A few days ago, my friend approached me to help her edit a video she had been working on. It was for a college assignment.

She told me that her free tier of the video editing service was ending in two days, and that she needed to finish it as soon as possible.

I asked her why she didn’t just purchase a subscription instead, as it was only a few dollars.

Her answer surprised me.

She said that the two day deadline was her motivation to complete the video as fast as she could.

Otherwise, she would end up taking weeks to finish it.

We all need a good reason to get something done. In school, we had to complete our homework so we wouldn’t get punished.

In college, we had to submit assignments on time if we wanted to pass the subject.

At work, every task needs to be completed by the deadline.

We do these things because we have to. Because if we don’t, we know that the consequences will be terrible.

I used to pull all-nighters at school on the day before the exam to cram all the material in one night.

The only reason I did that was to get good grades.

If we weren’t graded on tests or assignments, I simply wouldn’t have put that much effort into learning the material. I probably wouldn’t even have opened my textbook for the entire school year.

We spend almost our entire lives doing things because we have to. We finish things because we have deadlines, and we want good grades.

And that’s what makes the self study route so difficult.

When you are teaching yourself, there is no competition, and no deadline.

Staying motivated to complete things on your own initiative is hard, because there is no consequence if you don’t get things done.

However, if done right, self-learning is arguably one of the most effective forms of studying.

There may be no teacher or guidance, but you are learning something simply out of interest. You are learning material that you truly want to understand, rather than being forced to cram it to meet a deadline.

As I have mentioned in my previous articles, I have taken the self-study route to teach myself programming and data science.

My learning is far from complete, but I would like to share a few techniques I use to stay motivated.

In this article, I am going to give you a few tips to make self-study more effective. It is possible to learn new skills and enhance them with time, as long as you keep your focus.

Long-term goals

Long-term goals are things you want to achieve in a couple of years. It could be something like:

• Becoming a data scientist
• Mastering a programming language
• Becoming an expert at machine-learning

Everything I listed above are long-term goals. They are the reason you have embarked on your journey of self-learning, and are your main source of motivation to keep going.

However, long-term goals are years away. They are too big. If you don’t break them down properly, you may end up never getting there.

Short-term goals

I like to chunk long term goals down into short term goals (around 2–5 months). For example, if my long-term goal is to get really good at a programming language, then my short-term goal will be to complete a project in that language.

Here’s what short term goals look like:

• Create an end-to-end machine learning model in Python on disease classification, and visualize the model on a dashboard.
• Finish reading a textbook on sentiment analysis
• Complete a statistics course to build a good foundation for data science

All of these are short-term goals. They are a breakdown of your short term goal into smaller tasks.

When doing a project like the one above, you will gain a much better grasp of the different areas in data science. By the end of it, you would have a much better working knowledge of Python, and an understanding of data visualization tools.

Short-term and long-term goals go hand in hand, and you can think of short-term goals as a way of working towards your long-term goal.

Measuring progress

You need a way to keep track of both your long-term and short-term goals. I suggest chunking your short-term goals down into weekly tasks, so that your work is spread out evenly.

In order to measure progress, I suggest using one (or all) of these things:

• To-do list app
• Keep a checklist
• A vision board
• A timetable

You can use a to-do list or a checklist to ensure you finish every task by the deadline. A vision board is generally used for long-term goals. You can stick a vision board on your wall so that you can wake up and look at it every morning.

A timetable is useful for planning out every event in your day from the time you wake up.

Elon Musk usually plans his day ahead.

From waking up in the morning to going to bed at night, all the tasks that he wants to get done are planned the day before.

This is something I strongly suggest you try out. You won’t need to waste any time deciding what to do next. Instead, you can simply focus on the task at hand.

Passion and discipline

According to Lex Fridman, an AI researcher at MIT, passion and discipline go hand in hand.

We usually start doing things out of passion, such as learning how to code, or building new things.

And while passion helps you get started, it does disappear at times.

Sometimes, you might wake up in the morning feeling demotivated and completely disinterested in continuing. There might be times you feel like you’ve barely learnt anything at all, and you don’t feel like going on.

It is at these times — the times that passion fails us, that discipline becomes our saving grace.

You need to have the discipline to create a daily schedule (for example: study for five hours a day).

And even when you don’t feel like it, you need to have the discipline to keep to the schedule.

Discipline carries you through the difficult parts, and ensures that you stick to what you started even when passion fails you.

It isn’t possible to continuously be passionate about learning something. When working on a particularly difficult problem, it is easy to give up and not want to look at it anymore. It is easy to get demotivated.

If you are working on a college assignment, or studying for an exam, you will persevere through the difficult parts simply because you have to. You have to, otherwise you might fail.

When self-studying, there is no consequence to giving up. However, it is equally important to get through these difficult parts. The only way to do this is with discipline, and by holding yourself accountable.

Cultivate a Habit

When in school, I would always start studying the week before the exam. That was when the material stuck to my mind, and I wouldn’t forget.

However, it took me some time to realize that learning a new concept and studying for an exam were two completely different things.

If your goal is to learn how to code, or to learn data science, you will need to make a habit out of learning.

You should do it every day, at least for a few years, until you have achieved a level of competence such that it becomes second nature to you.

It is better to do something everyday for one minute than to do it once a year for an entire day.

If you are someone who wants to learn how to code, but has a full time job, then you probably dedicate your time to study on the weekend.

My advice would be to spend an additional hour programming once you come back from work.

If you’re unable to spend an entire hour, try doing 20 minutes.

This may not seem like much, but it will help you cultivate the habit of programming everyday.

Once you find yourself getting into this habit, the 20 minutes may turn into something longer, and programming will slowly start to feel like second nature to you.

Minimize all distractions

No phones on the study table.

Every time my phone is with me, I feel the urge to continuously check all my social media accounts every ten minutes.

Your phone is your biggest distraction, and different people take different approaches to deal with this.

Some people don’t use social media at all, because it is addictive and time consuming. Others set a limit for the amount of screen time they can have each day, and don’t exceed that limit.

In my case, I prefer to simply not have my phone with me while I’m studying.

It takes quite long to gain momentum when studying or working, but it is very easy to get distracted when there is a disruption.

If you have planned to study for five hours, then it is better to keep your phone out of the room for the entire five hours. You can also keep your phone on “do not disturb” or set your account status to “busy” so you don’t get calls or messages during this time.

Do things you’re excited about

Constantly learning material from a textbook and trying to understand new concepts can be difficult.

In my learning, I always sprinkle in something I am excited about, that gives me a reason to keep learning.

If I start to study the underlying concepts behind neural networks, I give myself an exciting goal to look forward to, such as

• Creating a GAN (Generative Adversarial Network) to generate realistic celebrity faces, and ask people to guess who they think it is

These are some small, exciting goals that keep me going when the learning gets boring. I know once I’m done that I will be able to have fun with the concepts I learnt, and build something cool with it.

I like to think of this as reward-based learning. Every time I learn something new, I get a fun project out of it.

Starting something new on your own and sticking to it can be difficult, especially when things get hard.

However, if you work towards your goal everyday and have the discipline to carry you through the difficult times, you will be able to master new skills easily.

Becoming really good at fields like data science and programming takes time and effort. If you are willing to put in that time and effort on your own with no deadlines or external motivation, you will be able to go very far.

I was an ordinary person who studied hard. There are no miracle people. It happens they get interested in this thing, and they learn all this stuff, but they’re just people. — Richard Feynman

Note

If you are a beginner in the data industry and are confused about the different career options, don't know how to start learning data science, or are looking to land a data science job, you can schedule a 30 minute or 1 hour consultation session with me here: https://lnkd.in/gURAj82