Vik Paruchuri
Vik Paruchuri
Learning Data Science: The Dataquest Teaching Philosophy
At Dataquest, we’ve spent years refining our approach to teaching. I was originally motivated to start Dataquest because of my own experience learning data science, and the main goal of our courses is still to help you apply your data science skills in the real world. This could be completing a project at work, being […]
Diversity and Online Education
Online education can be a democratizing force that brings better education to everyone, but only if we approach it in the right way.
Python vs R: Head to Head Data Analysis
Python vs. R — which is better for data science? We compare the two languages side by side and see how Python and R perform on the same analysis steps.
Fixing Education: Motivation and Freedom
Public education, at least in the US, only ever exposes you to one way of learning—top-down hierarchy, and assignments. While some people thrive in this environment, I am not one of them. After college, I was thrown into the world with a 2.1 GPA, no real skills, and no idea of what to do next. […]
The Tips and Tricks I used to succeed on Kaggle
I learned machine learning through competing in Kaggle competitions. I entered my first competitions in 2011, with almost no data science knowledge. I soon ended up in fifth place out of a hundred or so in a stock trading competition. Over the next year, I won several competitions on automated essay scoring and bond price […]
How to become a data scientist
Data science is one of the most buzzed about fields right now, and data scientists are in extreme demand. And with good reason — data scientists are doing everything from creating self-driving cars to automatically captioning images. Given all the interesting applications, it makes sense that data science is a very sought-after career. Data science […]
Building An Analytics Data Pipeline In Python
If you’ve ever wanted to learn python online with streaming data, or data that changes quickly, you may be familiar with the concept of a data pipeline. Data pipelines allow you transform data from one representation to another through a series of steps. Data pipelines are a key part of data engineering, which we teach […]
1 tip for effective data visualization in Python
Yes, you read correctly — this post will only give you 1 tip. I know most posts like this have 5 or more tips. I once saw a post with 15 tips, but I may have been daydreaming at the time. You’re probably wondering what makes this 1 tip so special. “Vik”, you may ask, […]
What is a Data Engineer?
Data engineers build pipelines that prepare and transform data for data scientists. We explore what a data engineer does, and why the role is necessary.
How to present your data science portfolio on GitHub
This is the fifth and final post in a series of posts on how to build a Data Science Portfolio. In the previous posts in our portfolio series, we talked about how to build a storytelling project, how to create a data science blog, how to create a machine learning project, and how to construct […]
The Six Elements of the Perfect Data Science Learning Tool
When I launched Dataquest a little under two years ago, one of the first things I did was write a blog post about why. At the time, if you wanted to become a data scientist, you were confronted with dozens of courses on sites like edX or Coursera with no easy path to getting a […]
How to get a data science job
You’ve done it. You just spent months learning how to analyze data and make predictions. You’re now able to go from raw data to well structured insights in a matter of hours. After all that effort, you feel like it’s time to take the next step, and get your first data science job. Unfortunately for […]
Pandas Tutorial: Data analysis with Python: Part 2
We covered a lot of ground in Part 1 of our pandas tutorial. We went from the basics of pandas DataFrames to indexing and computations. If you’re still not confident with Pandas, you might want to check out the Dataquest pandas Course. In this tutorial, we’ll dive into one of the most powerful aspects of […]
Python Web Scraping Tutorial using BeautifulSoup
When performing data science tasks, it’s common to want to use data found on the internet. You’ll usually be able to access this data in csv format, or via an Application Programming Interface (API). However, there are times when the data you want can only be accessed as part of a web page. In cases […]
I barely graduated college, and that’s okay
I didn’t do very well in high school. My grade point average was around a 2.5 out of 4. I did well in some subjects that I was interested in, like math, computer science, and history, but everything else was a wash. The less homework a class required me to do, the better my grade […]
Pandas Tutorial: Data analysis with Python: Part 1
Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages, and makes importing and analyzing data much easier. Pandas builds on packages like NumPy and matplotlib to give you a single, convenient, place to do most of your data analysis […]
NumPy Tutorial: Data analysis with Python
Don’t miss our FREE NumPy cheat sheet at the bottom of this post NumPy is a commonly used Python data analysis package. By using NumPy, you can speed up your workflow, and interface with other packages in the Python ecosystem, like scikit-learn, that use NumPy under the hood. NumPy was originally developed in the mid […]
Working with SQLite Databases using Python and Pandas
In this post, you’ll learn to query, update, and create SQLite databases in Python. And learn how to use the pandas package to speed up your workflow.
17 places to find data sets for data science projects
This is the fifth post in a series of posts on how to build a Data Science Portfolio. You can find links to the other individual posts in this series at the bottom of the post. If you’ve ever worked on a personal data science project, you’ve probably spent a lot of time browsing the […]
Tutorial: Working with Streaming Data and the Twitter API in Python
If you’ve done any data science or data analysis work, you’ve probably read in a CSV file or connected to a database and queried rows. A typical data analysis workflow involves retrieving stored data, loading it into an analysis tool, and then exploring it. This works well when you’re dealing with historical data such as […]