Data science has been branded as the hottest and sexiest job of the 21st century. The modern world we are living in today is full of pressing questions that must be answered by big data. The term data science comprises data analytics, business intelligence and much more. For businesses and nonprofit organizations, there is a seamless infinite amount of information that can be collected, sorted, analyzed and interpreted to help in making meaningful decisions.
A good question is how a business use purchasing data to create a marketing plan can? How can various departments in government use patterns and behavior to engage in community activities? For these and many other questions, we can only rely on big data analytics for answers.
Who is a Data Scientist?
A data scientist is a person trained to gather, organize and analyses data to help people from different industries make appropriate decisions, Data scientists come from different educational backgrounds be it math, computer science or engineering. A data science degree involves a range of computer-related majors but also features math and statistics. To become a data scientist, there are some natural skills you need to possess. First, you need to be curious and have a drive that pushes you to learn always.
To get started, you need to know the role of data scientist and what they play in the industry. Next, you will get yourself acquainted with python. When you get to know the basics of python, the next step is to explore statistics. When examining statistics, you should aim at having a firm grasp on the basics of statistics. You should also be ready at exploring a given dataset and performing their respective data visualization.
Next, you need to get into the basics of machine learning. In the end, you should develop enough knowledge to take part in hackathons and get a good ranking. Go into the depth of feature engineering as it forms one of the most exciting aspects of data science.
Data Science Persona
At this stage, you need to build a data science persona. The real challenge facing data scientists lies in explaining the power and capabilities of the models you create for non-technical people. Build your persona and work hard to get recognition and ranking in the groups you compete with.
Once you have built your persona, go into the depths of advanced machine learning and time series modeling. You should aim at tackling advanced ML algorithms and time series models. Note that most of the data you will deal with will be unstructured.
Once you get to understand how to deal with unstructured data, it’s time you introduce yourself to deep learning. At this stage, you get to know how to deal with neural networks and how to solve neural problems. Remember practice is the only real way to keep up with the demands of big data. A data science degree might be the most obvious career path, but other non-technical computer-based degrees can help you in launching your data science career. These degrees are in the fields of computer science, statistics, physics, social sciences, math, and economics.