In 2012, Data Science was tagged “The sexiest job of the 21st century” by technologists Thomas H. Davenport and DJ Patil, and it is no news to anyone, the rise and importance of the role in many fields due to the vast amount of data generated in our daily activities. It is predicted that data science jobs will experience a 36 percent growth between 2021 and 2031, according to the US Bureau of Labour Statistics. Data science is an easy discipline to learn and with the right guidance, holding your hands along the way.
This article is aimed to provide new professionals looking to move into Data science in 2023 and beyond with all the information needed to start this new journey. We will explain what data science is all about, the requirements you need to become one, career paths in Data science, what you can do to move fast in the space, and other related resources.
What is Data Science?
According to Wikipedia, Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data. It is centred on knowledge extraction from frequently enormous data sets and applying the knowledge and insights from that data to address issues in a variety of application sectors. In a wide range of application disciplines, the field includes preparing data for analysis, framing data science challenges, analysing data, generating data-driven solutions, and presenting findings to inform high-level choices.
Data science plays important role in the society that we are today as it is used in addressing crucial issues such as healthcare, policy making, climate change, and economic related issues. Many organizations, businesses, individuals, and governments makes use of data science to make informed decision.
How can I become a Data Scientist?
There are two aspects that we should consider when looking to move into the data science space. It is really expedient that you have experience in both aspects as this will really help you to flourish in this field. These two aspects are;
• Academic foundations
• Learning the required tools
For you to begin this journey, it is required that you have some knowledge in mathematics and statistics. They are not the core parts of these courses and they are easy to know if you put your mind and heart to it. Areas where you need to cover are Descriptive statistics, inferential statistics, Linear Algebra and Single and Multi-Variate calculus which you can learn as these courses are available online. If you are also looking to specialize in maybe a sector either Finance, Healthcare, or Policy making, it is good to have fore knowledge about these areas because it will help during visualization.
There are some tools you need to learn and this is chosen based on what you want to do and your own preference but it is important that you learn the required ones useful for you or useful for the type of problems you will be solving. The popular tools you should learn are; Python, SQL, R, Power BI, MySQL, Matplotlib, Tableau and many more. These software have their unique functions and it is good to make proper research before you commit to them.
To make the work easy as you go on this journey, you should look into programming topics like common data structures (e.g, dictionaries, lists, sets, tuples), control flows (e.g, for loop, while loop, if else statement, and so on), writing functions, object-oriented programming, and how to work with external libraries and frameworks (e.g, NumPy, Pandas and so on).
Git and GitHub
As a programmers, one of the places you should have online presence is GitHub. It helps to not online show your work to others in the space, but can be a place you find solutions to some of your programming issues. GitHub can serve as a place for your portfolio which you can share with potential employees if it is well built. Some of the advantages of having an account is that you can share your knowledge with everyone, you can give access to your code if you want them to fix something for you, and you can also find confidence or criticism for a work done which can be good encouragement for future work. You should take your time to learn how to use it because it will come in handy as you move along this path.
Career Paths in Data Science
Data scientists are multi-talented professionals and there are several roles in data science ranging from less technical to very technical. You can start your journey from the less technical then work your way up the ladder. Some of these roles are, but are not limited to;
• Data Analyst
• Data Scientists
• Business Analysts
• Data Engineer
• Data Architect
• Machine Learning Engineer
• Analytical Engineer
Some tips you should bear in mind to help you grow fast in this ever revolving and improving career are;
• Networking
• Attending Bootcamps
• Working on Projects
Networking
The first thing you should do when you realise that you want to walk in this path is to join a community. Communities provide a safe space to help you move at a fast pace as they are available when you run into issues and a form of support when you need encouragement. They also provide useful materials when you need it. It is also good to have a mentor but not necessary. Strive in joining one immediately and you can join more than one but be careful to when choosing one so that you don’t miss a path/jump on the roadmap.
Attending Bootcamps
Another way you can get to move fast is through the help of Bootcamps. Bootcamps provide a structured model of a good roadmap which will help you realize your goals quickly. They also provide communities as you are not the alone on this journey, there are several people just like yourself. You also get to meet professionals in this fields who share experiences that are useful along this journey.
Working on Projects
This is the next step after you have completed your learning path. This will help you to start building your portfolio for future jobs. It will not only build your portfolio, it will help you further understand the concepts and give you hands-on experience. You should do as many projects as you can to help you achieve these things.
Data science is one of the lucrative jobs in our world today and more roles will still be created as we continue to unravel how data can help in making our lives better. The world needs more data scientists and there are both free and paid platforms where you can start from. Do you see yourself in this profession? Start your journey today!
Top comments (1)
Nice