Before entering any career, it is necessary to understand if you have a professional profile that will do well in it. Working with Data Science is easier if you have had experiences that bring you closer to the knowledge needed by a data scientist, which does not mean that it is impossible to start from scratch.
All the skills listed here can be developed and practiced. However, accelerating your market entry will be easier if you have the following attributes.
- Knowledge in statistics
Data scientists are constantly working with statistical models. So, if you studied in a field such as Computer Engineering or Mathematics, you will learn much faster than those who have not yet mastered the discipline.
Familiarity with the techniques used in statistical models is the main point that someone must master to understand Data Science. After all, within companies, it will be your role to choose the best approach to obtain results with data management.
It doesn’t matter what type of company you choose to work for – it is knowledge of statistics that will help you design and evaluate the effectiveness of a strategy.
- Programming
Every data scientist needs to master at least a little bit of programming. Languages like R and Python are the most used in the area and are considered essential for someone to gain a position in Data Science.
This goes for anyone who wants to work in any career linked to data. You don’t have to be an expert or the best programmer in the world, but learning them will put the profession’s tools in your hands.
When choosing whether to specialize in R or Python, consider which path you want to take. OR is used mainly by researchers and academics who deal with a lot of data. On the other hand, Python is the preference of those who already program and plan to start using data analysis daily.
- Machine Learning and Artificial Intelligence
Technologies like Machine Learning and Artificial Intelligence will also be part of your Data Science routine. With this in mind, it will be necessary to understand how they work and in what areas they can be applied.
Neural networks and decision trees will be terms that you will often hear and need to understand how these techniques work. They will help you deal with complex data science problems and make valuable predictions for the company you work for.
Always remember that Data Science forces you to deal with large volumes of information constantly. Mastering the technologies that make this possible is essential.
- Data visualization
Speaking of dealing with gigantic data collections, we must not forget that they need to be understandable. It is the visualization of data that makes this possible.
The resources with which data scientists work need to be translated into visual information, such as graphs, tables, and other imagery representations. Tools like Tableau will help you create better visualizations, but you’ll need to judge how useful they are to your users.
- Curiosity
Did you think that all the points on this list would be technical? The truth is that many soft skills are essential to building a good data scientist. One of them is curiosity. When working with technology, it is necessary to accept that it constantly evolves and accelerated. The desire to acquire knowledge is what differentiates good professionals.
Studying new techniques, software, programming languages, mathematical models, and visualization tools will be very important to evolve your career. Courses and other updating programs will help you keep up with the news in the area.
- Good communication
Any professional that did data science certification in Bangalore can benefit from the ability to communicate better, including those who work with Data Science. Being able to pass on ideas to your colleagues is the only way to make them benefit from the data at their disposal, and it is up to you to translate what they mean for the other departments of the company, such as HR and Marketing.
It is necessary to learn to speak the same language as other employees and use storytelling resources. Telling stories with the information you have is a practical way of transmitting them to less technical professionals and a characteristic of good data scientists.
- Good training
Currently, you can find out several pieces of training specifically created for you to understand Data Science. These are theoretical and practical courses that will introduce the main concepts and techniques that make an excellent professional and guide you through the type of material you must consume to improve.
Alone, the courses are not enough for someone to stand out in the area. It takes a lot of dedication and focuses for them to bring results. Certifications are just one way to prove to employers that you have the skills to do a good job.
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