Important technical skills to become a Data Scientist

By the mid-18th century, there was a gold rush in America that prompted folks from across towns in the country to flock to California. Come 2020, and we see that data is pricier and people from across the world are flocking to absorb various aspects of the course.

How to make yourself into a successful Data Scientist?

Things will be easy if your academics and educational background or if you have a natural tendency for mathematics, engineering, or statistics. Do you have a natural tendency to unclog and declutter complicated solutions and problems coupled with a great sense of rationalism?

Technical skills on priority needed for a data scientist include:

Programming skills

Programming languages help to sort, clean, and structure unorganized data. Certain common programming languages that are in much demand for data science roles include Python, C/C++, Perl, SQL, and Java.

Knowledge of Analytical Tools

What do you do with all the cleaned and organized data sets? You need knowledge of analytical tools, like SAS, Hive, Pig, R, and Hadoop to make sense of the data. Certifications and expertise in these programs will help you to derive valuable insights from all the data.

Machine Learning and AI

Data scientists can further their careers with knowledge of machine learning techniques. Techniques like supervised machine learning, logistic regression, and decision trees will help to solve problems related to predictions of outcomes. A recent survey has shown that only a small portion of data scientists are proficient in handling advanced machine learning skills.

Competency in working with unstructured data and using data visualization tools

Part of the challenges of a career as a data scientist is working with content that does not fit into database tables. This includes videos, reviews, blogs, videos, etc. The problem with this format of content is that they are usually heavy content lumped together making them unstructured and undefined. Yes, and they have been rightly called dark analytics. Working with unstructured data gives you rewarding results but it also requires that you are proficient in sourcing data from various social media platforms and being proficient with them. People naturally gravitate to visual aspects rather than looking to decipher complex raw data. Data visualization tools like d3.js, ggplot, and Tableau help organizations and individuals to work with data directly rather than having to decipher complex formats.

For a promising career in Data Science, enroll with Skill Sigma now.