Looking to upskill in data analytics? Here are 7 tips for selecting the right course
By Ravikaran Peesapati, Executive Director Employability Business – Imarticus Learning
The economy today is primarily supported by data-driven insights to make major decisions. It would hardly be an exaggeration to say that data is the basis for a sustainable and profitable business ethos. Unsurprisingly, data scientists and analysts are in demand, and companies are willing to pay substantial amounts to onboard skilled professionals in this domain.
However, with the sophistication of technology, these professionals must continuously upskill and remain abreast with the latest developments to remain relevant. They must choose from a myriad of platforms offering upskilling courses to find the right fit in accordance with their job role and industry readiness. Additionally, those who want to make a career in analytics must decide if they want to opt for a full-time course or pursue a degree online along with their regular jobs. Here are seven tips that may help you make a better decision regarding course selection.
Determine your goals
The first step for course selection is to have a comprehensive estimate of your needs and aspirations. You must ascertain if you want to upskill, reskill or opt for an entirely new career trajectory. These goals would determine the kind, of course, most suited for you.
Look for a course with a practical approach
The field of data science entails entangling real-world problems. Therefore, it is imperative that the course you choose should give due importance to practical skills acquisition and provide hands-on training using industry-standard tools and techniques. Students should opt for courses that offer them opportunities to work on data sets, practice data cleaning and preparation along with visualisation and statistical analysis. These will help the learners to solve real-world problems and make them industry as well as job ready.
Consider the course content
The field of data analytics is evolving continuously, with new technologies coming to the forefront every now and then. The course curriculum is thus a central tenant of any upskilling program in the field. One must choose a platform that offers a syllabus designed by experts in accordance with industry standards. Learners must carefully study all aspects of the course material and ensure it is not a cheap copy of content already available online. The important topics a course should cover include data mining, data visualization, statistical analysis, and machine learning.
Additionally, you must take the time to familiarise yourself with the faculty members, their qualifications, and their professional achievements. This information will help you gauge the quality of the content and the pedagogy.
Check the course instructor’s credentials
The hallmark of a good course is the credibility and repute commanded by its instructors. Further elaborating on the aforementioned point, it is of utmost importance to look into faculty members’ academic qualifications and industry experience before opting for a course. A good teacher will be able to deliver course content in an easily comprehensible manner and cater to the learning requirements of a wide range of learners.
Check for reviews and recommendations
A good way of determining course efficiency and quality is to read the reviews and recommendations of those already enrolled in such courses or those working successfully in the field. Such assessments will help you gain insight into the specificities of the course and evaluate its underwhelming and compelling aspects.
Consider the course duration and format
A noteworthy quality of a course in data analytics is that it can be customized to suit one’s needs and time requirements. Since these programs can be of varying lengths and formats, learners can choose to attend an online self-paced course or a full-time university curriculum. The choice should be guided by considerations like the time available and the style of teaching preferred.
Look for additional resources and support
Possessing knowledge of the specificities of data analytics is essential. However, this knowledge is useless if one cannot market oneself adequately. Simply put, one should know of the opportunities in the field, be able to contact people of interest, and showcase their skills in a way that impresses the potential employer. Therefore, a good course should offer additional resources and support, such as online forums, mentorship, and career services.
Moreover, in cognizance of the fact that building a career in this field requires excellent communication skills, the course should offer training in resume building and conducting oneself in an interview. It is also essential to check the hiring partners of the platform to ascertain the career-building opportunities accorded post-course completion.
Bottom line
The hiring ecosystem has changed substantially over the years. Employers now prioritise skill possession in addition to the educational qualifications of the applicants. This is especially true for those who want to pursue a career in data science or analytics. Therefore, there is an upsurge in the number of ed-tech platforms offering various courses in this segment. However, students must be meticulous in choosing the course as this may determine their career trajectory. The platform of choice must offer a holistic curriculum that provides an engaging learning experience.
