data science has been coined everywhere, and everybody wants to express their views and thoughts on this subject even though they are a novice or lack adequate knowledge about data science! The idea that everyone can become a data scientist only by studying a few technological advances and solving any complicated problems cripples the world today.
Let us first understand the career perspectives of data science. Data science has three pillars:
First, make it clear whether you want to become a data analyst, a data engineer, or a data scientist.
Education is known to be one of the primary sections of resumes and it is not going to change at all. Educational background serves a signal to the employers to better know about their future employees. When it comes to Data Science, you’ll find most of the professionals holding Ph.D. education. As per the data gathered by 365datascience, the typical data scientist in 2020 holds a Master’s degree (56%), a Bachelor (13%), or a Ph.D. (27%) as their highest academic qualification. The highest level of education achieved by data science professionals is a doctorate. Though, the considerable drop in being a data scientist is a bachelor-level degree only. The advanced levels are just to ensure a specialization in data science. We have discussed degrees! But what is the best degree to become a data scientist? To answer this, degree related to Computer Science or Statistics and Mathematics are inclined to data science proficiency. Data Science and Analysis graduates have made their room on the top of the research on the career path of becoming a data scientist.
Let me tell you a hack here! In reality, no single degree can prepare a person for a real job in data science. Even if you are post-graduate in data science, but you don’t have strong analytical and programming skills, you can’t be a data scientist.
Primarily, you can choose either of the three learning formats- Online training, Offline training, and Self-learning. You can avail of data science training from various platforms like Coursera, Deakin, Udemy, and many more. Offline training, on the other hand, can also be a great option if you have proper resources of data science learning available around you. If you are already in the profession and don’t have time to avail of both online and offline learning, then you have another option to explore, it is self-learning. What you need is to religiously follow various resources online and offline. You can subscribe to various YouTube channels providing data science training and watch the videos as per your time availability.
Solving real-world data science problems will only improve your practice in data science. But from where will you start? Working with the dataset with the classic Titanic data set with survival classification or clustering is likely to damage your portfolio, rather than help. Instead, consider taking ideas from shared Github ventures. Look at what others are creating based on the network that you acquired from LinkedIn through tech sessions and certifications.