9 Essential Tips for Beginners starting a Career in Data Science

Advancements in science and technology have helped data science evolve. From being about generating datasets, it has become something much broader. Modern data science career paths are very diverse. All the fields offer a plethora of applications. Data science for beginners might appear like the processing of data. However, the field is about much more than that. In fact, data science also includes analysis, predictions, mining, machine learning, and so much more. Rather than only being a trend, a career in data science will help you be a part of cutting-edge technology. Since most businesses now have to process volumes of data, the field of data science is becoming more important than ever before. So, how exactly does one build a career in data science? Here’s a look at a few tips to help get through data science for beginners. In this article, we will also look at the various data science career paths and opportunities.

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What is data science?

Data science is a field of science concerned with collecting, storing, managing, processing and analysing data. It helps process and sieve through large volumes of data at break-neck speeds. It is an important process as it helps large organisations take integral data-driven decisions. Almost every single interaction we have with technology involves data. Whether it is your latest online purchase or a Netflix recommendation, everything makes use of data to accomplish its objectives. 

Data collection is vital for businesses. It gives companies important information involving customer behaviour. Amazon uses our search history and purchase history to suggest products you might like. Netflix also makes use of data regarding old shows we have watched, to suggest new ones for us. All of this happens thanks to data science. Data science also helps companies detect, analyse and pursue habitual purchases. Therefore, in many ways, data science helps both the consumer and the corporation.

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Scope of data science

Data science enables retailers to understand their customers, and customers to get the products they want. However, the scope of data science extends much further. Data science career paths play an integral part in several important industries and fields. For instance, by using wearable tech, data science can help healthcare workers track patients. Within the medical field, data science can help improve diagnostic accuracy, early detection of diseases and even accelerate drug development. 

For example, then Ebola broke out in Africa in 2014, data scientists tracked its spread and listed the most vulnerable areas and people. This helped government authorities focus on those areas and target groups, helping them prevent a massive outbreak. Therefore, a career in data science can literally help you save lives. If that wasn’t enough, data science also helps farmers grow crops more efficiently, food packagers cut back on waste, and NGOs boost their funding. Big data also helps scientists and researchers push the boundaries of science on a daily basis. It speeds scientific research, while also helping companies take beneficial economic decisions. 

All of this makes the future of data science very promising. Therefore, students must be encouraged to chase after careers in data science. Since it is vital in almost every industry, data scientists are in demand around the world. Everyone from Google and Amazon to NASA and Disney, need data scientists to process their data. Every field from digital security to the restaurant business makes use of big data to succeed and improve customer relations.

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Data science career opportunities

1. Data Scientist: Helps companies find, clean, manage, organise and process their data. These professionals sieve through large amounts of raw data. They find patterns and then use those patterns to make informed decisions.
2. Machine Learning Engineer: Help companies create data funnels and software solutions. These help to address company requirements. These professionals require a strong background in maths, statistics and programming. They help in designing, developing and operating ML systems.
3. Machine Learning Scientist: They help research and create new approaches for processing data. They look for new algorithms, techniques and methodologies to build adaptive systems. 
4. Applications Architect: These professionals help track applications, analyse interactions and review performance. They also help with building and designing new software for the company.
5. Enterprise Architect: Such professionals are responsible for ensuring that a company finds the right tools to implement and achieve its objectives. They understand the company’s requirements and then design the required architecture.
6. Data Architect: These people help ensure that the solutions built are as efficient as can be. They help create new database systems and also work towards improving the existing architecture.
7. Infrastructure Architect: They play a supervisory role, ensuring that the business system works flawlessly.

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9 Essential Tips for beginners starting a career in Data Science

1. Make sure you choose the right role within the data science industry. There are quite a lot of data science career paths, which all laid down different roads. Therefore, before you start, make sure you are clear of what area you want to explore. A data scientist, engineer, ML expert, AI expert and visualization expert, all do very different work. While they follow the same guiding principles, the nature of work performed is very different. Make sure you do enough research and understand the subtle differences before making your choice.

2. Talk to people in the industry and gain an idea of how it works. This will help you understand what skills you need to pick up and how best to do it. Talking to people will also help you gain insight into what projects you will be a part of. Furthermore, try taking up mentorship from people in power so that you figure out what area your skills best suit.

3. Take up data science for beginner courses so that you have the theoretical knowledge required. Put in the dedicated effort, and go through textbooks on the subject. Find the right material through online courses to build a profile suitable for a career in data science. Take up an online course in data science for beginners, and follow up actively. Go through all the coursework, submit all the assignments and take part in discussions.

4. Decide on a tool or language and keep working on it till you get adept at using it. It is important that you build hands-on experience in such a field. Therefore, make sure you put in the time and effort required to master the skills needed.

5. Join a community or peer group to actively take part in discussions and projects. Being around people who share the same passions will motivate you to try harder. This way you will have people to discuss with and grow along with. Interact with such people as much as possible and try to learn something new from them. Everyone has their own unique approach, and sometimes you can pick up valuable skills from strangers.

6. Do not get too swept up by the theory and forget building practical knowledge. Like all disciplines associated with coding, practice is key. You need to constantly work on projects and assignments to build practical know-how. Though the theory is important, nothing can be more influential than figuring out the process on your own.

7. Read up from the right resources and explore different niches. Dig up as much knowledge as you can, and go through everything you find. Go through blogs run by popular Data Scientists to keep yourself updated regarding what is happening in the field. Read journals and research papers so that you are aware of the newest technologies available.

8. Do not neglect your communication and social skills. Though you need a lot of technical knowledge, data scientists need to work with other people. Hence, you need to learn how to be a part of a team and work together with other people. The biggest skill you can have when working with others is being able to communicate effectively.

9. Network and build your connections within the field so that you build relevant experience. Doing so will also help you build confidence and work on important projects. As you progress, take part in conferences, meetups and hackathons to keep yourself aware of what is happening within the industry. Talk to community leaders and build good relations with them to advance your career in data science. 

The demand for data science will only grow in the future. Therefore, young engineers should keep their eyes open and work towards improving their skill sets. Take up data science for beginner courses, and work on projects to gain more knowledge and set yourself up for success!

Learn data science to develop a successful career

9 Essential Tips for Beginners starting a Career in Data Science