What Is More Beneficial for Data Science Career: Projects or Certifications?
Imagine! Just a few days ago, you had an interview for a data science job with one of the finest IT companies in the world.
You start working today!
How did you beat the competition and leave all those resumes behind?
It was not due to your education that you so diligently wanted to complete. It was because of your data science portfolio, your projects, and your data science certifications that you earned and showcased there.
The question that arises here is:
Should I pursue a data science project or a certification in this situation?
Let’s find out the answer…
Data science certifications and projects will strengthen your resume
Despite the industry’s demand and supply imbalance, it has always been mind-boggling to find a job in data science because it is nearly impossible to be a great fit for every company you apply to.
It is certainly necessary to take advantage of all available platforms and tools to differentiate yourself, but as an aspiring data science professional you should also prioritize and embrace the best approach. A haphazard adoption of numerous strategies today is leading to burnout among aspirants.
Let us first discuss the need to earn and showcase certifications in your data science portfolio.
👉 What’s the point of earning data science certifications?
Did you know!
It is difficult for employers to locate qualified data science professionals, as evidenced by the fact that 85 percent of AI and data science projects fail for a lack of suitable employees. Skills and frameworks learned from Data science certifications can save the day and give you the tools required to succeed in your projects in this situation. It is a highly beneficial time to take advantage of data science job vacancies through certifications to enhance and expand your skills in this field.
Stella Morris, Data Scientist at SAP:
I used open-source software to hone my programming and machine learning skills, but subsequently, I applied to a data analytics certification program. I was able to acquire various modern data science abilities thanks to their curriculum, which I then applied to some projects. I put these projects in the spotlight on my CV, which helped me scrape together the kind of living I’d always desired.
By earning data science credentials, you will be able to:
- Showcase your interest in self-driven learning: Only those professionals who have the most recent and up-to-date skills reflected on their portfolios stand a chance of being chosen from the hiring manager’s candidate pool in today’s competitive job market. It demonstrates to hiring managers that the applicants are self-driven and sincerely committed to their job search and career goals.
- Crack the job with handsome salary packages: Earning a data science certification sets a candidate apart from the competition and distinguishes them as having put in hard work, time, and energy as well as having gained practical experience and acquired skills by devotedly completing the certification course. Companies and hiring managers across the spectrum fully recognize how challenging it can be to secure and earn a certification. Your CV will demonstrate that you have invested in learning about data science, as opposed to being a list of highlights that the applicant hopes the hiring managers will find interesting. A recent Payscale survey suggests that entry-level data scientists make an average of USD 85,733 per year, which is quite high compared to other occupations.
- Ace the contemporary industry skills and techniques: It will be possible for you to gain a variety of fresh facts on how the subject of data science is developing and what the most recent advancements in it are. If you complete your professional certification. If a company is looking to hire candidates for positions linked to data science, such as data scientist and data analyst, you will be an invaluable resource if you have cutting-edge talents.
- Work in any type of industry: Data science has broad and diverse uses in a wide range of other areas, including government, construction, transportation, banking and finance, communications, media and entertainment, education, and healthcare. With the best data science certification, you will be able to work in all of these fields as a solution architect, data scientist, project manager, statistician, or business intelligence specialist.
Bear in mind! It is imperative to obtain certifications from reputable and well-known online certification providers. Institutions such as IBM, DASCA, Google, and SAS can provide you with credentials and help you get the data science horsepower you need to boost your career and seek out the best jobs.
Let us now discuss data science projects.
👉 Data science projects are weighty
Projects show how adept you are at overcoming difficulties in the real world. Developing projects that are close to your heart does more than only showcase your talent, it demonstrates your passion for your work. Data science projects and certifications go hand in hand; to work on projects, you must have a firm grasp of programming and data analysis skills that you can learn by earning data science certifications. Before working on projects involving data science, consider obtaining credentials. Some projects that can help your resume get noticed are:
1) Regression projects:
Regression-based projects, often considered a vital tool for data science professionals, are the first ones you ought to take into consideration. The procedure of regression is employed to assess the degree to which two variables are related to one another.
Regression tasks you could carry out include:
- Finding familiarity between age and voting behavior
- Predicting employee salary
- Predicting frauds and so on.
2) Sentiment evaluation projects:
The method of locating and calculating the attitudes and feelings contained in a text is known as sentiment analysis. Data science professionals should be familiar with sentiment analysis since it may be used to understand customer feedback, product reviews, and even stock market patterns.
You should think about completing the following projects using sentiment analysis:
- Analyzing Amazon’s product reviews
- Analyzing IMDb reviews
- Gaining insights from customer feedback etc.
3) Natural language processing (NLP) projects:
Understanding and retrieving data from text data is known as natural language processing (NLP). You will learn the fundamentals of NLP and how to obtain information from text data through this kind of assignment. Because it may be used to assess consumer evaluations, product ratings, and even legal papers, NLP is crucial for data scientists to understand.
Consider working on the following projects involving natural language processing:
- Extracting data from legal documents
- Extracting information about tweets about a firm or its contenders.
Wrapping up…
Consider earning the best data science certification and completing the projects to give your resume a lift and make it stand out. There are many ways that these projects can demonstrate your data science skills, from developing an artificial neural network or NLP algorithm to evaluating customer comments and product evaluations for insights.
Professionals in this field should also understand the importance of communicating these skills and projects on the right platforms such as GitHub, Medium, and LinkedIn.
