Difference Between Paid And Free Data Science Courses
Data science aspirants can find countless courses on the internet to learn and master machine learning (ML) skills. This, however, creates a lot of confusion among aspirants, especially while evaluating the difference between free and paid courses. Therefore, they end up making several wrong decisions in their path towards a career in data science. Thus, effectively planning and evaluating their study plan is vital for aspirants to expedite their learning process to get a job quickly. Analytics India Magazine breaks down the difference between paid and free courses to help learners make the right decisions:- Mentorship In paid courses, mentorship is the most important feature for aspirants who fail to find solutions or need guidance in adopting best practices for career development. In paid courses, mentors come from a wide range of backgrounds, such as industrial, academia and more. This helps learners gain different perspectives, and gives them the freedom to get their doubts addressed. While the approach of mentoring differs, it is always good to have someone whom you can approach for answers. Nevertheless, one can still enrol in free courses and learn the same skills, but this would require a lot of research. Peer Community The ones who enrol in paid versions get the advantage of networking with students who are pursuing the same courses. This enables them to assist one another and overcome technical barriers while learning. On the other hand, aspirants who have opted for free courses are on their own, and their best bet is StackOverflow. Although the peer community is helpful, the difference is not significant as other students are also learning the same skills for the first time. Hence, they may not have answers to all your queries. Instead, gaining proficiency in finding answers on StackOverflow will be vital as you learn to read other codes, and implement it by modifying it based on your needs. Certification Most aspirants often take paid courses only because they think certifications will help them demonstrate their expertise on resumes. Undoubtedly, a few companies do look for applicants who have completed paid courses as it shows that they are serious about the domain. However, some companies do not evaluate aspirants with the courses they have completed and only focus on their projects and skills. Project Review As a beginner, it is difficult to determine where you are going wrong, and how certain techniques can be optimized to perform. This is where the reviewers in the paid courses are helpful as they provide feedback to assist learners. However, this is not a massive advantage since learners who have already completed the paid courses host their projects on GitHub. Since the projects in the course rarely change, aspirants who took the free courses can look at projects on GitHub and find the difference in the code to analyse the best method. Job Search Job search is another benefit you can avail if you opt for paid courses. Often, edtech providers collaborate with various companies and conduct job fairs only for students who have enrolled in premium courses. Besides, some edtech platforms send resumes to the companies they are associated with. Guided Learning Guided learning in premium courses helps learners focus on learning more than finding the best practices. For learners who take free courses, they do not get one complete course to enrol and learn. Instead, the free courses are devised differently. For example, you will find one short course for basics, another for advanced, and a few more for other dependencies such as SQL, version control, dashboards, and more. You will have to learn from different sources.
Data science aspirants can find countless courses on the internet to learn and master machine learning (ML) skills. This, however, creates a lot of confusion among aspirants, especially while evaluating the difference between free and paid courses. Therefore, they end up making several wrong decisions in their path towards a career in data science. Thus, […]
Identifying the difference between paid and free data science courses is not straightforward. Thus, AIM breakdowns the variation.
["Courses", "Data Science Certification"]
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["AI", "machine learning", "ML", "data science", "analytics", "R", "SQL", "Go", "Git", "GitHub"]
Rohit is a technology journalist and technophile who likes to communicate the latest trends around cutting-edge technologies in a way that is straightforward to assimilate. In a nutshell, he is deciphering technology.
Email: rohit.yadav@analyticsindiamag.com