How to choose the right data science course?

How to choose the right data science course?

Over the years, data technology has advanced at a breakneck pace. It is currently the foundation of numerous enterprises across various sectors. Many people desire to be data scientists, but it’s essential to assess the benefits and drawbacks of the profession. Many professionals take data science training to stay updated on industry advancements and learn how to deal with problems. Conclusion: there are the best certification courses for computer science engineers that include Data Science subjects. Here are a few things to consider before enrolling in data science courses that can help you find work.

How to choose the right data science course?

  • Be clear on where you want to specialize.


Being a data scientist is only the beginning. While many aspire to be one because it was named the “sexiest job of the twenty-first century” by the Harvard Business Review in 2012, there are other roles in the data value chain that are equally important, in-demand, and even more rare given the needs of most businesses, particularly in the Philippines. The Data Steward, Data Engineer, Data Scientist, and Data Analyst are the four primary jobs in data science and analytics, according to the Analytics Association of the Philippines (AAP). And each of them would have a set of talents that was distinct from the others. But that’s a matter for another day.

  • Have an honest assessment of your current skill level.


I can’t emphasize this enough: don’t act like you’re someone you’re not. Knowing what you don’t know and having the acceptance and drive to acquire and study new abilities, no matter how unpleasant or intimidating they may seem, is the first step to learning and becoming more than you are today (at first).


When I took the AAP’s Analytics Professional Maturity Assessment, which was based on the APEC’s Project DARE (Data Analytics Raising Employment10 )’s Analytics Competencies, I wanted to be brutally honest, mainly because it was a self-assessment test.

  •  Plan out your budget accordingly.


Massive open online courses (MOOCs) like Coursera, edX, and Udacity have exploded in popularity, making excellent education accessible to people all over the world. Technology has changed the education sector, allowing everyone to gain new skills, develop their careers, and offer high-quality educational experiences at scale and speed.


Coursera, for example, allows you to acquire a data science certification course from leading colleges across the world for as little as US$49 (approximately PhP2,500) every month. You may legally put these in your CV or LinkedIn page to bolster your qualifications.

  •  Consider the time and mind space you are willing to put in.


If you want to take this seriously and enjoy the benefits as soon as possible, you’ll need to consider how much time and effort you’re willing to put into learning data science and analytics. Suppose you are presently working or operating a business. In that case, you may want to consider taking online courses at your speed, enrolling in courses with after-work and weekend schedules, or enrolling in 2–3 day Bootcamp training if you cannot afford to be away from work for an extended time.


It could appear that becoming a data scientist is a challenging task. To be quite honest, it is not straightforward; it, like any other learning experience, will need time, practice, patience, and perseverance. On the other side, a college diploma will not be necessary.

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