We have conducted some research online that we found out the major obstacles and challenges to work as data scientist or to switch a career to be the data scientist?
#Don’t know where to start or where to learn?
#No Network to find a job or company you like?
#No past experience working as the data scientist? Even you know how to write the algorithm?
Here come the 8 Essential Tips to follow
1. Set your goal first
Looking for new challenging jobs? Just enjoy algorithm or mathematics? Want to start your own startup? Have a special problem, want to look for the solution? Or just to have a better job with more money?
2. Find someone who went through the path that you are interested in, then ask him/her to be a mentor?
It is like running a startup, it takes a lot of energy, time, dedication, motivation, discipline, sometimes even amount of money. You can learn all the best deep learning courses from those famous professors and experts all over the world, however, when it comes to soft skill, you need a mentor to help you, if he/she has even extensive networks, that is even better.
3. Use online education and make a plan to learn and study
Needless to say Andrew Ng’s deep learning courses at Coursera, partnered with NVIDIA Deep Learning Institute.
Andrew Ng is one of the best instructor and teacher I have ever heard and seen, he is perfect articulated, patient, and full of passion to teach as well. I personally took a couple of his classes online at Standford. (the course was really simple enough for anyone who is determined to start!
Btw, I sucked at Linear Algebra during high school 🙁
If you like more entertaining ones, the Youtube star: Siraj Raval also has Youtube channel and Udemy courses online to follow and learn, his goal is to use machine learning to build anything you can be dreamed of. After enough time for studying and online learning, it is always great to apply to the topic you are especially interested.
Don’t forget the traditional way, reading a book: The Bible of the deep learning which was written by Ian Goodfellow and Yoshua Bengio and Aaron Courville.
Certainly, if you like more personal touch, we offer Deep Learning Bootcampin January in Berlin with the topic of NLP, time series forecasting, and computer vision. Our instructors are from IBM and the famous research institute Max Planck Institute. Romeo Kienzler, he also has Youtube channel and is one of the most successful Deep Learning instructor in Europe.
4. Join some online communities and also offline to help you to learn and engage also receiving some feedback to improve
Online: Github, Codeacademy, Kaggle, KD Nuggets
Offline: Meetup, Eventbrite
5. Choose a Tool / Language and stick to it
This is one of the most common questions for beginners. We can have one more article to go deeper into that in the future. For now, choose a language that you are the most familiar with or the simplest for you. If you are completely new, then choose in between the data handling capabilities, advancements in tool, career chance, deep learning support. From my personal experience, I was consulting a machine learning startup with one Python scientist, one R scientist, every time when I had problem with data, I asked Python scientist to write me a quick code to fix my problem while R could not really deal in a such an easy way. Python becomes love of my life for now.
6. Focus on real cases and applications not just learning theory
Think about some scenario you want to work on, music recommendation, Game of throne’s ending? Parking problem? Predict stock market? (Check out our DeepLearning Bootcamp on Eventbrite)
7. Don’t forget machine learning and deep learning it comes down to your mathematics capacity.
Warning: do not just take deep learning and NLP courses, but forget math is the real foundation. Take also some linear algebra courses also or at least linear algebra.
8. Finally, you can start the network but always remember, play smart.
Don’t waste too much energy and time on it, especially a lot of them come with free alcohols…Check the topic before you attend also attendees, are they your target audiences or not really? Or sign up some recruiting event, there will be tons of recruiters and HR managers from companies. (We are launching our First Recruiting Day focused on the data team recruitment in March 2018)
P.S. M.I.E is currently re-branding to Beyond Machine, our mission to connect and boost AI ecosystem through connecting and training. We will launch series events in 2018, following with Deep Learning Bootcamp, Data Analytics Workshop, Recruitment Day, Self-Driving Workshop, Machine Learning Week. Furthermore, we will launch also outside of Berlin and bring more corporation and partnership exchange in and outside of Germany. If you are interested in any kind of sponsorship, partnership, just simply drop us a line.
Build it, Train it, Test it!