Essentials of Data Science in 90 Minutes
The 3 basic components of Data Science that you need to get down before launching into your career as a Data Scientist.
So... you're here because you've heard all about this big data science fuss. Everyone's talking about data science and data scientists being the next big thing - they're going to take over the world of data and analytics as we know it. But... you're not really sure what to make of it all?
Maybe you've thought to yourself:
- Sure, it sounds cool... but what exactly does a data scientist do?
- What kind of skills do you need to do data science?
- Or... how do you even get started with learning the "complex art" of data science?
Don't fret - I've been there.
I got started with data science around 2 years ago, and - through a lot of hard work, research and studying in my free time (I'm a little nerd) - have advanced far enough that I am now working my dream job as a Data Scientist for an esports company.
And it's time I teach everything I've learned to the next batch of young data scientists!
This course is right for you if:
- You've been hearing a lot about this whole 'data science' thing and you think it all sounds super cool
- You don't know where or how to get started with data science
- You want to get insight into what a data scientist does
- You're looking for the most basics and fundamental of foundations to build your data science career on
- You want to know all the simple skills you need to nail to start on your data science journey
- You want all this information fast and quick; you don't have any time to waste!
This course is not for you if...
- You're looking for in-depth, specific data science knowledge and topics
- You're already heavily involved with data science and want to advance your knowledge
I've been working as a data scientist for a little while now, and to date, the most common question I still get is: "But... what exactly is data science?"
And I normally launch into a big long rant talking about data pre-processing, hyper parameter optimization or feature selection. They normally look back at me with blank stares.
Understandably.
Because data science is honestly not that complicated. It can really just be broken down three essential components: statistics, data visualization, and programming.
And that's exactly what this course covers.
1. Statistics: we talk about the types of data you'll encounter, types of averages, variance, standard deviation, correlation, and more.
2. Data visualization: we talk about why we need to visualize our data, and the different ways of doing it (1 variable graphs, 2 variable graphs and 3 variable graphs.)
3. Programming: we talk about why programming helps us with data science including the ease of automation and recommended Python libraries for you to get started with data science.
"Excellent overview to Data Science. Great introduction that covers various aspects of data science (e.g. statistics, data visualization, programming) prior to a deeper dive into the specifics. I really appreciate the beginner-friendly approach Max took to explain the various concepts. All-in-all, it is an amazing module and I am looking forward to taking the next-in-line course of Data Science. Many thanks Max!"
- Shao Jun
"This course gives a solid background info for statistical information. It presents to you the various ways to convey the knowledge gained from surveys and other types of data collection. If you've never taken a statistics course, I would highly recommend taking this to get a better understanding of it."
- Brady Ryun, Realtor
So if you're looking to dip your toes into the pools of data science (cool analogy, right?) - then get started right now and you'll know whether data science is right for you in about 90 minutes!
Frequently Asked Questions
Your Instructor
In June 2016, I graduated with a degree in Physics, but instead of delving into a life of research and the lab, I decided to explore other possible options for my life and career.
I found myself more and more drawn towards programming, data mining, data processing, and data analytics. So I decided to teach myself Python, C, C++, Machine Learning, Data Science, Web-Scrapping, APIs, and Data Mining.
Now, I work as a Data Scientist for an e-sports company (total dream job).
So, I thought I would turn the tables and teach you all the knowledge I've been able to gather to make you the ultimate programmer or data scientist.
I have over 9,000 students on various platforms learning programming and data science - join them and get started with your project!