Career Resources for Data Science, Machine Learning, Big Data and Business Analytics Career Repository
This repo is designed to give prospective analytical employees some additional information that might help with the job search. It takes inspiration from Conor Dewey, Academic, CIO, ZuZooVN, Maxim, ryanswanstorm
| Name | Switchup Rating | Cost | Locations |
|---|---|---|---|
| NYC Data Science Academy | 4.87 | $17,600 | New York City and online |
| Dataquest | 4.92 | $29 for a basic monthly subscription; $49 for a premium monthly subscription | Online |
| RMOTR | 4.91 | $349 per month; one-week free trial available | Online |
| Springboard | 4.73 | $499 per month | Online |
| General Assembly | 3.98 | $3,950 for the part-time online courses; $15,950 for the in-person full-time immersive bootcamp program | Dallas, Providence, San Diego, San Francisco, Seattle, New York City, Washington (D.C.), Austin, Los Angeles, Atlanta, Denver, Chicago, London, Singapore, Hong Kong, Sydney, Melbourne, Boston, Santa Monica and online |
| Metis | 4.91 | $750 per course | Chicago, New York City, San Francisco, Seattle, Singapore and online |
| Data Science Dojo | 4.91 | Packages range from $3,799 to $4,499 with the option for flexible payment plans | Seattle, Washington (D.C.), Austin, Chicago, New York City, Toronto, Barcelona, Bucharest, Las Vegas, Singapore, Dubai, Amsterdam, Pretoria and Bangalore |
| Thinkful | 4.89 | $16,000 for the full-time course; $9,500 for the flexible six-month course | Washington (D.C.), Philadelphia, Houston, Portland, Dallas, Los Angeles, Phoenix, San Diego, Atlanta, Miami, Tampa, Chicago, Raleigh-Durham, Denver, Boston, San Francisco, Detroit, Salt Lake City, Seattle, Minneapolis, Austin and online |
| DataCamp | 4.61 | $25 per month | Online |
| The Dev Masters | 4.97 | $4,995 for project-based learning; $6,995 for the mastering applied data science program; $3,500 for the data science for professionals program. | Los Angeles, Orange County and Santa Monica |
| Ubiqum Code Academy | 4.85 | $9,000 | Amsterdam, Barcelona, Berlin and Madrid |
| Level | 4.52 | $4,495 for the introductory data analytics course; $7,995 for the intermediate data analytics program | Boston, Charlotte, San Francisco, San Jose, Seattle, Toronto and online |
| The Data Incubators | 4.52 | Free for accepted fellows | Boston, New York City, San Francisco, Washington (D.C.) and online |
| Jedha | 5.0 | $3,595 for the full stack data science program; $995 for the fundamentals in data science | Lyon and Paris |
| Science to Data Science | 4.83 | £800 registration fee, after that the course is free if you are accepted | London and online |
I don’t know the other areas that well, send my your thought leaders by pull request.
Quora
Data Science Weekly is definitely a fan-favorite, and for good reason. The newsletter started in 2013 and has pumped out 276 consistent issues since. It starts off with an Editor Picks section and quickly moves onto listing a bunch of data science articles and videos. Furthermore, it includes a section for job openings, tutorials, and books as well. Sent every Thursday, this one is well worth your time. Check out a recent issue.
You have probably heard of O’Reilly Media in one way or another. Personally, I have a collection of their books sitting on my desk at all times. They also publish ebooks, host conferences, and offer other learning solutions. Their data-focused newsletter delivers 10 links each week that range from news to tutorials to white-papers.
Data Elixir takes a similar approach, breaking things down into a wide-ranging collection of weekly news, insights, tools & techniques, resources, and data visualization. The newsletter goes out to over 29,000 subscribers and is delivered every Tuesday. Check out a recent issue.
Data Machina is a more technical newsletter that breaks down links by technology, hitting on topics from R to blockchain to algorithms. There’s really a little bit of everything here. I subscribe to the free version, sent every two weeks but it looks like you can pay to receive the newsletter every week if you would like. Check out a recent issue.
Mode offers a number of enterprise data solutions, but they also put out a pretty good data newsletter every week. They primarily focus on articles that catch their eye around the community but also include a section for featured data jobs as well. Check out a recent issue.
As you might have guessed, Machine Learnings focuses on ML and AI news primarily. I particularly enjoy the Awesome and Not Awesome sections that give bite-sized news if you’re in a rush. Others seem to like it as well, as the newsletter boasts 40,000+ subscribers. Check out a recent issue.
Another newsletter that has been around for some time, The Data Science Roundup has 177 published issues and over 7,000 subscribers to date. This newsletter takes a more concise approach, offering 5 or so links each week with an insightful reflection written on each article. Check out a recent issue.
Not a data science newsletter per se, but a valuable resource nonetheless. Like most people in tech, I love Hacker News. However, I had a hard time keeping up with it, until I found this. You can dictate the frequency and amount of links that are sent to you based on the number of upvotes on each post.
This newsletter contains any recent blog posts, interviews, or news regarding Kaggle, everyone’s favorite machine learning competition site. It also includes links, resources, meetups, and job openings around the community. I couldn’t find a subscribe link for this one, pretty sure Kaggle automatically subscribes you when you make an account.
Stratechery’s Daily Update is a little different than the others in that it’s a paid, daily membership. Not a traditional data science newsletter, these reports focus on tech strategy think-pieces. It’ll run you around $10/month, a little less if you pay yearly. This is one of the few places where I gladly pay for written content, Medium being the other. There’s also plenty of free essays available on the site. Check out this post and others to get a feel for it.
Import AI leans heavily on technical machine learning and AI resources, often white-papers and recent research results. The issues also include an impressive amount of analysis. Even if none of that is your thing, make sure to read the Tech Tales section at the end for an always-interesting futuristic story. Check out a recent issue.
Similar to Import AI, this newsletter covers technical machine learning and AI tutorials, projects, research papers, and news. Delivered a bit sporadically, The Wild Week in AI has over 17,000 subscribers if that’s any indication of the content. Check out a recent issue.
Data Is Plural is delivered weekly, focusing solely on interesting datasets for you to explore or use in your next side-project. There’s also a pretty awesome Google doc that serves as the archive for all these datasets dating back to 2015. Check out a recent issue.
Last but not least, the team at Towards Data Science puts out both weekly and monthly digests of the most popular posts on the publication. You can receive these emails by accepting Letters from TDS if you go to the dropdown found on their homepage. Check out a recent issue.
Data is Beautiful
I could spend hours just browsing this subreddit of data visualizations. You’ll be interested in all of the unique ideas and questions that people think up. There’s also monthly challenge where a dataset is chosen, and users are tasked with visualizing it in the most effective way possible. Sort by best all time for instant gratification.
Kaggle
I would be remiss if I didn’t mention the poster child of online data science. There’s a couple ways to use Kaggle effectively for inspiration. First, you can look at the trending datasets and think of interesting ways to leverage the information. If you’re more interested in machine learning and the examples themselves, the kernels feature has gotten better and better over time.
The Pudding
It really is true that visual essays are an emerging form of journalism. The Pudding embodies this movement like none other. The team uses original datasets, primary research, and interactivity in order to explore tons of interesting topics.
FiveThirtyEight
A classic, but still good to this day. I mean come on, Nate Silver is the man. The data-driven blog touches on everything from politics to sports to culture. Not to mention, they just revamped their much improved data export page.
Towards Data Science
Lastly, I’ve got to give a shoutout to the TDS Team for bringing together this community of smart people with a passion for achieving things and helping others grow in data science. Browsing recent stories will bring you more than a few interesting project ideas on any given day.
General
Algorithmic Coding & Python
Statistics and Probability
Data Manipulation & SQL
Data Analysis & Pandas
Machine Learning
Product and Experimentation
Big Data
Tech Interview Handbook
Python
Scala
MongoDB
MySQL
SQL
“Best to work for”
Arcadia Data,
FiveTran,
InfluxData,
Dataiku,
Confluent,
Redis Labs,
StreamSets,
Looker,
Periscope Data,
ThoughtSpot,
Alation,
Dremio,
H2O.ai and
SAP
“Great to work for”
Pivotal Software,
Domo,
Salesforce,
SiSense,
Google,
Couchbase,
Microsoft,
DataStax,
Actifio,
MongoDB,
Databricks,
MemSQL,
Informatica,
Talend,
Qubole
“Good to work for”
Tamr,
VoltDB,
Sumo Logic ,
Reltio,
Trifacta,
DataRobot,
MarkLogic,
Delphix,
EnterpriseDB,
Dell EMC,
Tableau Software,
Amazon Web Services,
Paxata,
Big Squid,
Kyvos Insights,
RapidMiner,
TIBCO
“It is a job”
Qlik,
IBM,
SAS,
Magnitude Software,
Zaloni,
Splunk,
Information Builders,
Hewlett Packard Enterprise,
MicroStrategy,
Cloudera,
Oracle,
Alteryx,
Logi Analytics,
GoodData,
MapR Technologies,
Syncsort,
SnapLogic,
Outlier,
Zoomdata,
Hitachi Vantara/Pentaho,
Datameer
Firmai.org is a project that focuse on the aggregation of open source AI-BI applications. FirmAI envisions a future of open data access and the facilitation of small-medium enterprise automation.
Tired of technical phone screens? Take Triplebyte’s quiz and go straight to final onsite interviews! Also check out Triplebyte’s Salary Tool! They use real data from actual offers made to Triplebyte engineers. A few of the companies that use Triplebyte include Adobe, Robinhood, Box, Dropbox, Instacart, Evernote, Hipmunk, Grammarly & Palantir
r/datascienceproject is a subreddit where you can share all your data science projects. There is no restrictions on self promotion. Let the best post rise to the top. One rule, it has to relate to a data science project.