What’s the Best Way to Prepare for a Career in Data Science/Machine Learning?
By: Miguel Saldana
Tags: Learning, Self Improvement, Machine Learning, Digital, Data Science

University Enrollment (Undergrad/Graduate Degree, Short Courses, and Boot Camps)

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The traditional learning method for individuals to gain new skills and pivot their careers is to attend a classical university and enroll to get a degree. The degree is usually an individual milestone that companies and organizations accept as verifying that someone has attained the skills that they need to be successful. For this reason, these types of programs are still heavily favored by those who can afford the time and money it takes to complete them. I’m currently in an accelerated Computer Science program with a concentration in Data Science. I’ve been extremely lucky that the company I work for has selected me for this role and is covering the cost of the program and allowing me to be on a sabbatical until I complete the program. I would say one of the biggest benefits of this mode of learning is having interactive discussions with professors and classmates, as well as to discuss the common error traps, useful tips, and build connections. A good example of this is prior to starting my program, I would be heavily reliant on sites like stackoverflow.com, Github, as well as Medium articles to try and solve coding and/or issues with things that I was learning. One thing that a novice (who uses these sources as unquestionable truths) may not understand initially is that not all content is created equally, meaning there is a lot of erroneous and less than ideal things put on these sites since it is crowdsourcing for a solution. Learning from trusted and reliable sources like the professors and the coursework has helped guide me to start to be a better searcher (and interpreter) of these sites and how to understand whether or not it makes sense and is actually going to help me with my problem. Another example is how by taking an online course or self-learning coding you may feel a bit overconfident in where your actual competency lies. For a long time I felt I was making major strides, but really didn’t understand a lot of core things about the base Python language, rather I was really good at importing packages and calling functions. When I was put into a traditional classroom setting with assignments, I quickly realized I needed to focus on the base things to get me to script and code in a more efficient manner. These are just a few examples of how I feel the traditional university route could be helpful, but it does come at a hefty price for both money and time needed to complete. There are other options like graduate degrees if you already have a STEM degree (and still costs a sizeable amount of money but less time than an undergraduate degree). In addition, there accelerated non-degree programs like boot camps and other short certificate courses that you can enroll and take. These give a variety of options as well to go down this route. Many renowned universities like Harvard, UC Berkeley, and MIT all offer some sort of boot camp and/or online degree program that you can take. From my own experience, I would like to believe this is the most effective method of learning due to the added interaction you get with people and network-building opportunities, but it does come at a cost.