Top 6 YouTube Series for Data Science Beginners

Want to start your data science journey from home, for free, and work at your own pace? Have a dive into this data science roadmap using the YouTube series.



Top 6 YouTube Series for Data Science Beginners
Image by Editor

 

Learning a new skill can be daunting, especially when you’ve spent much of your time trying to find the right course, university degree or boot camp. Before you even get to that point of spending a penny, use the free resources available first. Feel it out, see if you like it, and learn most of the content online for free before you’re ready to leap to get certified. 

In this article, I will go through the top X YouTube series that every beginner wanting to learn data science needs to bookmark!

 

Python with freeCodeCamp

 

Link: freeCodeCamp

When a lot of people think about getting into data science and what programming language they should learn - a lot of people naturally turn to Python. And there’s a reason for this. It is considered one of the best programming languages to learn and has been number one for a while now. It contains a variety of libraries and frameworks and uses readable code.

The YouTube series linked by freeCodeCamp is a 4.5-hour video that goes through everything so that you can become a Python programmer. The video is also available in Spanish, Arabic, Portuguese, or Hindi. 

 

Statistics with StatQuest

 

Link: StatQuest

A lot of bootcamps sometimes don’t go over certain elements that are very important to the world of data science - statistics is one of them. From personal experience, I entered the data science world with little to no understanding of the statistics side as my course never offered it. I caught myself having to go back to relearn a lot of things - the right way!

And in that journey was Josh Starmer from StatQuest who made statistics fun and easy to learn. Statistics is important to data science and important to the progression of your career. It allows you to have a better understanding of what data science is and why it matters in your entire data science workflow when creating solutions. 

 

Mathematics with 3Blue1Brown

 

Link: 3Blue1Brown

There is no harm in diving in a little bit deeper when it comes to learning the statistics/mathematical side of data science. I say this because it will only benefit you in your data science learning and career. 3Blue1Brown is a YouTube channel that covers math in an animated form. 

There is a series in the channel which dives into linear algebra, neural networks, and central limit theorem which will be highly beneficial to your data science learning. 

 

Data Cleaning with DataCamp

 

Link: DataCamp

As a data scientist, you will work with a lot of data (obvious right?). But when working with data, you need to remember that a lot of the data given will be messy and you will need to spend time cleaning the data. This is one of the first steps in the data science workflow and is an important one. 

In this YouTube video with Data Camp, you will learn the importance and different techniques on how to get clean and consistent data. The live training will give you insight into the type of data-cleaning challenges you will come across. 

 

Machine Learning with Krish Naik

 

Link: Krish Naik

Machine learning is big right now and it’s only going to get bigger. As part of your data science learning journey, it is important to understand the intricacies of machine learning - this is why I will recommend Krish Naik. 

The video linked is a 6-hour run-through of machine learning. I don’t expect you to take it in through one sitting, but in this 6-hour video, you will learn about the different aspects of machine learning, from the linear regression algorithm to clustering algorithms. When learning these, you will start to understand why understanding statistics is important in data science - things will start to make sense. 

 

Data Visualisations with Simplilearn

 

Link: Simplilearn

When working with data, your only job won’t be learning how to clean it and produce outputs for the decision-making process. As part of your role as a data scientist, you will be responsible for turning your outputs into data visualizations. This is to present your data in other forms, as well as cater to stakeholders who are not highly technically inclined. 

In this YouTube series from Simplilearn, you will learn how to create data visualizations using Matplotlib, Seaborn and Bokeh. By the end of the series, you will become a pro at data visualization by analyzing your data and finding patterns visually. 

 

Wrapping it up

 

Once you master these 6 aspects of data science, you will have a great amount of knowledge and skills to continue your learning with more unique sectors such as deep learning or natural language processing. 

Start your data science journey for free with these YouTube series!
 
 

Nisha Arya is a data scientist, freelance technical writer, and an editor and community manager for KDnuggets. She is particularly interested in providing data science career advice or tutorials and theory-based knowledge around data science. Nisha covers a wide range of topics and wishes to explore the different ways artificial intelligence can benefit the longevity of human life. A keen learner, Nisha seeks to broaden her tech knowledge and writing skills, while helping guide others.