• Stars
    star
    623
  • Rank 72,088 (Top 2 %)
  • Language
  • Created over 6 years ago
  • Updated 7 months ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Learning from multiple companies in Silicon Valley. Netflix, Facebook, Google, Startups

Data Scientist Roadmap

Below you can find a chart demonstrating the paths that you can take and the milestones that you would want to achieve in order to become a data scientist. We spoke to senior data scientists and data science managers from various top tech companies in the Silicon Valley, and consolidated learnings from these conversations and data science Meetups in the Bay Area. We hope this can serve as a guide to everyone interested in breaking into data science, especially people who do not live in close proximity to any tech hubs and donโ€™t have a strong personal network in data engineering.

We are continuing to add recommended resources, example practice projects and additional tips to expand the roadmap. Contributions are welcome and highly appreciated.

Depending on your background, you may already possess certain skills on the roadmap so skip those modules to craft your own path. If you have succeeded in making the transition to data science, we would love to hear from you and share your personal path with many others.

If you are having difficulties to commit through this entire roadmap yourself. I will suggest finding someone like minded and have similar goals to start the arduous task of learning together. Heading over to meetups is one way to network with people who are looking to learn. We started a community to help connect people with similar learning goals. We plan to make it forever free for users. If you are interested, head over to http://ml.boringppl.com/

Disclaimer

The purpose of this roadmap is to give you an overview of the core skills needed in data science. These are views help by individuals we have spoken to and do not represent any companiesโ€™ opinion. Data science roles vary from one company to another, and from one role to another. If you are interested in a specific data engineering role, please invest time to research on the specific requirements and double down efforts on the relevant branches on the chart. If anything is missing, send a PR to update the chart. If you found any insights that helped you in your journey, the community will greatly benefit from your contribution.

Roadmap

Roadmap

Resources

Successful Paths contributed by data scientists

More Repositories

1

data-engineer-roadmap

Learning from multiple companies in Silicon Valley. Netflix, Facebook, Google, Startups
901
star
2

Linkedin-profiles-scraping

Automatically scrape the web data of people profiles on Linkedin based on a specific search query
Jupyter Notebook
59
star
3

Sales-Reporting

Conduct a Report and Analysis on 200,000 sales data points to answer revenue-related questions for the business
Jupyter Notebook
21
star
4

presidential-debates-comments-clustering

At the point when we started this project, election week is coming up. There was so much excitement in the air on who is the next US president to be elected. There were thousands of articles on who's leading the polls. The US election has been trending on most, if not all, social media platforms. Being Data scientists, we wonder if it would be possible to leverage on these different data sources to understand various topics of discussion surrounding each candidate. Of which, we have decided to focus on Youtube comments as a starting point for this project.
Jupyter Notebook
13
star
5

deeplearning-roadmap

Deep Learning path with multiple notebooks
Jupyter Notebook
5
star
6

data-project-guideline-from-Netflix

"Data science is such a nebulous term. To some, it means data analytics; to some it is synonymous to machine learning; others think there is a data engineering flavor to it. The wide spectrum of possible responsibilities and the nuanced differences across companies or even teams within the same company make the identity evasive. You literally have to speak to a data scientist in company X to understand how company X sees data science. This guidline is inspired by a Netflix talk with a focus on the structure of a data science projects."
5
star
7

Auto-Send-Linkedin-Connect-Request

Automatically send Linkedin invites with personalized messages to a database of targeted profiles.
Python
4
star
8

flownote-dockers

Python
3
star
9

boringppl-meeting-summarization

Jupyter Notebook
3
star
10

k8s-gateway

JavaScript
2
star
11

Crash-Course-on-Python

A comprehensive curriculum of Python programming foundation
Python
1
star
12

hasbrain-helper-files

Helper files for hasBrain notebooks
Python
1
star
13

Rename-and-Organize-files-directories

Toy problem: Practice generating fake data; then, rename and organize the data into folders of their genres
Python
1
star
14

onboarding

JavaScript
1
star