Undoubtedly, Data Science is one of the most desired careers in recent years and has attracted tons of talented people from various domains and experience levels.
According to the World Economic Forum projection, there will be 11.5 million new jobs in data science by 2026, and data scientists will become the number one emerging role in the world. In the past few years, the demand for data science professionals has grown rapidly and hundreds of thousands of jobs couldn’t find qualified data science professionals and were left vacant.
Data science myths:
We see myths about data science going around. Here are the top 5:
- Data science is only for Maths geeks.
- Need to be a good programmer BB for a data science job.
- Data science is all about modelling.
- Artificial intelligence will soon replace data science jobs.
- Just a hype.
Well, none of the above statements are true.
According to DataMites, a leading data science institute with more than 50k learners, 70% of the candidates who successfully transitioned to data science careers are from non-IT and non-Maths backgrounds.
That brings a question, what exactly are the prerequisites for pursuing a career in data science?
Skills Required for Data Science
Let’s start with understanding data science itself as a practice, before dwelling on eligibility requirements.
In simple words, Data Science is the field of study that combines knowledge of statistics, programming skills, machine learning, and domain expertise to extract actionable insights.
Domain expertise is gained through many years of experience and is usually not expected from a data science professional. Based on the data science project nature, subject matter experts are involved to contribute towards domain expertise.
So it comes down to statistics, programming and machine learning.
Statistics is a vast subject and what you need for data science is limited topics from quantitative statistics. Based on the data from DataMites learners, it takes about 60 learning hours spread over a month to gain necessary statistics skills for someone with a decent foundation from high school and graduation mathematics.
Programming, specifically Python, is a necessary skill, as it provides means to gather, manipulate and analyse large amounts of data without any constraints. Data Science professionals need not master programming as a software developer, but essential programming skills to prepare the data for data science modeling.
DataMites learners with no programming skills take about 80 hours over 4 weeks to gain the required level of programming skills for Data Science.
Machine learning has become a major tool kit for Data science to analyse large amounts of data both structured and unstructured, to create predictive analytics models. The recent popularity of data science can be attributed to the adoption of machine learning. Machine learning is an advanced field and creating a new machine algorithm can be quite a complex task, but fortunately, data science professionals only need to worry about applying the machine learning algorithms and fine-tune the model performance as per the data and business case, also known as applied machine learning.
A beginner can gain a good knowledge of applied machine learning in about 150 hours over 8 weeks.
Data Science Roles:
Data science offers a broad spectrum of opportunities not only for beginners but also for experienced professionals from various industries and hierarchical levels.
Data science roles in business areas: business leaders, delivery managers, head of data science practice, account managers don’t need programming or technical hands-on experience. Though, they should have a good understanding of how data science machine learning models works, possibilities and limitations, so that they can make the right decisions at the business level.
Data science roles in analyst and functional areas: data analysts, process consultants, visual analysts, may not require hands-on experience on machine learning modeling but a good understanding to perform their functional roles.
Data science roles in technology areas: data engineers, machine learning modelers, data scientists, involves data gathering, manipulating data and designing machine learning models, thus requires hands-on knowledge on programming, machine learning modeling etc.,
No hard prerequisites, you are eligible!
In a nutshell, there are no hard prerequisites for pursuing a career in data science. If you enjoy working with data, have good analytical skills, and like solving problems, you can learn the necessary skills for a data science role to start your Data Science career journey, irrespective of your academic background, current domain and years of experience.
Data science provides millions of job opportunities across industries and various experience levels. As we see, this trend will continue growing in the coming years.
DataMites, a leading institute for Data Science.
Mentors play an important role in the lives of people looking to achieve new levels of success in their careers. DataMites’s qualified mentors essentially provide a structured learning approach to get you market ready for a data science job
DataMites is a leading institute for data science with nearly a decade of experience training more than 50,000 learners. DataMites mentors are industry experts, Ph.Ds in the field of data science, analytics and AI and the course curriculum is accredited by global data science certification bodies, in line with industry standards. DataMites offers a wide range of data science courses for beginners as well as working professionals in all learning modes.
Speak to DataMites counselors for free expert counseling.
DataMites: https://datamites.com/
COMMents
SHARE