Microsoft Azure has an abundance of data science capabilities (and non-data science capabilities). It can be challenging to keep up with the latest updates/releases. Luckily, Azure has a page to let you know exactly what has changed. You just need to know where to find it, and the following video will help you find that page.
LinkedIn’s 2017 report had put Data Scientist as the second fastest growing profession and it’s number one on 2019’s list of most promising jobs. There are three main reasons why data science has been rated as a top job according to research. Firstly, the number of available job openings is rapidly increasing and the highest in comparison to other jobs, data science has an extremely high job satisfaction rating, and the median annual salary base is undeniably desirable.
While data science is unquestionably a fantastic career path regarding the impressive ratings and the fact that it is such an in-demand job, statistics show that there will be no slowing down for the surprisingly rapid increase for the demand of data scientists around the globe.
Checkout the top 5 companies to work for if you are a data scientist based on employee reviews, job satisfaction ratings, and CEO approval.
Dataiku is a top-rated computer software company that was founded in 2013 and its headquarters can be found in New York. This company develops collaborative data science software and according to Glassdoor reviews, 99% of the employees that work for Dataiku would recommend working at this company and 100% approve of the CEO. This shows that the vast majority of the employees are satisfied with the company and they are also a top choice for data science and machine learning positions based on annual pay packages.
Checkout: Dataiku Careers
StreamSets was founded in 2014, its headquarter is located in San Francisco, California. The company develops a DataOps platform that can allow business to manage streaming data flows. An impressive 98% of individuals employed at this company would recommend it to their friends and 100% of the employees here also approve of the CEO. StreamSets is a top option for data management and integration.
Checkout: StreamSets Careers
#3 1010 Data
1010 Data has its headquarter in the New York and the company has over 15 years of experience in handling data analytics with over 850 clients across various industries. It is ranked as the third best company to opt for as a data scientist, 1010 Data is also a great option with 96% of employees recommending the company and 99% of employees approving of the CEO.
Checkout: 1010 Data Careers
Reltio is based in Redwood Shores, California and the company was founded in 2011. This top-rated company is recommended by 96% of its employees and a top choice for data management and integration. Even though it is fourth on the list according to statistics, it is still a fantastic company to expand your experience as a data scientist.
Checkout: Reltio Careers
Looker was founded in 2012 and its headquarters are located in Santa Cruz, California. Looker is suggested as a great company to opt for by 95% of their happy employees and 93% of the employees that work at Looker approve of the CEO. This company is great for business analytics.
Checkout: Looker Careers
How can you get a job as a data scientist?
Having a degree in Data Science, Computer Science, Mathematics, Statistics, Social Science, Engineering with additional knowledge of Python, R Programming, Hadoop increases the possibility of getting a starting position job. Plenty of universities offer specialized data science program both online and offline. In recent times, we have observed a rise in online masters in data science, because of the convenience it offers to professionals, especially those looking to switch careers.
Build a portfolio using real data to complete projects that can showcase your abilities as a data scientist. You could also opt for an internship to further develop your skills and knowledge as a data scientist.
Recently updated, is the March 2019 Machine Learning Study Path. It contains links and resources to learn Tensorflow and Scikit-Learn.
If you are interested in details on the study path and how to best use the resources. There is a livestream on Facebook, Sunday March 17 on the Math for Data Science Facebook page.
1. Be Honest
Try not to exaggerate your skills. If the job sounds more engineering focused than you are wanting, be honest and say that. Data Science is getting very broad and you don’t want to get in a position that is a bad fit.
You often sound worse when you try to explain something you do not understand. Just be honest and say, “I have not needed to use that yet, can you explain to me when you have done that?”
Find the job you are looking for, not just any position someone is trying to fill.
2. Tell Stories of Your work
Talk about things you have built. If you built something as part of a team or project, tell about why and your involvement.
If you have a side project, talk about that. This is why side-projects are so important. They help you learn a lot, plus they give you something exciting to talk about, which only you can talk about.
Interviews are intimidating. There is really no way to avoid that. The best you can do is be prepared for the interview. Pramp provides a platform for practicing data science interviews. Practice makes perfect.
Machine Learning for Kids is a site for children and teachers to explore machine learning with the Scratch Programming language. It includes numerous lessons and tutorials for building fun programs which incorporate machine learning.
Read to the end to learn more about a new study group I will be launching.
In Late January 2019, Microsoft launched 3 new certifications aimed at Data Scientists/Engineers. For a while, Microsoft has been toying with different methods for training and credentials. They launched the Microsoft Professional Program in Data Science back in 2017. While it provides great content, it did not result in either a college diploma or an official Microsoft certification. Now Microsoft is in the process of restructing certifications to be more role-focused. Here are details about the 3 certification of interest to data scientists and data engineers.
1. Azure Data Scientist Associate
For more details and to register, go to the Azure Data Scientist Associate page.
2. Azure AI Engineer Associate
For more details and to register, go to the Azure AI Engineer Associate page.
3. Azure Data Engineer Associate
For more details and to register, go to the AzureData Engineer Associate page.
As of March 2019, the exams are in beta phase and the details of what is on the exams are very sparse and vague.
New Study Group
Are you interested in taking one or all of the exams? I am organizing a study group/community. Sign up to get the latest details from Microsoft Data Science Certification Study Group.
Full Disclosure: I am not a Microsoft Employee, and this group is not sponsored or endorsed by Microsoft. I am just excited about the certifications and hoping to help others (and myself) prepare.
University can be a great way to learn data science. However, many universities are very expensive, difficult to get admitted, or not geographically feasible. Luckily, a few of them are willing to share data science, machine learning and deep learning materials online for everyone. Here is just I small list I have come across lately.
- MIT Deep Learning – Lecture notes, slides and guest talks about deep learning and self driving cars
- Introduction to Artificial Intelligence from UC Berkeley – lecture notes, slides, homework from the Fall 2018 course
- Deep Learning Course from University of Paris-Saclay – lecture notes and Python code
- Stanford Machine Learning – cheatsheets from Stanford’s CS 229 machine learning course, translated in multiple languages
Do you have any favorite university resources? If so, please leave a comment.