With internet growth and digitization, data is at the heart of modern technological breakthroughs, giving the globe a platter of limitless options and possibilities. Data science has played a pivotal role in driving innovations in today’s modern society, and advancements in the data science field are expanding at unprecedented rates due to the incorporation of machine learning and artificial intelligence tools and techniques that help organizations extract valuable insights from massive volumes of data at their disposal. From being named the sexiest job of the twenty-first century by Harvard Business Review a decade ago to recently making the cut as one of the top three jobs in the world according to Glassdoor, with employees earning a national average salary close to $110,000 per year, it is not surprising that more professionals want to pivot and switch careers to enter the data science realm.
So, can earning a data science certificate help one make the transition into a data scientist career? If you are expecting a straightforward Yes or No response, you may be disappointed because the correct response is a little more nuanced. However, obtaining a data science certificate can unquestionably set you on the right learning path and make your journey a little smoother. If you are considering a career as a data scientist, keep reading since this article will provide information regarding the basic trivia that can help you get started.
What is a data science certification?
Data science certificates are widely accepted, business-backed credentials. To earn certification, candidates must first take and pass a qualifying exam. Hence, one’s extensive knowledge and skill sets in the technologies and techniques used in data science are validated via these exams. Data scientists must keep up with the most recent industry reformations and standards, update their knowledge, and add new skills to their toolkit if they want to stay relevant because the field of data science is still relatively young and is undergoing radical changes because of technological advancements.
Can earning a data science certificate help you switch careers?
While a data science certification confirms your expertise and industry knowledge, which might help you stand out in front of recruiters among a pool of like-minded individuals, it cannot be considered a golden ticket to enter the data science realm. The skills and advanced information gained while finishing a certification program, on the other hand, can help you develop a successful profession. To be a data scientist, one must have a diverse skill set that includes understanding of data science tools and frameworks, technical acumen, expertise in mathematics, statistics, and programming languages, and real-world practical experience. By learning about the most recent developments in the field of data science and keeping up with the most recent skills and tools needed for starting a successful career in data science, earning a certificate can help set you on the path to becoming a data scientist.
A candidate who has earned a certification demonstrates to recruiters how much dedication and work they have put into meeting the exam’s requirements, conveying a sense of sincerity and professional aptitude. Numerous areas, including government, banking and finance, media and entertainment, healthcare, and education, can benefit from data science. If you have a data science certification, you can work in these areas as a solution architect, data scientist, project manager, or business intelligence specialist. Credentials are also a great method to increase your income, grow in your profession, and increase your job options.
How to make the career switch to data science?
Here are the basic steps you need to follow to ensure a successful outing in the data science field.
1. Enhance your technical aptitude
The first thing that you need to do if you want to make a switch to a data science career is to learn programming or coding as these are crucial for analyzing data. A data scientist should be proficient in programming languages like Python, R, SQL, or Java. SQL, or Structured Query Language, is a sophisticated programming language that can be used to manage data stored in relational databases. Knowledge of SQL is extremely vital because it allows data analysts to perform activities such as data updating and retrieval in their company’s databases. Python is one of the most frequently used general programming languages and has been used extensively in the fields of data science and analytics. Another language, R, is a free and open-source statistical computing or data analysis graphical language.
Along with learning programming languages, proficiency in mathematics and statistics is absolutely crucial if you want to become a data scientist. You cannot skip gaining knowledge in machine learning and deep learning techniques and tools like modeling techniques that include sedimentation and segmentation, Tensor Flow, artificial neural networks, etc.
2. Cultivate or build on your soft skills
Following are some of the soft skills that can put you ahead in your game:
· Communication skills
· Teamwork
· Flexibility
· Critical thinking
· business acumen
3. Conduct research on suitable data science roles that matches your technical prowess
A data scientist’s responsibilities are adaptable. Because data science contexts are diverse and unmatched, each data scientist will have a unique experience and understanding of their work. Choosing the areas and categories of data positions in which you want to work is thus the first and most important stage in your path to data science when changing careers.
4. Earn a certification
For additional knowledge and developing job-ready skills, enroll in certification programs that have a well-structured curriculum, which will assist you in developing the necessary skillsets and provide you the opportunity to gain real-world practical experience. Moreover, you stand to learn from industry experts, and upon successful competition, you are awarded the certification, which validates your expertise and technical prowess and helps you stand out amongst a sea of competitors.
5. Networking
By networking, you can learn more about the job and discover useful information. For instance, a seasoned data scientist can suggest the finest programming languages to learn so you can concentrate on learning them to support your application to potential employers. Additionally, it could aid in your comprehension of the job market and the requirements of employers. Building a strong network is the greatest approach to obtaining internal referrals.
