Guide To Get In Data Science — Part-2
Things to know to get into Data Science
- Statistics — A lot of companies ask on Bayes theorem and Normal distribution
- Machine/Deep learning basics — Algorithm pros/cons and working
- Strong coding skills — Python + Competitive coding
- Database — Minimum required is SQL skills. Good to know both SQL and NoSQL databases.
- Cloud computing — A huge add-on but not an absolute necessity. Learn AWS(Amazon Web Services)
- Github — Displaying good work on Github shows confidence and enthusiasm — what best companies look for
- Blog — Blogging leads to self-clarity on your topics of interests. Also, since I learnt a lot by reading blogs of others, I always feel like giving back by to the community.
In general how the study looks like!
Math basics (Calculus and Linear Algebra)
There is no doubt why you should make Python your playground for all the data science activities. (Avoid ‘R’ language at all cost as it has no advantage over Python)
- Andrew’s course(Do assignments in Python and not in Octave for best start)
- Udacity’s course(I think it’s better to watch it after Andrew’s course)
- StatQuest insights
- Data science handbook
- How to Win a Data Science Competition
NLP(Natural Language Processing)
- Computer vision → Convolutional Neural Networks
- NLP → Natural Language Processing with Deep Learning
- Reinforcement learning by David Silver
Cloud & Big Data
Amazon Web Services(AWS) cloud skills are in high demand right now as everyone wants to deploy their new and old solutions on cloud. Sizzle it up with Big-data skills and you will become every company’s fantasy employee.