Can I learn data science in six months?

Data science is a rapidly growing domain that delivers exciting career possibilities. However, it can take a lot of work, so it’s hard to gauge how long it will take to pick up the skills needed to become a successful data scientist. 

While it may be tempting to think you can learn data science in just six months, most people will need a less ambitious timeline. It is possible to build a solid foundation in the fundamentals in six months, but a lot more time and dedication is needed to master data science. 

Factors to consider when planning accelerated learning in data science

THIS ARTICLE COVERS:

• Factors to consider when planning accelerated learning in data science
• How long does it take to learn data science?
• What you should master at each level of learning
• What you can learn in six months
• Developing your expertise

How long you take to grasp the basics of data science will depend on:

• Your experience and current skill set;
• How much time you can devote to your data science studies;
• How you intend to use the knowledge you gain.

Typically people with backgrounds in analytical fields like accounting, engineering, computer science, mathematics, and physics need less time to grasp the basics than those with no analytical background.

How long does it take to learn data science?

The answer to this must take into account:

• Your existing knowledge base;
• The data science curriculum you choose;
• The learning mode you choose;
• The total number of hours you are prepared to put into learning and practising data science.

If you have no prior coding experience or mathematical background, you need seven to 12 months of intensive study to become an entry-level data scientist.

What you should master at each level of learning

There are three levels of learning in data science – basic, intermediate and advanced. 

Basic-level data science (6 to 12 months)

Once you have completed this level of learning you should be able to work with datasets generally presented in comma-separated value (CSV) format, and be competent in basic data science, visualisation, and linear regression.

Intermediate-level data science (7 to 18 months)

Once you have completed your intermediate level data science studies you should be at home using Sci-kit-learn for model building, understand several metrics for assessing the quality of a classification algorithm, and be familiar with all binary classification algorithms.

Advanced-level data science (18 to 48 months) 

At this level, you should be able to work with advanced datasets such as text, images, audio, and video. You should also be able to deploy your skills in:

• Deep learning;
• Neural networks;
• Clustering algorithms; and
• Cloud systems such as AWS and Azure.

What you can learn in six months

So yes, you can grasp the foundations of data science in six months if you have a strong background in mathematics, statistics and coding, and depending on how you pace yourself.

These tips will help you achieve what most others cannot: 

• Always be learning;
• Learn:
  • To program with Python and R;
  • The various methods of analysis;
  • How to use data science tools;
  • How to tell stories using data;
• Familiarise yourself with databases;
• Practice – start working on beginner projects; and
• Network with data science professionals.

Developing your expertise

If you put in the effort you can learn the basics of data science in six months. And while you can master data science fundamentals in less than a year, your level of expertise will develop only through mastery of various skills and lots of practice – so don’t expect to become an advanced data pro in a matter of months! 
Enrol in a Digital Regenesysdata science course and get the most out of your education. These courses are designed to provide you with comprehensive overviews and hands-on experience. More data science course details here