Certifications and Training
Certification in data science: Get a certification in data science, such as a Certified Analytics Professional (CAP) or Certified Data Management Professional (CDMP), to prove competence in not just the technical aspects but also scientific principles of effective data science.
Cloud Platform Certifications: Certifications such as the AWS Certified Big Data – Specialty or Google Professional Data Engineer show competence in cloud-based data based solutions and services.
Vendor-Specific Certifications: Become certified by vendors, such as Microsoft (for example, Azure Data Scientist Associate), Cloudera (for example, Cloudera Certified Professional Data Engineer), IBM or others, in working with specific data science platforms and technologies.
Online Courses and Tutorials: Take online courses on Coursera, edX, Udacity or other sites to learn about data science in general, advanced techniques and special topics.
Bootcamps and Immersive Programs: Think about enrolling in the data science bootcamps or the immersive data science programs provided by the well-known institutions or organizations that offer the solid hands-on learning and the practical experience.
Workshops and Conferences: Join workshops, hackathons, and industry conferences in order to get informed of the current trends, technologies, and best practices in data science.
Self-Study and Practice: Read about textbooks, research papers and of course, online resources, while, at the same time, practice data science skills through personal projects, Kaggle competitions, or even some open-source contributions.
Networking and Mentorship: Network and obtain mentoring through a professional association or online forums and conferences between students and networking to obtain mentorship from data science architects thus, obtaining assistance in career path.
How to become a Data Science Architect?
In the changing business world, data science architects are the key people who lead the way in combining the new techniques of data analysis with the organization’s plans. They are the persons who move in the area where the data analysis meets the solutions that can be executed, thus the technological competence is brought into line with the business goals. Nowadays, organizations are becoming more and more data-driven, and thus, data science architects are becoming more and more important in this process. This introduction part is for the exploration of the pathways, skills, certifications and training which are the steps that the person should take to start the career in a data science architect, it will guide the people to master the art of converting the data into strategic assets.