A Journey of a thousand miles starts with a single step.
Ever since MOOC’s democratized education, all the resources that a student needs to learn or acquire a new skill is easily available to everyone. MOOC is changing the current education paradigm, by enabling millions of people around the globe to get the education they deserve, but couldn’t. Also, the students on completion of the program are provided with a certificate of accomplishment, which serves as proof of their expertise in the skill. Today, students and professionals are widely encouraged to enroll in these courses to improve and learn new marketable skills. Every coin has two sides, so does MOOC. MOOC systems are still evolving, they are not stable yet. One major drawback of MOOC’s is the assessment system — MOOC platforms currently do not have a solid assessment system. i.e. The students can be bestowed with these certifications, without really working on the coursework or attaining proficiency in the subject. This is causing a serious imbalance in the job market today. People falsely claiming to be experts, on the basis of these certificates are diluting their value. Candidates with actual skills are only a fraction when compared to the previous members. This is a commonplace scenario in niche technologies like Machine Learning, Deep Learning, and AI.
I was speaking to a technical recruiter a while back, and the experience from one of his interviews really left me wondering. With nearly 80% of the candidates having a minimum of 2 certifications in Machine Learning or Deep Learning, many of them couldn’t answer the questions related to the subject. That conversation made me realize that Certificates are not an effective metric to evaluate a candidate. Certificates indicate that the candidate has been exposed to the subject, but doesn’t necessarily prove that the mastery over the skill.
After my recent realization, I started to reevaluate my approach and priorities. A couple of years ago, I was obsessed with these certifications too. I completed about 12 courses and accumulated the certificates only to brag about them on LinkedIn. It was meaningless, it did nothing fruitful. I rarely used the knowledge I gained from many of those courses in my routine. I don’t want to make the same mistakes. So I’m mindfully shifting my focus — Certificates are no more a priority, Gaining knowledge and mastery is the ultimate destiny. I’m still going to use all the best resources available on the internet, but now with a different perspective. I strongly believe that I will have a deeper understanding of the subjects by following this approach.
As mentioned previously, I don’t want to learn this and never use it in the future ever again. I want a fruitful outcome to keep me motivated and feel satisfied. Experts suggest doing a project to practically implement the knowledge learned through classes to better understand and retain the ideas (A typical ‘Learn by Doing’ approach.) ‘The Highly-Ambitious Me’ came up with an idea to do 100 Projects related to the Machine Learning/Deep Learning. The ‘Rational Me’ was super excited and super freaked about this idea. A very big commitment and it requires a high level of consistency, patience, and perseverance. The benefits are equally high. So, I decided to go ahead and committing myself to work on this insanely huge and equally interesting challenge.
#100MLProjects — I wanted to come up with a super cool name but decided to stay with a simple one because there is a ton of work to start doing. 100MLProjects is a Challenge where I commit myself to learn Machine Learning and Deep Learning concepts by doing 100 projects. I’m going to start from scratch starting with simple projects and keep increasing the complexity as I progress through the challenge. I’ll make a blog or a video-log for every project that I complete as a part of this challenge, so other interested people can follow through as well.
If you have reached this final section here! Thank you very much for reading till here! Wish me luck! I would love to hear your feedback, suggestions, criticisms, comments, or ideas that you think will help me in this journey.
To Professionals/Experts: I would love to get suggestions, comments, and guidance from you.
#100MLProjects
