK's engaging content aims to educate and inspire your journey in technology.

What Makes This Channel Unique

CS Dojo stands out by blending foundational computer science concepts with cutting-edge AI tools and career-focused advice, delivered through a mix of engaging tutorials, in-depth interviews, and YK's personal insights. The channel effectively bridges the gap between academic learning and real-world tech application, offering practical roadmaps and interviews with influential figures like Evan You and Scott Hanselman.

Irregular
English
Target Audience

Aspiring and current software engineers, computer science students, aspiring AI/ML practitioners, and individuals interested in tech careers. The audience ranges from beginners seeking foundational knowledge to intermediate developers looking to specialize or advance.

Content Formats
TutorialsInterviewsExplainersCareer AdviceCase StudiesLive CodingDevlogs
Primary Topics
Programming & Computer Science FundamentalsArtificial Intelligence & AI Coding ToolsSoftware Engineering & Career DevelopmentData Structures & AlgorithmsWeb Development
Towards Data Science YouTube channel profile picture
2

Towards Data Science

@TowardsDataScience

We provide a platform for thousands of people to exchange ideas and to expand our understanding of data science. Our audience is mixed, consisting of beginne...

Canada
Subscribers
18.1k
Total Views
351.4K
Videos
152
Ryan Fedasiuk - Can the U.S. and China collaborate on AI safety? thumbnail
48:20

Ryan Fedasiuk - Can the U.S. and China collaborate on AI safety?

608 views3 years ago

Towards Data Science is a Canadian‑based YouTube channel that curates in‑depth AI and data‑science podcast interviews with leading researchers, industry experts, and thought‑leaders. Each episode delves into cutting‑edge topics such as AI safety, large‑model scaling, data observability, ethics, and emerging applications like synthetic data and ML sensors. The channel serves as a knowledge hub where listeners can hear firsthand insights, research breakthroughs, and practical perspectives that bridge academia and industry. Its long‑form format (≈50 minutes) allows nuanced discussion, making complex concepts accessible without oversimplifying. Viewers gain exposure to the latest trends, scholarly debates, and future directions of data science, helping both seasoned professionals and aspiring enthusiasts stay ahead of the curve.

What Makes This Channel Unique

TDS aggregates high‑caliber, research‑level conversations from a diverse set of AI experts into a single, easily searchable podcast channel, offering listeners direct access to frontier insights rarely found in standard tutorial‑style content.

Irregular – historically clustered releases, roughly monthly when active but no consistent schedule in recent years
English
Target Audience

Data scientists, AI researchers, graduate students, tech professionals, and informed enthusiasts interested in advanced AI concepts and industry trends, primarily English‑speaking ages 20‑45.

Content Formats
InterviewsPodcast EpisodesPanel Discussions
Primary Topics
AI safety and alignmentLarge language model and multimodal researchData observability and governanceAI ethics, trust and regulationEmerging AI applications (synthetic data, ML sensors)

Frequently Asked Questions

What is the best way to start learning Data Science?

A combination of theoretical study and practical application is best. Start by learning a programming language like Python or R, and the basics of statistics. Then, apply what you learn by working on projects, such as analyzing public datasets from Kaggle. Supplement this with online courses or tutorials from the channels listed here.

Should I learn Python or R for Data Science?

Both are excellent choices. Python is generally recommended for beginners due to its simple syntax and versatility, especially if you want to move into Machine Learning or Deep Learning. R is a powerhouse for statistical analysis and academic research. Many professionals end up learning the basics of both, but Python is currently more dominant in the industry.

Do I need a strong math background to become a Data Scientist?

While a degree in mathematics isn't strictly necessary, a solid understanding of certain mathematical concepts is crucial. Focus on Probability, Statistics, Linear Algebra, and Calculus (specifically derivatives and gradients for optimization). You don't need to be a mathematician, but you need to understand how algorithms work under the hood.

What kind of projects should I include in my portfolio?

Aim for a diverse mix of projects that showcase different skills: an Exploratory Data Analysis (EDA) project to show your storytelling ability, a Machine Learning project to demonstrate your modeling skills, and perhaps a deployed app (using Streamlit or Flask) to show you can put models into production.