Learn Data Science Without being Frustrated !!

Over the last year, I’ve had to work very hard to maintain my motivation to learn data science. I made my own curriculum entirely from (free) web resources, and each day, no matter my level of motivation, I set aside at least few hours towards expanding my skill set.

However, this last year has also seen really hard days. Days where I struggled with my motivation and almost gave up despite all I have done.

In my experience, no matter what path you take towards data science, you will face challenges that threaten to extinguish your motivation. You will take on tasks that may make you feel small and incapable, or demons that whisper in your ear, “This is too hard. You should give up”

Data science is a sexy job. The salaries are high, the work is interesting, and there’s significant prestige that comes with the title. As a result, MANY people want to be data scientists.

Unfortunately, even if you are passionate about data science, and can do the work really well, you can’t force yourself to love the process. And this leads to some unsettling advice for aspiring data scientists.

You can be fascinated by data science, but if you hate the day-to-day tasks and feelings that come with it, it will be very difficult to maintain your motivation.

For most people starting out, it may take months before you actually get to the “doing” phase of your education. (Where you actually build full-scale data science projects.) And at that point, realizing that you hate the process can be a heavy personal blow. To save you the trouble, I have compiled a list of some common frustrations that data scientists face.

These are some of the tasks and feelings you will need to be comfortable with if you choose to pursue a career in data science:

Feelings:

• The feeling of never being done with learning.
• The feeling of being out of your depth/overwhelmed.
• The feeling of failing many, many times to get one success.
• The feeling of having something you spent weeks on, fail or be ignored.

Tasks:

• Teaching yourself a skill that you have zero knowledge of.
• Spending dozens of hours to answer a single, seemingly simple, question.
• Comparing yourself to (seemingly) more successful people.
• Communicating with people who don’t understand (or care about) data science.
• Doing work that is 95% preparation, and 5% execution.
• Doing a lot of work that is not “sexy”. (Database work, data munging,…)
• Coding…. a lot of coding.

My advice: Do your research before you jump in.

Data science is an awesome profession, but there are definitely some serious frustrations that come with it.

For the aspiring data scientist, I encourage you to learn more about the tools and tasks a normal data scientist does before you commit to a career in data science.

A little bit of research, in the beginning, will drastically increase your chances of following through on your educational journey.

Learn how to Deal with Anxiety.

When you start researching how to become a data scientist, you will discover an unfortunate fact about the profession. Namely, that becoming a data scientist requires knowledge of a broad and deep set of tools, technologies, and skills. All of which makes the prospect of becoming a data scientist VERY intimidating.

You might start asking questions like: Do I have to go back to school and get a Ph. D.? How do I get these skills without work experience? Am I even capable of learning all of this?

When you set out on your journey towards data science, you will feel a lot of anxiety and stress. This is a totally normal reaction and everyone who has been in your shoes has felt the same way.

Just know that this time at the beginning of your educational journey is absolutely crucial to your long-term success. The actions that you take in these first few weeks will determine what habits you set for yourself, and as a result, will determine how you will deal with the negative effects of stress and anxiety throughout your journey.

If you can find healthy ways to deal with stress and anxiety from the very start, your confidence and motivation will become unshakeable as time goes on.

However, there is a danger here that needs to be addressed. It is absolutely critical that during this time you avoid unhealthy ways of coping with negative stressors.

Unfortunately what is healthy and unhealthy can depend a lot on who you are as a person. But in my own journey, I have recognized a few unhealthy coping mechanisms that have damaged my motivation in the past.

Here are a few of the unhealthy ways to deal with stress that you should avoid.

Avoiding being overwhelmed: Buying an all-inclusive course or textbook.

This one has really tripped me up in the past. Whenever I start to feel overwhelmed by the sheer volume of things I need to learn, I feel a strong urge to give up on teaching myself, and buy into someone else's lesson-plan.

If I do end up buying the all-inclusive course or textbook, learning starts to feel like a chore that someone else has tasked me with. Worse still, because I haven’t had to put effort into planning what I need to learn, I become disconnected from why I am learning a particular skill or concept in the first place. The result? Whenever I buy an online course, my motivation to learn quickly tanks.

Why you should avoid this: Even if you can learn well from someone else’s curriculum, I would still advise against it. Why? Because the most important skill you can learn on your journey towards data science is being able to teach yourself.

Teaching yourself is the process of identifying holes in your skillset, researching new technologies to close that gap, and making an actionable plan to acquire that skill. If you have relied solely on hand-holdy courses during your journey, you will have much less experience with this process.

That can be really bad as time goes on. When you actually get the job, you may be tasked with a very unique, domain-specific, problem that you have little experience with. And if there isn’t a MOOC or textbook that can teach you the skills you need, you will have a VERY hard time.

Avoiding Stress: Putting it off, or designating a single day for study.

The worst mistake you can possibly make during the beginning of your journey is to put off learning. It doesn’t matter if you feel like you are too busy, if you are going to be successful on your journey you will need to set aside time each day to learn.

If you don’t practice and learn daily your motivation will quickly fade and you will inevitably lose interest in a potentially fulfilling career.

Why you should avoid this: Pursuing data science is a marathon, not a sprint. The skill set required for the job is so diverse, it can only really be acquired through consistent effort over a long period of time. If you try to learn in short bursts, you will eventually exhaust yourself and extinguish your motivation to go on.

Worse still, if you put off your learning until you feel like you have time, you will probably never even embark on your journey. And, if you do, you will have cemented in your mind the idea that learning is something that you do when time permits. In data science, that mindset is a quick end to a career.

My advice: Set healthy habits, early on.

Whether you are working full-time and want to make a career pivot, or are studying at a university and want to follow a career path that excites you; Either way you need to find healthy habits that allow you to overcome stress.

A few healthy habits you can set from the beginning:

• Set time aside every day to learn something new.
• Try to get connected in the data science community. You’d be surprised how many people will relate to your feelings of anxiety.
• If you feel exhausted and anxious from learning, take some time off and build a project with something you have learned recently. This is a great way to de-stress and reconnect with why you are learning in the first place!

I hope this helps, please don’t hesitate to let me know if you have any other questions.