It is beyond any doubt that Data Science is the most desired career path in this century. The optimistic estimates from credible sources show that the demand for data scientists far surpasses qualified data science professionals.
- Data Science is predicted to create 11.5 million new job openings by 2026, as per the US Bureau of Labour.
- Linkedin named the data science jobs as the fastest-growing.
- Estimated nearly 190,000 professionals shortage with Data Science skills in the United States alone as per McKinsey Global Institute.
The governments, universities and educational institutions across the globe have come forward to mitigate the shortage by facilitating, upgrading and creating new Data Science programs, aligned with the industry requirements.
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Who can pursue a career in Data Science?
Data Science is a multidisciplinary field combining statistics, programming skills, machine learning, and domain expertise to extract insights for business decision making. Though each field of Data Science is a vast subject by itself, we only need the applied knowledge of these fields in Data Science.
There is a common misconception that Data Science is related to software engineering and that only developers or programmers can pursue it. This is, simply not true. The real fact is that candidates with no technical expertise, with no background in computer science or information technology, are most likely to make the career transition to data science.
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So, Data Science requires applied knowledge of Statistics, Machine Learning and essential programming. In other words, NO hard prerequisites for pursuing a career in data science. Anyone with good analytical skills, data intuition and interest to learn Data Science fields can pursue a career in Data Science.
How to choose the right Data Science course?
Not surprisingly, the market is flooded with thousands of Data Science Courses from numerous universities and institutes. Also, there are a plethora of free Data Science courses.
These courses are offered in various formats, learning modes, durations and costs.
Top 10 areas to be considered while choosing the Data Science course:
- Learning Mode
- Curriculum
- Duration
- Batch Size
- Mentors/Teachers Profiles
- Industry Alignment
- Certifications
- Projects
- Internship Opportunities
- Job Assistance
Learning Mode:
There are many self-learning Data Science courses at the basic/foundation levels. As we move towards intermediate and advanced Data Science concepts, self-learning is not recommended. As you tend to waste a lot of time in understanding concepts as there is no option for clarifying your queries with a live mentor.
It is highly recommended to choose a course with a live instructor-led training option, either in-person or online data science training.
Curriculum:
The curriculum has to be comprehensive covering programming skills, statistics, and machine learning from fundamentals to advanced levels. It is recommended to select a course which is accredited by reputed certification bodies.
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Duration:
There are courses with various durations from one month to 2 years. It is important to analyse the training/coaching hours rather than the course duration. For example, a 6-month course with 20-hr/week learning hours is better than a one-year course with 4-hr/week learning hours. A 20-hr week provides the right momentum to learn Data Science concepts optimally.
A course of 6-8 months duration with 20-hr/week would be ideal.
Batch Size:
This is an important area many ignore when choosing live-instructor led training. It is NOT recommended to join courses with more than 50 learners as it is not possible for the mentors to provide personalised attention. In many cases, the mentors cover only simple concepts and avoid advanced or confusing topics to keep the queries at manageable levels.
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An ideal batch size would be 25 - 40 to provide a good learning environment as a group.
Mentors/Trainers/Coach profile:
It is recommended that the mentors/trainers/coaches have not only academic knowledge but also industrial experience in delivering real-life Data Science solutions. When choosing the Data Science Training, validate the mentors' profiles.
Industry Alignment
The course should be aligned with the changing industry requirements. It is recommended to use the current industry practices, platforms, and packages and do projects with industry-validated use-cases.
Certifications
The reputed Data Science Certifications add significant value to your profile and open windows for Data Science Job Opportunities. It is recommended to validate the credibility of the certifications.
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Data Science Projects
The best way to learn and master the Data Science concepts is by working on as many projects as possible. It is recommended to have at least 4 - to 5 end-to-end data science projects as a part of the course.
It is highly recommended to do a real-time project, a client project or a startup project, as it not only helps to appreciate the business value of a Data Science project but also adds significant value to your resume..
Internship Opportunities
Though not all courses offer internships as a bundle, it is highly recommended to explore courses with internships in AI companies as a bundle. A Data Science internship is a smooth way to transition to a data science career.
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Job Assistance
Getting job ready requires guidance from industry experts. It is recommended that the course offers Job assistance services such as resume fine-tuning, mock interviews, job assistance etc.
Why DataMites® for Data Science Courses?
DataMites® is a global Data Science and AI institute with more than 50,000 learners in the past 7 years of experience. DataMites® provides popular live-instructor-led courses along with in-person training in most major cities.
DataMites® Popular Data Science Courses
- Certified Data Scientist
- AI Expert
- Data Engineer
- Python Developer
- Machine Learning Expert
Among these, Certified Data Scientist is the most popular job oriented data science course.
DataMites® Certified Data Scientist Course highlights:
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- 7-month course, A comprehensive curriculum validated by IABAC®, an EU accreditation body.
- Live-instructor led training in most time zones.
- Mentors are industry experts with decades of experience, from reputed universities with PhDs.
- DataMites®' average batch size is 20, ensuring healthy mentor-learner interactions.
- DataMites® offers globally recognized certification from IABAC®, International Association of Business Analytics Certification along with NASSCOM Future Skills and JAINx - JAIN, Deemed to be a University.
- Offers 3 months internship is included as a part of the course.
- Proven Job Assistance service with the best in the industry track record.
Contact DataMites® for free Data Science counselling and Demo sessions.
