Computer industry has significantly progressed throughout these years, starting with a computing device to the rise of data science as career. Changing times have brought new trends in the world of technology and some of them have greatly impacted the career opportunities and growth.
The prominent trendsetters to be mentioned are artificial intelligence, data science, IOT, block chain and innovations are still being made. Talking about the popularity of data science, it is one of the commonly learnt and used technique.
Learning data science is complicated when you are starting from the scratch. What techniques to master on? Which tools to learn? The pros and the cons, all these combined confuse your decision of getting started.
The second step after learning data science is to start a career in this diverse field which comes along with perplexity and complications. Due to lack of resources, starting a career in data science or analytics can be daunting, but what can help you to be a successful data scientist is a road map and some guidance.
Here are a Few Requirements Necessary for Opting Data Science as Career:
• R-Programming:
Data science needs in depth knowledge of advanced programming techniques and among all of them, professionals show a preference towards R. The reason behind this preference is that its specific design and structure for data science needs. One can solve any problem occurring in data science using R. The only complication in using this technique is that it is a bit difficult to learn and master but as you must know where there is a will, there is a way!
• Technical Skills:
While starting a career in such a field, getting your hands on the basic knowledge of some technical computing skills becomes necessary. You should have a good command over python coding as it is the most commonly used coding language in data science and AI roles. SQL is another major aspect to be proficient in as it is known as one of the major components of data science along with Hadoop platform due its ability to access, communicate and work efficiently on data. Along with Hadoop, you cannot forget about Apache spark which is a big data computation framework when it comes to preventing loss of data.
• Non-technical Skill Set:
Establishment of a career requires personal intelligence, problem solving skills, impressive communication and skills and teamwork. Data Science also requires the basic qualities of teamwork behind strategies, a business mindset ready to manage a sufficient amount of resources along with passion and dedication towards your career path.
All these impactful additions to your skill set will help you to start a career in the diverse and vast field of data science. Exploration of technical needs and clear understanding of your goals are the key to success.
Feel free to add on any crucial skill needed to start your journey as a data scientist in the comments below.